diff --git accumulo-handler/src/test/results/positive/accumulo_predicate_pushdown.q.out accumulo-handler/src/test/results/positive/accumulo_predicate_pushdown.q.out index 197d3bae0e..3a0b34c3a5 100644 --- accumulo-handler/src/test/results/positive/accumulo_predicate_pushdown.q.out +++ accumulo-handler/src/test/results/positive/accumulo_predicate_pushdown.q.out @@ -414,10 +414,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: accumulo_pushdown - filterExpr: (not COALESCE((key < '90'),false)) (type: boolean) + filterExpr: (key < '90') is not true (type: boolean) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Filter Operator - predicate: (not COALESCE((key < '90'),false)) (type: boolean) + predicate: (key < '90') is not true (type: boolean) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Select Operator expressions: key (type: string), value (type: string) diff --git hbase-handler/src/test/results/positive/hbase_ppd_key_range.q.out hbase-handler/src/test/results/positive/hbase_ppd_key_range.q.out index dcfe7c72ba..78fa53f226 100644 --- hbase-handler/src/test/results/positive/hbase_ppd_key_range.q.out +++ hbase-handler/src/test/results/positive/hbase_ppd_key_range.q.out @@ -416,7 +416,7 @@ STAGE PLANS: alias: hbase_pushdown Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Filter Operator - predicate: (not COALESCE((key < '90'),false)) (type: boolean) + predicate: (key < '90') is not true (type: boolean) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Select Operator expressions: key (type: string), value (type: string) diff --git hbase-handler/src/test/results/positive/hbase_pushdown.q.out hbase-handler/src/test/results/positive/hbase_pushdown.q.out index e81442339a..255009678d 100644 --- hbase-handler/src/test/results/positive/hbase_pushdown.q.out +++ hbase-handler/src/test/results/positive/hbase_pushdown.q.out @@ -305,7 +305,7 @@ STAGE PLANS: alias: hbase_pushdown Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Filter Operator - predicate: (not COALESCE((key = 90),false)) (type: boolean) + predicate: (key = 90) is not true (type: boolean) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Select Operator expressions: key (type: int), value (type: string) diff --git pom.xml pom.xml index 9871bae60e..994fcbcd61 100644 --- pom.xml +++ pom.xml @@ -127,7 +127,7 @@ 1.12.0 1.8.2 0.8.0.RELEASE - 1.17.0 + 1.18.0 4.2.4 4.1.17 4.1.19 diff --git ql/src/test/results/clientpositive/alter_partition_coltype.q.out ql/src/test/results/clientpositive/alter_partition_coltype.q.out index d484f9e223..7cc50366f5 100644 --- ql/src/test/results/clientpositive/alter_partition_coltype.q.out +++ ql/src/test/results/clientpositive/alter_partition_coltype.q.out @@ -571,6 +571,9 @@ POSTHOOK: type: QUERY POSTHOOK: Input: pt@alterdynamic_part_table POSTHOOK: Input: pt@alterdynamic_part_table@partcol1=2/partcol2=1 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `intcol` +FROM `pt`.`alterdynamic_part_table` +WHERE ROW(`partcol1`, `partcol2`) IN (ROW(2, '1'), ROW(1, '__HIVE_DEFAULT_PARTITION__')) STAGE DEPENDENCIES: Stage-0 is a root stage diff --git ql/src/test/results/clientpositive/ambiguitycheck.q.out ql/src/test/results/clientpositive/ambiguitycheck.q.out index aff57522e3..fb9bf5c92f 100644 --- ql/src/test/results/clientpositive/ambiguitycheck.q.out +++ ql/src/test/results/clientpositive/ambiguitycheck.q.out @@ -709,7 +709,7 @@ POSTHOOK: query: explain extended select int(1.2) from src limit 1 POSTHOOK: type: QUERY POSTHOOK: Input: default@src #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST(1.2 AS INTEGER) AS `$f0` +OPTIMIZED SQL: SELECT CAST(1.2 AS INTEGER) AS `_o__c0` FROM `default`.`src` LIMIT 1 STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/annotate_stats_filter.q.out ql/src/test/results/clientpositive/annotate_stats_filter.q.out index 44f77b8f50..957fd1262d 100644 --- ql/src/test/results/clientpositive/annotate_stats_filter.q.out +++ ql/src/test/results/clientpositive/annotate_stats_filter.q.out @@ -845,18 +845,18 @@ STAGE PLANS: Map Operator Tree: TableScan alias: loc_orc - filterExpr: (((year = 2001) and year is null) or (state = 'CA')) (type: boolean) + filterExpr: (state = 'CA') (type: boolean) Statistics: Num rows: 8 Data size: 816 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: (((year = 2001) and year is null) or (state = 'CA')) (type: boolean) - Statistics: Num rows: 2 Data size: 204 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (state = 'CA') (type: boolean) + Statistics: Num rows: 1 Data size: 102 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: state (type: string), locid (type: int), zip (type: bigint), year (type: int) + expressions: 'CA' (type: string), locid (type: int), zip (type: bigint), year (type: int) outputColumnNames: _col0, _col1, _col2, _col3 - Statistics: Num rows: 2 Data size: 204 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 1 Data size: 102 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 2 Data size: 204 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 1 Data size: 102 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat diff --git ql/src/test/results/clientpositive/cbo_rp_simple_select.q.out ql/src/test/results/clientpositive/cbo_rp_simple_select.q.out index cb22b61f26..96ac1255d0 100644 --- ql/src/test/results/clientpositive/cbo_rp_simple_select.q.out +++ ql/src/test/results/clientpositive/cbo_rp_simple_select.q.out @@ -761,18 +761,18 @@ STAGE PLANS: Map Operator Tree: TableScan alias: cbo_t2 - filterExpr: (c_int = c_int) (type: boolean) + filterExpr: c_int is not null (type: boolean) Statistics: Num rows: 20 Data size: 7138 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: (c_int = c_int) (type: boolean) - Statistics: Num rows: 10 Data size: 3660 Basic stats: COMPLETE Column stats: COMPLETE + predicate: c_int is not null (type: boolean) + Statistics: Num rows: 18 Data size: 6406 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) outputColumnNames: key, value, c_int, c_float, c_boolean, dt - Statistics: Num rows: 10 Data size: 3660 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 18 Data size: 6406 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 10 Data size: 3660 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 18 Data size: 6406 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -853,18 +853,18 @@ STAGE PLANS: Map Operator Tree: TableScan alias: cbo_t2 - filterExpr: (c_int = c_int) (type: boolean) + filterExpr: c_int is not null (type: boolean) Statistics: Num rows: 20 Data size: 7138 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: (c_int = c_int) (type: boolean) - Statistics: Num rows: 10 Data size: 3660 Basic stats: COMPLETE Column stats: COMPLETE + predicate: c_int is not null (type: boolean) + Statistics: Num rows: 18 Data size: 6406 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) outputColumnNames: key, value, c_int, c_float, c_boolean, dt - Statistics: Num rows: 10 Data size: 3660 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 18 Data size: 6406 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 10 Data size: 3660 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 18 Data size: 6406 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -881,47 +881,31 @@ PREHOOK: query: -- c_int is not null EXPLAIN select * from cbo_t2 where (cbo_t2.c_int) IN (NULL) PREHOOK: type: QUERY PREHOOK: Input: default@cbo_t2 -PREHOOK: Input: default@cbo_t2@dt=2014 #### A masked pattern was here #### POSTHOOK: query: -- c_int is not null EXPLAIN select * from cbo_t2 where (cbo_t2.c_int) IN (NULL) POSTHOOK: type: QUERY POSTHOOK: Input: default@cbo_t2 -POSTHOOK: Input: default@cbo_t2@dt=2014 #### A masked pattern was here #### STAGE DEPENDENCIES: - Stage-1 is a root stage - Stage-0 depends on stages: Stage-1 + Stage-0 is a root stage STAGE PLANS: - Stage: Stage-1 - Map Reduce - Map Operator Tree: - TableScan - alias: cbo_t2 - filterExpr: (c_int = null) (type: boolean) - Statistics: Num rows: 20 Data size: 7138 Basic stats: COMPLETE Column stats: COMPLETE - Filter Operator - predicate: (c_int = null) (type: boolean) - Statistics: Num rows: 10 Data size: 3660 Basic stats: COMPLETE Column stats: COMPLETE - Select Operator - expressions: key (type: string), value (type: string), null (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) - outputColumnNames: key, value, c_int, c_float, c_boolean, dt - Statistics: Num rows: 10 Data size: 3624 Basic stats: COMPLETE Column stats: COMPLETE - File Output Operator - compressed: false - Statistics: Num rows: 10 Data size: 3624 Basic stats: COMPLETE Column stats: COMPLETE - table: - input format: org.apache.hadoop.mapred.SequenceFileInputFormat - output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat - serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe - Execution mode: vectorized - Stage: Stage-0 Fetch Operator limit: -1 Processor Tree: - ListSink + TableScan + alias: cbo_t2 + Statistics: Num rows: 1 Data size: 564 Basic stats: COMPLETE Column stats: PARTIAL + Filter Operator + predicate: false (type: boolean) + Statistics: Num rows: 1 Data size: 564 Basic stats: COMPLETE Column stats: PARTIAL + Select Operator + expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) + outputColumnNames: key, value, c_int, c_float, c_boolean, dt + Statistics: Num rows: 1 Data size: 564 Basic stats: COMPLETE Column stats: PARTIAL + ListSink PREHOOK: query: -- rewrite to NULL EXPLAIN select * from cbo_t2 where (cbo_t2.c_int) IN (cbo_t2.c_int, 2*cbo_t2.c_int) @@ -945,10 +929,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: cbo_t2 - filterExpr: ((c_int = c_int) or (c_int = (2 * c_int))) (type: boolean) + filterExpr: (c_int is not null or (c_int = (2 * c_int))) (type: boolean) Statistics: Num rows: 20 Data size: 7138 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((c_int = (2 * c_int)) or (c_int = c_int)) (type: boolean) + predicate: ((c_int = (2 * c_int)) or c_int is not null) (type: boolean) Statistics: Num rows: 20 Data size: 7138 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) @@ -991,10 +975,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: cbo_t2 - filterExpr: ((c_int = c_int) or (c_int = 0)) (type: boolean) + filterExpr: (c_int is not null or (c_int = 0)) (type: boolean) Statistics: Num rows: 20 Data size: 7138 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((c_int = 0) or (c_int = c_int)) (type: boolean) + predicate: ((c_int = 0) or c_int is not null) (type: boolean) Statistics: Num rows: 20 Data size: 7138 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) diff --git ql/src/test/results/clientpositive/cbo_simple_select.q.out ql/src/test/results/clientpositive/cbo_simple_select.q.out index 32e69204f6..8beaecfcb1 100644 --- ql/src/test/results/clientpositive/cbo_simple_select.q.out +++ ql/src/test/results/clientpositive/cbo_simple_select.q.out @@ -761,18 +761,18 @@ STAGE PLANS: Map Operator Tree: TableScan alias: cbo_t2 - filterExpr: (c_int = c_int) (type: boolean) + filterExpr: c_int is not null (type: boolean) Statistics: Num rows: 20 Data size: 7138 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: (c_int = c_int) (type: boolean) - Statistics: Num rows: 10 Data size: 3660 Basic stats: COMPLETE Column stats: COMPLETE + predicate: c_int is not null (type: boolean) + Statistics: Num rows: 18 Data size: 6406 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 - Statistics: Num rows: 10 Data size: 3660 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 18 Data size: 6406 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 10 Data size: 3660 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 18 Data size: 6406 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -853,18 +853,18 @@ STAGE PLANS: Map Operator Tree: TableScan alias: cbo_t2 - filterExpr: (c_int = c_int) (type: boolean) + filterExpr: c_int is not null (type: boolean) Statistics: Num rows: 20 Data size: 7138 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: (c_int = c_int) (type: boolean) - Statistics: Num rows: 10 Data size: 3660 Basic stats: COMPLETE Column stats: COMPLETE + predicate: c_int is not null (type: boolean) + Statistics: Num rows: 18 Data size: 6406 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 - Statistics: Num rows: 10 Data size: 3660 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 18 Data size: 6406 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 10 Data size: 3660 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 18 Data size: 6406 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -881,47 +881,31 @@ PREHOOK: query: -- c_int is not null EXPLAIN select * from cbo_t2 where (cbo_t2.c_int) IN (NULL) PREHOOK: type: QUERY PREHOOK: Input: default@cbo_t2 -PREHOOK: Input: default@cbo_t2@dt=2014 #### A masked pattern was here #### POSTHOOK: query: -- c_int is not null EXPLAIN select * from cbo_t2 where (cbo_t2.c_int) IN (NULL) POSTHOOK: type: QUERY POSTHOOK: Input: default@cbo_t2 -POSTHOOK: Input: default@cbo_t2@dt=2014 #### A masked pattern was here #### STAGE DEPENDENCIES: - Stage-1 is a root stage - Stage-0 depends on stages: Stage-1 + Stage-0 is a root stage STAGE PLANS: - Stage: Stage-1 - Map Reduce - Map Operator Tree: - TableScan - alias: cbo_t2 - filterExpr: (c_int = null) (type: boolean) - Statistics: Num rows: 20 Data size: 7138 Basic stats: COMPLETE Column stats: COMPLETE - Filter Operator - predicate: (c_int = null) (type: boolean) - Statistics: Num rows: 10 Data size: 3660 Basic stats: COMPLETE Column stats: COMPLETE - Select Operator - expressions: key (type: string), value (type: string), null (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) - outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 - Statistics: Num rows: 10 Data size: 3624 Basic stats: COMPLETE Column stats: COMPLETE - File Output Operator - compressed: false - Statistics: Num rows: 10 Data size: 3624 Basic stats: COMPLETE Column stats: COMPLETE - table: - input format: org.apache.hadoop.mapred.SequenceFileInputFormat - output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat - serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe - Execution mode: vectorized - Stage: Stage-0 Fetch Operator limit: -1 Processor Tree: - ListSink + TableScan + alias: cbo_t2 + Statistics: Num rows: 1 Data size: 564 Basic stats: COMPLETE Column stats: PARTIAL + Filter Operator + predicate: false (type: boolean) + Statistics: Num rows: 1 Data size: 564 Basic stats: COMPLETE Column stats: PARTIAL + Select Operator + expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 + Statistics: Num rows: 1 Data size: 564 Basic stats: COMPLETE Column stats: PARTIAL + ListSink PREHOOK: query: -- rewrite to NULL EXPLAIN select * from cbo_t2 where (cbo_t2.c_int) IN (cbo_t2.c_int, 2*cbo_t2.c_int) @@ -945,10 +929,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: cbo_t2 - filterExpr: ((c_int = c_int) or (c_int = (2 * c_int))) (type: boolean) + filterExpr: (c_int is not null or (c_int = (2 * c_int))) (type: boolean) Statistics: Num rows: 20 Data size: 7138 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((c_int = (2 * c_int)) or (c_int = c_int)) (type: boolean) + predicate: ((c_int = (2 * c_int)) or c_int is not null) (type: boolean) Statistics: Num rows: 20 Data size: 7138 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) @@ -991,10 +975,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: cbo_t2 - filterExpr: ((c_int = c_int) or (c_int = 0)) (type: boolean) + filterExpr: (c_int is not null or (c_int = 0)) (type: boolean) Statistics: Num rows: 20 Data size: 7138 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((c_int = 0) or (c_int = c_int)) (type: boolean) + predicate: ((c_int = 0) or c_int is not null) (type: boolean) Statistics: Num rows: 20 Data size: 7138 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) diff --git ql/src/test/results/clientpositive/complex_alias.q.out ql/src/test/results/clientpositive/complex_alias.q.out index f9315f8045..f6688defaf 100644 --- ql/src/test/results/clientpositive/complex_alias.q.out +++ ql/src/test/results/clientpositive/complex_alias.q.out @@ -147,10 +147,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: agg1 - filterExpr: (col0 = col0) (type: boolean) + filterExpr: col0 is not null (type: boolean) Statistics: Num rows: 1 Data size: 17 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (col0 = col0) (type: boolean) + predicate: col0 is not null (type: boolean) Statistics: Num rows: 1 Data size: 17 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: '42' (type: string), col0 (type: int) @@ -170,10 +170,10 @@ STAGE PLANS: Statistics: Num rows: 2 Data size: 34 Basic stats: COMPLETE Column stats: NONE TableScan alias: agg1 - filterExpr: (col0 = col0) (type: boolean) + filterExpr: col0 is not null (type: boolean) Statistics: Num rows: 1 Data size: 17 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (col0 = col0) (type: boolean) + predicate: col0 is not null (type: boolean) Statistics: Num rows: 1 Data size: 17 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: '41' (type: string), col0 (type: int) diff --git ql/src/test/results/clientpositive/constantPropWhen.q.out ql/src/test/results/clientpositive/constantPropWhen.q.out index 5fb2a4b7e8..95c329695c 100644 --- ql/src/test/results/clientpositive/constantPropWhen.q.out +++ ql/src/test/results/clientpositive/constantPropWhen.q.out @@ -40,7 +40,7 @@ STAGE PLANS: alias: test_1_n4 Statistics: Num rows: 4 Data size: 24 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: (not COALESCE((id = id2),false)) (type: boolean) + expressions: (id = id2) is not true (type: boolean) outputColumnNames: _col0 Statistics: Num rows: 4 Data size: 24 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -90,7 +90,7 @@ STAGE PLANS: alias: test_1_n4 Statistics: Num rows: 4 Data size: 24 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: (not COALESCE((id = id2),false)) (type: boolean) + expressions: (id = id2) is not true (type: boolean) outputColumnNames: _col0 Statistics: Num rows: 4 Data size: 24 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -140,7 +140,7 @@ STAGE PLANS: alias: test_1_n4 Statistics: Num rows: 4 Data size: 24 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: COALESCE((id = id2),false) (type: boolean) + expressions: (id = id2) is true (type: boolean) outputColumnNames: _col0 Statistics: Num rows: 4 Data size: 24 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -190,7 +190,7 @@ STAGE PLANS: alias: test_1_n4 Statistics: Num rows: 4 Data size: 24 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: COALESCE((id = id2),false) (type: boolean) + expressions: (id = id2) is true (type: boolean) outputColumnNames: _col0 Statistics: Num rows: 4 Data size: 24 Basic stats: COMPLETE Column stats: NONE File Output Operator diff --git ql/src/test/results/clientpositive/constantPropagateForSubQuery.q.out ql/src/test/results/clientpositive/constantPropagateForSubQuery.q.out index 221837b410..6bd04e18ab 100644 --- ql/src/test/results/clientpositive/constantPropagateForSubQuery.q.out +++ ql/src/test/results/clientpositive/constantPropagateForSubQuery.q.out @@ -11,7 +11,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@src POSTHOOK: Input: default@src1 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('429' AS STRING) AS `ak`, `t0`.`value` AS `av`, `t1`.`key` AS `bk`, `t1`.`value` AS `bv` +OPTIMIZED SQL: SELECT CAST('429' AS VARCHAR(65536)) AS `ak`, `t0`.`value` AS `av`, `t1`.`key` AS `bk`, `t1`.`value` AS `bv` FROM (SELECT `value` FROM `default`.`src` WHERE `key` = '429') AS `t0`, diff --git ql/src/test/results/clientpositive/constant_prop_3.q.out ql/src/test/results/clientpositive/constant_prop_3.q.out index 2b314d7ebd..b783a41a5b 100644 --- ql/src/test/results/clientpositive/constant_prop_3.q.out +++ ql/src/test/results/clientpositive/constant_prop_3.q.out @@ -283,7 +283,7 @@ STAGE PLANS: outputColumnNames: _col1, _col3, _col4, _col5, _col6, _col7, _col9 Statistics: Num rows: 1 Data size: 18 Basic stats: PARTIAL Column stats: NONE Filter Operator - predicate: ((_col6 = 0L) or (_col9 is null and _col1 is not null and (_col7 >= _col6))) (type: boolean) + predicate: (((_col7 >= _col6) or (_col6 = 0L) or _col9 is not null or _col1 is null) and (_col1 is not null or (_col6 = 0L) or _col9 is not null) and (_col9 is null or (_col6 = 0L))) (type: boolean) Statistics: Num rows: 1 Data size: 18 Basic stats: PARTIAL Column stats: NONE Select Operator expressions: _col1 (type: int), _col3 (type: string), _col4 (type: string), _col5 (type: int) diff --git ql/src/test/results/clientpositive/constprog_when_case.q.out ql/src/test/results/clientpositive/constprog_when_case.q.out index d237f135ac..bc98a3a06c 100644 --- ql/src/test/results/clientpositive/constprog_when_case.q.out +++ ql/src/test/results/clientpositive/constprog_when_case.q.out @@ -50,7 +50,7 @@ STAGE PLANS: alias: src_orc Statistics: Num rows: 1000 Data size: 266000 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: if(CASE WHEN (bool0) THEN (true) WHEN ((not bool0)) THEN (false) ELSE (null) END, key0, if(CASE WHEN (bool0) THEN (false) WHEN ((not bool0)) THEN (true) ELSE (null) END, key1, key2)) (type: string) + expressions: if(CASE WHEN (true) THEN (CASE WHEN (bool0) THEN (true) WHEN ((not bool0)) THEN (false) ELSE (null) END) WHEN (false) THEN (CASE WHEN (bool0) THEN (false) WHEN ((not bool0)) THEN (true) ELSE (null) END) ELSE (CASE WHEN (bool0) THEN (null) WHEN ((not bool0)) THEN (null) ELSE (null) END) END, key0, if(CASE WHEN (false) THEN (CASE WHEN (bool0) THEN (true) WHEN ((not bool0)) THEN (false) ELSE (null) END) WHEN (true) THEN (CASE WHEN (bool0) THEN (false) WHEN ((not bool0)) THEN (true) ELSE (null) END) ELSE (CASE WHEN (bool0) THEN (null) WHEN ((not bool0)) THEN (null) ELSE (null) END) END, key1, key2)) (type: string) outputColumnNames: _col0 Statistics: Num rows: 1000 Data size: 266000 Basic stats: COMPLETE Column stats: NONE File Output Operator diff --git ql/src/test/results/clientpositive/decimal_udf.q.out ql/src/test/results/clientpositive/decimal_udf.q.out index 3ef40023eb..4b61fdd627 100644 --- ql/src/test/results/clientpositive/decimal_udf.q.out +++ ql/src/test/results/clientpositive/decimal_udf.q.out @@ -991,14 +991,14 @@ STAGE PLANS: Processor Tree: TableScan alias: decimal_udf - Statistics: Num rows: 1 Data size: 3590 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 3590 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: (UDFToDouble(key) / null) (type: double) + expressions: null (type: double) outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 3590 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE Limit Number of rows: 1 - Statistics: Num rows: 1 Data size: 3590 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE ListSink PREHOOK: query: SELECT key / NULL FROM DECIMAL_UDF limit 1 diff --git ql/src/test/results/clientpositive/druid/druidmini_extractTime.q.out ql/src/test/results/clientpositive/druid/druidmini_extractTime.q.out index 4ea95f6930..30ed7a28c2 100644 --- ql/src/test/results/clientpositive/druid/druidmini_extractTime.q.out +++ ql/src/test/results/clientpositive/druid/druidmini_extractTime.q.out @@ -589,7 +589,7 @@ STAGE PLANS: properties: druid.fieldNames vc,vc0,vc1 druid.fieldTypes double,int,string - druid.query.json {"queryType":"scan","dataSource":"default.druid_table_alltypesorc","intervals":["1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z"],"filter":{"type":"and","fields":[{"type":"expression","expression":"(((CAST(timestamp_extract(\"__time\",'MONTH','US/Pacific'), 'DOUBLE') / 4) + 1) == 4)"},{"type":"bound","dimension":"__time","lower":"11","lowerStrict":false,"upper":"12","upperStrict":false,"ordering":"numeric","extractionFn":{"type":"timeFormat","format":"M","timeZone":"US/Pacific","locale":"en-US"}}]},"virtualColumns":[{"type":"expression","name":"vc","expression":"((CAST(timestamp_extract(\"__time\",'MONTH','US/Pacific'), 'DOUBLE') / CAST(4, 'DOUBLE')) + CAST(1, 'DOUBLE'))","outputType":"DOUBLE"},{"type":"expression","name":"vc0","expression":"timestamp_extract(\"__time\",'MONTH','US/Pacific')","outputType":"LONG"},{"type":"expression","name":"vc1","expression":"substring(timestamp_format(timestamp_floor(timestamp_parse(timestamp_format(\"__time\",'yyyy-MM-dd\\u0027T\\u0027HH:mm:ss.SSS\\u0027Z\\u0027','US/Pacific'),'','UTC'),'P1D','','UTC'),'yyyy-MM-dd','UTC'), 5, 2)","outputType":"STRING"}],"columns":["vc","vc0","vc1"],"resultFormat":"compactedList","limit":1} + druid.query.json {"queryType":"scan","dataSource":"default.druid_table_alltypesorc","intervals":["1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z"],"filter":{"type":"and","fields":[{"type":"expression","expression":"(((CAST(timestamp_extract(\"__time\",'MONTH','US/Pacific'), 'DOUBLE') / CAST(4, 'DOUBLE')) + CAST(1, 'DOUBLE')) == 4)"},{"type":"bound","dimension":"__time","lower":"11","lowerStrict":false,"upper":"12","upperStrict":false,"ordering":"numeric","extractionFn":{"type":"timeFormat","format":"M","timeZone":"US/Pacific","locale":"en-US"}}]},"virtualColumns":[{"type":"expression","name":"vc","expression":"4","outputType":"DOUBLE"},{"type":"expression","name":"vc0","expression":"timestamp_extract(\"__time\",'MONTH','US/Pacific')","outputType":"LONG"},{"type":"expression","name":"vc1","expression":"substring(timestamp_format(timestamp_floor(timestamp_parse(timestamp_format(\"__time\",'yyyy-MM-dd\\u0027T\\u0027HH:mm:ss.SSS\\u0027Z\\u0027','US/Pacific'),'','UTC'),'P1D','','UTC'),'yyyy-MM-dd','UTC'), 5, 2)","outputType":"STRING"}],"columns":["vc","vc0","vc1"],"resultFormat":"compactedList","limit":1} druid.query.type scan Select Operator expressions: vc (type: double), vc0 (type: int), vc1 (type: string) @@ -630,7 +630,7 @@ STAGE PLANS: properties: druid.fieldNames vc,vc0 druid.fieldTypes int,double - druid.query.json {"queryType":"scan","dataSource":"default.druid_table_alltypesorc","intervals":["1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z"],"filter":{"type":"and","fields":[{"type":"expression","expression":"(timestamp_extract(\"__time\",'QUARTER','US/Pacific') >= 4)"},{"type":"expression","expression":"(((CAST(timestamp_extract(\"__time\",'MONTH','US/Pacific'), 'DOUBLE') / 4) + 1) == 4)"}]},"virtualColumns":[{"type":"expression","name":"vc","expression":"timestamp_extract(\"__time\",'QUARTER','US/Pacific')","outputType":"LONG"},{"type":"expression","name":"vc0","expression":"((CAST(timestamp_extract(\"__time\",'MONTH','US/Pacific'), 'DOUBLE') / CAST(4, 'DOUBLE')) + CAST(1, 'DOUBLE'))","outputType":"DOUBLE"}],"columns":["vc","vc0"],"resultFormat":"compactedList","limit":1} + druid.query.json {"queryType":"scan","dataSource":"default.druid_table_alltypesorc","intervals":["1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z"],"filter":{"type":"and","fields":[{"type":"expression","expression":"(timestamp_extract(\"__time\",'QUARTER','US/Pacific') >= 4)"},{"type":"expression","expression":"(((CAST(timestamp_extract(\"__time\",'MONTH','US/Pacific'), 'DOUBLE') / CAST(4, 'DOUBLE')) + CAST(1, 'DOUBLE')) == 4)"}]},"virtualColumns":[{"type":"expression","name":"vc","expression":"timestamp_extract(\"__time\",'QUARTER','US/Pacific')","outputType":"LONG"},{"type":"expression","name":"vc0","expression":"4","outputType":"DOUBLE"}],"columns":["vc","vc0"],"resultFormat":"compactedList","limit":1} druid.query.type scan Select Operator expressions: vc (type: int), vc0 (type: double) diff --git ql/src/test/results/clientpositive/druid/druidmini_floorTime.q.out ql/src/test/results/clientpositive/druid/druidmini_floorTime.q.out index 8d9382443e..b927d7da75 100644 --- ql/src/test/results/clientpositive/druid/druidmini_floorTime.q.out +++ ql/src/test/results/clientpositive/druid/druidmini_floorTime.q.out @@ -590,7 +590,7 @@ STAGE PLANS: properties: druid.fieldNames vc,vc0,vc1 druid.fieldTypes double,int,string - druid.query.json {"queryType":"scan","dataSource":"default.druid_table_alltypesorc","intervals":["1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z"],"filter":{"type":"and","fields":[{"type":"expression","expression":"(((CAST(timestamp_extract(\"__time\",'MONTH','US/Pacific'), 'DOUBLE') / 4) + 1) == 4)"},{"type":"bound","dimension":"__time","lower":"11","lowerStrict":false,"upper":"12","upperStrict":false,"ordering":"numeric","extractionFn":{"type":"timeFormat","format":"M","timeZone":"US/Pacific","locale":"en-US"}}]},"virtualColumns":[{"type":"expression","name":"vc","expression":"((CAST(timestamp_extract(\"__time\",'MONTH','US/Pacific'), 'DOUBLE') / CAST(4, 'DOUBLE')) + CAST(1, 'DOUBLE'))","outputType":"DOUBLE"},{"type":"expression","name":"vc0","expression":"timestamp_extract(\"__time\",'MONTH','US/Pacific')","outputType":"LONG"},{"type":"expression","name":"vc1","expression":"substring(timestamp_format(timestamp_floor(timestamp_parse(timestamp_format(\"__time\",'yyyy-MM-dd\\u0027T\\u0027HH:mm:ss.SSS\\u0027Z\\u0027','US/Pacific'),'','UTC'),'P1D','','UTC'),'yyyy-MM-dd','UTC'), 5, 2)","outputType":"STRING"}],"columns":["vc","vc0","vc1"],"resultFormat":"compactedList","limit":1} + druid.query.json {"queryType":"scan","dataSource":"default.druid_table_alltypesorc","intervals":["1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z"],"filter":{"type":"and","fields":[{"type":"expression","expression":"(((CAST(timestamp_extract(\"__time\",'MONTH','US/Pacific'), 'DOUBLE') / CAST(4, 'DOUBLE')) + CAST(1, 'DOUBLE')) == 4)"},{"type":"bound","dimension":"__time","lower":"11","lowerStrict":false,"upper":"12","upperStrict":false,"ordering":"numeric","extractionFn":{"type":"timeFormat","format":"M","timeZone":"US/Pacific","locale":"en-US"}}]},"virtualColumns":[{"type":"expression","name":"vc","expression":"4","outputType":"DOUBLE"},{"type":"expression","name":"vc0","expression":"timestamp_extract(\"__time\",'MONTH','US/Pacific')","outputType":"LONG"},{"type":"expression","name":"vc1","expression":"substring(timestamp_format(timestamp_floor(timestamp_parse(timestamp_format(\"__time\",'yyyy-MM-dd\\u0027T\\u0027HH:mm:ss.SSS\\u0027Z\\u0027','US/Pacific'),'','UTC'),'P1D','','UTC'),'yyyy-MM-dd','UTC'), 5, 2)","outputType":"STRING"}],"columns":["vc","vc0","vc1"],"resultFormat":"compactedList","limit":1} druid.query.type scan Select Operator expressions: vc (type: double), vc0 (type: int), vc1 (type: string) @@ -631,7 +631,7 @@ STAGE PLANS: properties: druid.fieldNames vc,vc0 druid.fieldTypes int,double - druid.query.json {"queryType":"scan","dataSource":"default.druid_table_alltypesorc","intervals":["1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z"],"filter":{"type":"and","fields":[{"type":"expression","expression":"(timestamp_extract(\"__time\",'QUARTER','US/Pacific') >= 4)"},{"type":"expression","expression":"(((CAST(timestamp_extract(\"__time\",'MONTH','US/Pacific'), 'DOUBLE') / 4) + 1) == 4)"}]},"virtualColumns":[{"type":"expression","name":"vc","expression":"timestamp_extract(\"__time\",'QUARTER','US/Pacific')","outputType":"LONG"},{"type":"expression","name":"vc0","expression":"((CAST(timestamp_extract(\"__time\",'MONTH','US/Pacific'), 'DOUBLE') / CAST(4, 'DOUBLE')) + CAST(1, 'DOUBLE'))","outputType":"DOUBLE"}],"columns":["vc","vc0"],"resultFormat":"compactedList","limit":1} + druid.query.json {"queryType":"scan","dataSource":"default.druid_table_alltypesorc","intervals":["1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z"],"filter":{"type":"and","fields":[{"type":"expression","expression":"(timestamp_extract(\"__time\",'QUARTER','US/Pacific') >= 4)"},{"type":"expression","expression":"(((CAST(timestamp_extract(\"__time\",'MONTH','US/Pacific'), 'DOUBLE') / CAST(4, 'DOUBLE')) + CAST(1, 'DOUBLE')) == 4)"}]},"virtualColumns":[{"type":"expression","name":"vc","expression":"timestamp_extract(\"__time\",'QUARTER','US/Pacific')","outputType":"LONG"},{"type":"expression","name":"vc0","expression":"4","outputType":"DOUBLE"}],"columns":["vc","vc0"],"resultFormat":"compactedList","limit":1} druid.query.type scan Select Operator expressions: vc (type: int), vc0 (type: double) diff --git ql/src/test/results/clientpositive/druid/druidmini_mv.q.out ql/src/test/results/clientpositive/druid/druidmini_mv.q.out index 0c1ca76451..c8aa99553e 100644 --- ql/src/test/results/clientpositive/druid/druidmini_mv.q.out +++ ql/src/test/results/clientpositive/druid/druidmini_mv.q.out @@ -233,8 +233,13 @@ STAGE PLANS: Map Operator Tree: TableScan alias: cmv_basetable_n2 +<<<<<<< HEAD + filterExpr: ((d = 3) and (a = 3)) (type: boolean) + Statistics: Num rows: 6 Data size: 96 Basic stats: COMPLETE Column stats: NONE +======= filterExpr: ((a = 3) and (d = 3)) (type: boolean) Statistics: Num rows: 6 Data size: 96 Basic stats: COMPLETE Column stats: COMPLETE +>>>>>>> asf/master Filter Operator predicate: ((a = 3) and (d = 3)) (type: boolean) Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE @@ -253,15 +258,15 @@ STAGE PLANS: TableScan alias: cmv_mat_view2_n0 properties: - druid.fieldNames a,c - druid.fieldTypes int,double - druid.query.json {"queryType":"scan","dataSource":"default.cmv_mat_view2_n0","intervals":["1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z"],"columns":["a","c"],"resultFormat":"compactedList"} + druid.fieldNames c + druid.fieldTypes double + druid.query.json {"queryType":"scan","dataSource":"default.cmv_mat_view2_n0","intervals":["1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z"],"columns":["c"],"resultFormat":"compactedList"} druid.query.type scan - Statistics: Num rows: 3 Data size: 36 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 3 Data size: 24 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator sort order: - Statistics: Num rows: 3 Data size: 36 Basic stats: COMPLETE Column stats: NONE - value expressions: a (type: int), c (type: double) + Statistics: Num rows: 3 Data size: 24 Basic stats: COMPLETE Column stats: NONE + value expressions: c (type: double) Execution mode: vectorized, llap LLAP IO: no inputs Reducer 2 @@ -273,15 +278,27 @@ STAGE PLANS: keys: 0 1 +<<<<<<< HEAD + outputColumnNames: _col0, _col1 + Statistics: Num rows: 18 Data size: 450 Basic stats: COMPLETE Column stats: NONE +======= outputColumnNames: _col0, _col1, _col2 Statistics: Num rows: 3 Data size: 63 Basic stats: COMPLETE Column stats: NONE +>>>>>>> asf/master Select Operator - expressions: _col0 (type: int), _col1 (type: double), _col0 (type: int), _col2 (type: double) + expressions: 3 (type: int), _col0 (type: double), 3 (type: int), _col1 (type: double) outputColumnNames: _col0, _col1, _col2, _col3 +<<<<<<< HEAD + Statistics: Num rows: 18 Data size: 450 Basic stats: COMPLETE Column stats: NONE + File Output Operator + compressed: false + Statistics: Num rows: 18 Data size: 450 Basic stats: COMPLETE Column stats: NONE +======= Statistics: Num rows: 3 Data size: 63 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false Statistics: Num rows: 3 Data size: 63 Basic stats: COMPLETE Column stats: NONE +>>>>>>> asf/master table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -596,8 +613,13 @@ STAGE PLANS: Map Operator Tree: TableScan alias: cmv_basetable_n2 +<<<<<<< HEAD + filterExpr: ((d = 3) and (a = 3)) (type: boolean) + Statistics: Num rows: 7 Data size: 112 Basic stats: COMPLETE Column stats: NONE +======= filterExpr: ((a = 3) and (d = 3)) (type: boolean) Statistics: Num rows: 7 Data size: 112 Basic stats: COMPLETE Column stats: COMPLETE +>>>>>>> asf/master Filter Operator predicate: ((a = 3) and (d = 3)) (type: boolean) Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE @@ -616,15 +638,15 @@ STAGE PLANS: TableScan alias: cmv_mat_view2_n0 properties: - druid.fieldNames a,c - druid.fieldTypes int,double - druid.query.json {"queryType":"scan","dataSource":"default.cmv_mat_view2_n0","intervals":["1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z"],"columns":["a","c"],"resultFormat":"compactedList"} + druid.fieldNames c + druid.fieldTypes double + druid.query.json {"queryType":"scan","dataSource":"default.cmv_mat_view2_n0","intervals":["1900-01-01T00:00:00.000Z/3000-01-01T00:00:00.000Z"],"columns":["c"],"resultFormat":"compactedList"} druid.query.type scan - Statistics: Num rows: 3 Data size: 36 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 3 Data size: 24 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator sort order: - Statistics: Num rows: 3 Data size: 36 Basic stats: COMPLETE Column stats: NONE - value expressions: a (type: int), c (type: double) + Statistics: Num rows: 3 Data size: 24 Basic stats: COMPLETE Column stats: NONE + value expressions: c (type: double) Execution mode: vectorized, llap LLAP IO: no inputs Reducer 2 @@ -636,15 +658,27 @@ STAGE PLANS: keys: 0 1 +<<<<<<< HEAD + outputColumnNames: _col0, _col1 + Statistics: Num rows: 21 Data size: 525 Basic stats: COMPLETE Column stats: NONE +======= outputColumnNames: _col0, _col1, _col2 Statistics: Num rows: 3 Data size: 63 Basic stats: COMPLETE Column stats: NONE +>>>>>>> asf/master Select Operator - expressions: _col0 (type: int), _col1 (type: double), _col0 (type: int), _col2 (type: double) + expressions: 3 (type: int), _col0 (type: double), 3 (type: int), _col1 (type: double) outputColumnNames: _col0, _col1, _col2, _col3 +<<<<<<< HEAD + Statistics: Num rows: 21 Data size: 525 Basic stats: COMPLETE Column stats: NONE + File Output Operator + compressed: false + Statistics: Num rows: 21 Data size: 525 Basic stats: COMPLETE Column stats: NONE +======= Statistics: Num rows: 3 Data size: 63 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false Statistics: Num rows: 3 Data size: 63 Basic stats: COMPLETE Column stats: NONE +>>>>>>> asf/master table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat diff --git ql/src/test/results/clientpositive/dynamic_partition_skip_default.q.out ql/src/test/results/clientpositive/dynamic_partition_skip_default.q.out index f76b24e7d9..8c22e9ecf0 100644 --- ql/src/test/results/clientpositive/dynamic_partition_skip_default.q.out +++ ql/src/test/results/clientpositive/dynamic_partition_skip_default.q.out @@ -214,6 +214,9 @@ POSTHOOK: Input: default@dynamic_part_table POSTHOOK: Input: default@dynamic_part_table@partcol1=1/partcol2=1 POSTHOOK: Input: default@dynamic_part_table@partcol1=1/partcol2=__HIVE_DEFAULT_PARTITION__ #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `intcol` +FROM `default`.`dynamic_part_table` +WHERE `partcol2` IN ('1', '__HIVE_DEFAULT_PARTITION__') AND `partcol1` = '1' STAGE DEPENDENCIES: Stage-0 is a root stage diff --git ql/src/test/results/clientpositive/fold_case.q.out ql/src/test/results/clientpositive/fold_case.q.out index d04d6b4650..a03969f87b 100644 --- ql/src/test/results/clientpositive/fold_case.q.out +++ ql/src/test/results/clientpositive/fold_case.q.out @@ -18,10 +18,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: (key = '238') (type: boolean) + filterExpr: (key = '238') is true (type: boolean) Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (key = '238') (type: boolean) + predicate: (key = '238') is true (type: boolean) Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE Select Operator Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE @@ -75,10 +75,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: (not COALESCE((key = '238'),false)) (type: boolean) + filterExpr: (key = '238') is not true (type: boolean) Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (not COALESCE((key = '238'),false)) (type: boolean) + predicate: (key = '238') is not true (type: boolean) Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE Select Operator Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE @@ -208,10 +208,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: (key = '238') (type: boolean) + filterExpr: (key = '238') is true (type: boolean) Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (key = '238') (type: boolean) + predicate: (key = '238') is true (type: boolean) Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE Select Operator Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE @@ -321,10 +321,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: (key = '238') (type: boolean) + filterExpr: (key = '238') is true (type: boolean) Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (key = '238') (type: boolean) + predicate: (key = '238') is true (type: boolean) Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE Select Operator Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE @@ -378,13 +378,13 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: (not COALESCE((key = '238'),false)) (type: boolean) + filterExpr: (key = '238') is not true (type: boolean) Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (not COALESCE((key = '238'),false)) (type: boolean) + predicate: (key = '238') is not true (type: boolean) Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: CASE WHEN ((key = '238')) THEN (null) ELSE (false) END (type: boolean) + expressions: ((key = '238') is true and null) (type: boolean) outputColumnNames: _col0 Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -467,10 +467,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: CASE WHEN ((key = '238')) THEN (null) ELSE (true) END (type: boolean) + filterExpr: (key = '238') is not true (type: boolean) Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((key = '238')) THEN (null) ELSE (true) END (type: boolean) + predicate: (key = '238') is not true (type: boolean) Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE Select Operator Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE diff --git ql/src/test/results/clientpositive/fold_eq_with_case_when.q.out ql/src/test/results/clientpositive/fold_eq_with_case_when.q.out index 25825b824d..81b86bfd6a 100644 --- ql/src/test/results/clientpositive/fold_eq_with_case_when.q.out +++ ql/src/test/results/clientpositive/fold_eq_with_case_when.q.out @@ -44,26 +44,26 @@ STAGE PLANS: Map Operator Tree: TableScan alias: lineitem - filterExpr: ((DATE'1996-03-30' = to_date(CAST( l_shipdate AS TIMESTAMP))) and (l_shipmode = 'RAIL')) (type: boolean) + filterExpr: (CASE WHEN ((DATE'1996-03-30' = to_date(CAST( l_shipdate AS TIMESTAMP)))) THEN (true) ELSE (null) END and ((l_shipmode = 'RAIL') is true or (null and (l_shipmode = 'RAIL') is not true))) (type: boolean) Statistics: Num rows: 100 Data size: 11999 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((DATE'1996-03-30' = to_date(CAST( l_shipdate AS TIMESTAMP))) and (l_shipmode = 'RAIL')) (type: boolean) - Statistics: Num rows: 25 Data size: 2999 Basic stats: COMPLETE Column stats: NONE + predicate: (((l_shipmode = 'RAIL') is true or (null and (l_shipmode = 'RAIL') is not true)) and CASE WHEN ((DATE'1996-03-30' = to_date(CAST( l_shipdate AS TIMESTAMP)))) THEN (true) ELSE (null) END) (type: boolean) + Statistics: Num rows: 50 Data size: 5999 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: l_orderkey (type: int), (UDFToDouble(l_partkey) / 1000000.0D) (type: double) outputColumnNames: _col0, _col1 - Statistics: Num rows: 25 Data size: 2999 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 50 Data size: 5999 Basic stats: COMPLETE Column stats: NONE Group By Operator aggregations: sum(_col1), sum(1) keys: _col0 (type: int) mode: hash outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 25 Data size: 2999 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 50 Data size: 5999 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: int) sort order: + Map-reduce partition columns: _col0 (type: int) - Statistics: Num rows: 25 Data size: 2999 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 50 Data size: 5999 Basic stats: COMPLETE Column stats: NONE value expressions: _col1 (type: double), _col2 (type: bigint) Execution mode: vectorized Reduce Operator Tree: @@ -72,14 +72,14 @@ STAGE PLANS: keys: KEY._col0 (type: int) mode: mergepartial outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 12 Data size: 1439 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 25 Data size: 2999 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col1 (type: double), _col2 (type: bigint) outputColumnNames: _col0, _col1 - Statistics: Num rows: 12 Data size: 1439 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 25 Data size: 2999 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 12 Data size: 1439 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 25 Data size: 2999 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -109,13 +109,13 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: (key = '238') (type: boolean) + filterExpr: (key = '238') is true (type: boolean) Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (key = '238') (type: boolean) + predicate: (key = '238') is true (type: boolean) Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: '238' (type: string) + expressions: key (type: string) outputColumnNames: _col0 Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -151,18 +151,18 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: (key) IN ('238', '94') (type: boolean) + filterExpr: (key) IN ('238', '94') is true (type: boolean) Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (key) IN ('238', '94') (type: boolean) - Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE + predicate: (key) IN ('238', '94') is true (type: boolean) + Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: key (type: string) outputColumnNames: _col0 - Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -193,13 +193,13 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: (key = '238') (type: boolean) + filterExpr: (key = '238') is true (type: boolean) Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (key = '238') (type: boolean) + predicate: (key = '238') is true (type: boolean) Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: '238' (type: string) + expressions: key (type: string) outputColumnNames: _col0 Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -235,18 +235,18 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: CASE WHEN ((key <> '238')) THEN ((key = '238')) WHEN ((key = '23')) THEN ((key = '238')) ELSE (null) END (type: boolean) + filterExpr: (((key <> '238') or (key = '23')) is true and (key = '238') is true) (type: boolean) Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((key <> '238')) THEN ((key = '238')) WHEN ((key = '23')) THEN ((key = '238')) ELSE (null) END (type: boolean) - Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE + predicate: (((key <> '238') or (key = '23')) is true and (key = '238') is true) (type: boolean) + Statistics: Num rows: 125 Data size: 1328 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: key (type: string) outputColumnNames: _col0 - Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 125 Data size: 1328 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 125 Data size: 1328 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat diff --git ql/src/test/results/clientpositive/fold_when.q.out ql/src/test/results/clientpositive/fold_when.q.out index 956a17b41b..06c2298caf 100644 --- ql/src/test/results/clientpositive/fold_when.q.out +++ ql/src/test/results/clientpositive/fold_when.q.out @@ -174,13 +174,13 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: (key = '238') (type: boolean) + filterExpr: (key = '238') is true (type: boolean) Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (key = '238') (type: boolean) + predicate: (key = '238') is true (type: boolean) Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: '238' (type: string) + expressions: key (type: string) outputColumnNames: _col0 Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -218,13 +218,13 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: (key = '238') (type: boolean) + filterExpr: (key = '238') is true (type: boolean) Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (key = '238') (type: boolean) + predicate: (key = '238') is true (type: boolean) Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: '238' (type: string) + expressions: key (type: string) outputColumnNames: _col0 Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -332,13 +332,13 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: (key = '238') (type: boolean) + filterExpr: (key = '238') is true (type: boolean) Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (key = '238') (type: boolean) + predicate: (key = '238') is true (type: boolean) Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: '238' (type: string) + expressions: key (type: string) outputColumnNames: _col0 Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -376,10 +376,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: (not COALESCE((key = '238'),false)) (type: boolean) + filterExpr: (key = '238') is not true (type: boolean) Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (not COALESCE((key = '238'),false)) (type: boolean) + predicate: (key = '238') is not true (type: boolean) Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: key (type: string) @@ -501,10 +501,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: (not COALESCE((key = '11'),false)) (type: boolean) + filterExpr: (key = '11') is not true (type: boolean) Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (not COALESCE((key = '11'),false)) (type: boolean) + predicate: (key = '11') is not true (type: boolean) Statistics: Num rows: 250 Data size: 2656 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: key (type: string) diff --git ql/src/test/results/clientpositive/groupby_sort_1_23.q.out ql/src/test/results/clientpositive/groupby_sort_1_23.q.out index 7826f2eb7a..daa2a3188f 100644 --- ql/src/test/results/clientpositive/groupby_sort_1_23.q.out +++ ql/src/test/results/clientpositive/groupby_sort_1_23.q.out @@ -3665,7 +3665,7 @@ OPTIMIZED SQL: SELECT `key`, COUNT(*) AS `$f1` FROM `default`.`t1_n80` GROUP BY `key` UNION ALL -SELECT CAST(CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) AS STRING) AS `key`, COUNT(*) AS `_o__c1` +SELECT CAST(CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) AS VARCHAR(65536)) AS `key`, COUNT(*) AS `_o__c1` FROM `default`.`t1_n80` GROUP BY CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/groupby_sort_skew_1_23.q.out ql/src/test/results/clientpositive/groupby_sort_skew_1_23.q.out index 674e8bfe32..663a1b677f 100644 --- ql/src/test/results/clientpositive/groupby_sort_skew_1_23.q.out +++ ql/src/test/results/clientpositive/groupby_sort_skew_1_23.q.out @@ -2998,7 +2998,7 @@ group by key + key POSTHOOK: type: QUERY POSTHOOK: Input: default@t1_n56 POSTHOOK: Output: default@outputtbl1_n13 -OPTIMIZED SQL: SELECT CAST(CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) AS STRING) AS `_o__c0`, SUM(COUNT(*)) AS `_o__c1` +OPTIMIZED SQL: SELECT CAST(CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) AS VARCHAR(65536)) AS `_o__c0`, SUM(COUNT(*)) AS `_o__c1` FROM `default`.`t1_n56` GROUP BY CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) STAGE DEPENDENCIES: @@ -3945,7 +3945,7 @@ OPTIMIZED SQL: SELECT `key`, COUNT(*) AS `$f1` FROM `default`.`t1_n56` GROUP BY `key` UNION ALL -SELECT CAST(CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) AS STRING) AS `key`, COUNT(*) AS `_o__c1` +SELECT CAST(CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) AS VARCHAR(65536)) AS `key`, COUNT(*) AS `_o__c1` FROM `default`.`t1_n56` GROUP BY CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/in_typecheck_char.q.out ql/src/test/results/clientpositive/in_typecheck_char.q.out index 6948719881..96529b33be 100644 --- ql/src/test/results/clientpositive/in_typecheck_char.q.out +++ ql/src/test/results/clientpositive/in_typecheck_char.q.out @@ -209,10 +209,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: ax - filterExpr: (((s = 'a') and (t = 'a ')) or ((s = null) and (t = 'bb '))) is null (type: boolean) + filterExpr: (((s = 'a') and (t = 'a ')) or (null and (t = 'bb '))) is null (type: boolean) Statistics: Num rows: 3 Data size: 36 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (((s = 'a') and (t = 'a ')) or ((s = null) and (t = 'bb '))) is null (type: boolean) + predicate: (((s = 'a') and (t = 'a ')) or (null and (t = 'bb '))) is null (type: boolean) Statistics: Num rows: 1 Data size: 12 Basic stats: COMPLETE Column stats: NONE Select Operator Statistics: Num rows: 1 Data size: 12 Basic stats: COMPLETE Column stats: NONE diff --git ql/src/test/results/clientpositive/infer_const_type.q.out ql/src/test/results/clientpositive/infer_const_type.q.out index db3b012951..a154ca4a7e 100644 --- ql/src/test/results/clientpositive/infer_const_type.q.out +++ ql/src/test/results/clientpositive/infer_const_type.q.out @@ -139,10 +139,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: infertypes - filterExpr: ((UDFToDouble(ti) = 128.0D) or (UDFToInteger(si) = 32768) or (UDFToDouble(i) = 2.147483648E9D) or (UDFToDouble(bi) = 9.223372036854776E18D) or null) (type: boolean) + filterExpr: ((UDFToDouble(ti) = 128.0D) or (UDFToInteger(si) = 32768) or (UDFToDouble(i) = 2.147483648E9D) or (UDFToDouble(bi) = 9.223372036854776E18D)) (type: boolean) Statistics: Num rows: 1 Data size: 1170 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((UDFToDouble(bi) = 9.223372036854776E18D) or (UDFToDouble(i) = 2.147483648E9D) or (UDFToDouble(ti) = 128.0D) or (UDFToInteger(si) = 32768) or null) (type: boolean) + predicate: ((UDFToDouble(bi) = 9.223372036854776E18D) or (UDFToDouble(i) = 2.147483648E9D) or (UDFToDouble(ti) = 128.0D) or (UDFToInteger(si) = 32768)) (type: boolean) Statistics: Num rows: 1 Data size: 1170 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: ti (type: tinyint), si (type: smallint), i (type: int), bi (type: bigint), fl (type: float), db (type: double), str (type: string) diff --git ql/src/test/results/clientpositive/infer_join_preds.q.out ql/src/test/results/clientpositive/infer_join_preds.q.out index 2bd92aedb6..58b18ab62e 100644 --- ql/src/test/results/clientpositive/infer_join_preds.q.out +++ ql/src/test/results/clientpositive/infer_join_preds.q.out @@ -1178,7 +1178,7 @@ STAGE PLANS: predicate: prid is not null (type: boolean) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Select Operator - expressions: idp_warehouse_id (type: bigint), prid (type: bigint), concat(CAST( prid AS STRING), ',', CASE WHEN (prtimesheetid is null) THEN (1) ELSE (prtimesheetid) END, ',', CASE WHEN (prassignmentid is null) THEN (1) ELSE (prassignmentid) END, ',', CASE WHEN (prchargecodeid is null) THEN (1) ELSE (prchargecodeid) END, ',', CASE WHEN (prtypecodeid is null) THEN ('') ELSE (CAST( prtypecodeid AS STRING)) END, ',', CASE WHEN (practsum is null) THEN (1) ELSE (practsum) END, ',', CASE WHEN (prsequence is null) THEN (1) ELSE (prsequence) END, ',', CASE WHEN (length(prmodby) is null) THEN ('') ELSE (prmodby) END, ',', CASE WHEN (prmodtime is null) THEN (TIMESTAMP'2017-12-08 00:00:00') ELSE (prmodtime) END, ',', CASE WHEN (prrmexported is null) THEN (1) ELSE (prrmexported) END, ',', CASE WHEN (prrmckdel is null) THEN (1) ELSE (prrmckdel) END, ',', CASE WHEN (slice_status is null) THEN (1) ELSE (slice_status) END, ',', CASE WHEN (role_id is null) THEN (1) ELSE (role_id) END, ',', CASE WHEN (length(user_lov1) is null) THEN ('') ELSE (user_lov1) END, ',', CASE WHEN (length(user_lov2) is null) THEN ('') ELSE (user_lov2) END, ',', CASE WHEN (incident_id is null) THEN (1) ELSE (incident_id) END, ',', CASE WHEN (incident_investment_id is null) THEN (1) ELSE (incident_investment_id) END, ',', CASE WHEN (odf_ss_actuals is null) THEN (1) ELSE (odf_ss_actuals) END) (type: string) + expressions: idp_warehouse_id (type: bigint), prid (type: bigint), concat(CAST( CASE WHEN (prid is null) THEN (1) ELSE (prid) END AS STRING), ',', CASE WHEN (prtimesheetid is null) THEN (1) ELSE (prtimesheetid) END, ',', CASE WHEN (prassignmentid is null) THEN (1) ELSE (prassignmentid) END, ',', CASE WHEN (prchargecodeid is null) THEN (1) ELSE (prchargecodeid) END, ',', CASE WHEN (prtypecodeid is null) THEN ('') ELSE (CAST( prtypecodeid AS STRING)) END, ',', CASE WHEN (practsum is null) THEN (1) ELSE (practsum) END, ',', CASE WHEN (prsequence is null) THEN (1) ELSE (prsequence) END, ',', CASE WHEN (length(prmodby) is null) THEN ('') ELSE (prmodby) END, ',', CASE WHEN (prmodtime is null) THEN (TIMESTAMP'2017-12-08 00:00:00') ELSE (prmodtime) END, ',', CASE WHEN (prrmexported is null) THEN (1) ELSE (prrmexported) END, ',', CASE WHEN (prrmckdel is null) THEN (1) ELSE (prrmckdel) END, ',', CASE WHEN (slice_status is null) THEN (1) ELSE (slice_status) END, ',', CASE WHEN (role_id is null) THEN (1) ELSE (role_id) END, ',', CASE WHEN (length(user_lov1) is null) THEN ('') ELSE (user_lov1) END, ',', CASE WHEN (length(user_lov2) is null) THEN ('') ELSE (user_lov2) END, ',', CASE WHEN (incident_id is null) THEN (1) ELSE (incident_id) END, ',', CASE WHEN (incident_investment_id is null) THEN (1) ELSE (incident_investment_id) END, ',', CASE WHEN (odf_ss_actuals is null) THEN (1) ELSE (odf_ss_actuals) END) (type: string) outputColumnNames: _col0, _col1, _col2 Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Reduce Output Operator @@ -1211,7 +1211,7 @@ STAGE PLANS: predicate: prid is not null (type: boolean) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Select Operator - expressions: prid (type: bigint), concat(CASE WHEN (length(pruid) is null) THEN ('') ELSE (pruid) END, ',', prid, ',', CASE WHEN (prtimesheetid is null) THEN (1) ELSE (prtimesheetid) END, ',', CASE WHEN (prassignmentid is null) THEN (1) ELSE (prassignmentid) END, ',', CASE WHEN (prchargecodeid is null) THEN (1) ELSE (prchargecodeid) END, ',', CASE WHEN (prtypecodeid is null) THEN ('') ELSE (CAST( prtypecodeid AS STRING)) END, ',', CASE WHEN (practsum is null) THEN (1) ELSE (practsum) END, ',', CASE WHEN (prsequence is null) THEN (1) ELSE (prsequence) END, ',', CASE WHEN (length(prmodby) is null) THEN ('') ELSE (prmodby) END, ',', CASE WHEN (prmodtime is null) THEN (TIMESTAMP'2017-12-08 00:00:00') ELSE (prmodtime) END, ',', CASE WHEN (prrmexported is null) THEN (1) ELSE (prrmexported) END, ',', CASE WHEN (prrmckdel is null) THEN (1) ELSE (prrmckdel) END, ',', CASE WHEN (slice_status is null) THEN (1) ELSE (slice_status) END, ',', CASE WHEN (role_id is null) THEN (1) ELSE (role_id) END, ',', CASE WHEN (length(user_lov1) is null) THEN ('') ELSE (user_lov1) END, ',', CASE WHEN (length(user_lov2) is null) THEN ('') ELSE (user_lov2) END, ',', CASE WHEN (incident_id is null) THEN (1) ELSE (incident_id) END, ',', CASE WHEN (incident_investment_id is null) THEN (1) ELSE (incident_investment_id) END, ',', CASE WHEN (odf_ss_actuals is null) THEN (1) ELSE (odf_ss_actuals) END) (type: string) + expressions: prid (type: bigint), concat(CASE WHEN (length(pruid) is null) THEN ('') ELSE (pruid) END, ',', CASE WHEN (prid is null) THEN (1) ELSE (prid) END, ',', CASE WHEN (prtimesheetid is null) THEN (1) ELSE (prtimesheetid) END, ',', CASE WHEN (prassignmentid is null) THEN (1) ELSE (prassignmentid) END, ',', CASE WHEN (prchargecodeid is null) THEN (1) ELSE (prchargecodeid) END, ',', CASE WHEN (prtypecodeid is null) THEN ('') ELSE (CAST( prtypecodeid AS STRING)) END, ',', CASE WHEN (practsum is null) THEN (1) ELSE (practsum) END, ',', CASE WHEN (prsequence is null) THEN (1) ELSE (prsequence) END, ',', CASE WHEN (length(prmodby) is null) THEN ('') ELSE (prmodby) END, ',', CASE WHEN (prmodtime is null) THEN (TIMESTAMP'2017-12-08 00:00:00') ELSE (prmodtime) END, ',', CASE WHEN (prrmexported is null) THEN (1) ELSE (prrmexported) END, ',', CASE WHEN (prrmckdel is null) THEN (1) ELSE (prrmckdel) END, ',', CASE WHEN (slice_status is null) THEN (1) ELSE (slice_status) END, ',', CASE WHEN (role_id is null) THEN (1) ELSE (role_id) END, ',', CASE WHEN (length(user_lov1) is null) THEN ('') ELSE (user_lov1) END, ',', CASE WHEN (length(user_lov2) is null) THEN ('') ELSE (user_lov2) END, ',', CASE WHEN (incident_id is null) THEN (1) ELSE (incident_id) END, ',', CASE WHEN (incident_investment_id is null) THEN (1) ELSE (incident_investment_id) END, ',', CASE WHEN (odf_ss_actuals is null) THEN (1) ELSE (odf_ss_actuals) END) (type: string) outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Reduce Output Operator diff --git ql/src/test/results/clientpositive/innerjoin1.q.out ql/src/test/results/clientpositive/innerjoin1.q.out index 0bde0c9fe0..07adbf9c19 100644 --- ql/src/test/results/clientpositive/innerjoin1.q.out +++ ql/src/test/results/clientpositive/innerjoin1.q.out @@ -82,37 +82,37 @@ STAGE PLANS: Map Operator Tree: TableScan alias: c1 - filterExpr: CASE WHEN (a1 is not null) THEN (a1 is not null) ELSE (a2 is not null) END (type: boolean) + filterExpr: (a1 is not null or a2 is not null) (type: boolean) Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN (a1 is not null) THEN (a1 is not null) ELSE (a2 is not null) END (type: boolean) - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + predicate: (a1 is not null or a2 is not null) (type: boolean) + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: a1 (type: string), a2 (type: string), CASE WHEN (a1 is not null) THEN (a1) ELSE (a2) END (type: string) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col2 (type: string) sort order: + Map-reduce partition columns: _col2 (type: string) - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE value expressions: _col0 (type: string), _col1 (type: string) TableScan alias: c2 - filterExpr: CASE WHEN (b1 is not null) THEN (b1 is not null) ELSE (b2 is not null) END (type: boolean) + filterExpr: (b1 is not null or b2 is not null) (type: boolean) Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN (b1 is not null) THEN (b1 is not null) ELSE (b2 is not null) END (type: boolean) - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + predicate: (b1 is not null or b2 is not null) (type: boolean) + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: b1 (type: string), b2 (type: string), CASE WHEN (b1 is not null) THEN (b1) ELSE (b2) END (type: string) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col2 (type: string) sort order: + Map-reduce partition columns: _col2 (type: string) - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE value expressions: _col0 (type: string), _col1 (type: string) Reduce Operator Tree: Join Operator @@ -122,14 +122,14 @@ STAGE PLANS: 0 _col2 (type: string) 1 _col2 (type: string) outputColumnNames: _col0, _col1, _col3, _col4 - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: string), _col3 (type: string), _col4 (type: string) outputColumnNames: _col0, _col1, _col2, _col3 - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -173,37 +173,37 @@ STAGE PLANS: Map Operator Tree: TableScan alias: c1 - filterExpr: CASE WHEN (a1 is not null) THEN (a1 is not null) ELSE (a2 is not null) END (type: boolean) + filterExpr: (a1 is not null or a2 is not null) (type: boolean) Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN (a1 is not null) THEN (a1 is not null) ELSE (a2 is not null) END (type: boolean) - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + predicate: (a1 is not null or a2 is not null) (type: boolean) + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: a1 (type: string), a2 (type: string), CASE WHEN (a1 is not null) THEN (a1) ELSE (a2) END (type: string) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col2 (type: string) sort order: + Map-reduce partition columns: _col2 (type: string) - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE value expressions: _col0 (type: string), _col1 (type: string) TableScan alias: c2 - filterExpr: CASE WHEN (b1 is not null) THEN (b1 is not null) ELSE (b2 is not null) END (type: boolean) + filterExpr: (b1 is not null or b2 is not null) (type: boolean) Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN (b1 is not null) THEN (b1 is not null) ELSE (b2 is not null) END (type: boolean) - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + predicate: (b1 is not null or b2 is not null) (type: boolean) + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: b1 (type: string), b2 (type: string), CASE WHEN (b1 is not null) THEN (b1) ELSE (b2) END (type: string) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col2 (type: string) sort order: + Map-reduce partition columns: _col2 (type: string) - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE value expressions: _col0 (type: string), _col1 (type: string) Reduce Operator Tree: Join Operator @@ -213,14 +213,14 @@ STAGE PLANS: 0 _col2 (type: string) 1 _col2 (type: string) outputColumnNames: _col0, _col1, _col3, _col4 - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: string), _col3 (type: string), _col4 (type: string) outputColumnNames: _col0, _col1, _col2, _col3 - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 7 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat diff --git ql/src/test/results/clientpositive/input23.q.out ql/src/test/results/clientpositive/input23.q.out index 4140b3c63f..189f70e3df 100644 --- ql/src/test/results/clientpositive/input23.q.out +++ ql/src/test/results/clientpositive/input23.q.out @@ -11,7 +11,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=11 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `t0`.`key`, `t0`.`value`, CAST('2008-04-08' AS STRING) AS `ds`, CAST('11' AS STRING) AS `hr`, `t2`.`key` AS `key1`, `t2`.`value` AS `value1`, CAST('2008-04-08' AS STRING) AS `ds1`, CAST('14' AS STRING) AS `hr1` +OPTIMIZED SQL: SELECT `t0`.`key`, `t0`.`value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds`, CAST('11' AS VARCHAR(65536)) AS `hr`, `t2`.`key` AS `key1`, `t2`.`value` AS `value1`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds1`, CAST('14' AS VARCHAR(65536)) AS `hr1` FROM (SELECT `key`, `value` FROM `default`.`srcpart` WHERE `ds` = '2008-04-08' AND `hr` = '11') AS `t0`, diff --git ql/src/test/results/clientpositive/input42.q.out ql/src/test/results/clientpositive/input42.q.out index b2a3c6a0a4..3c8608257e 100644 --- ql/src/test/results/clientpositive/input42.q.out +++ ql/src/test/results/clientpositive/input42.q.out @@ -12,7 +12,7 @@ POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=11 POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS STRING) AS `ds`, `hr` +OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds`, `hr` FROM `default`.`srcpart` WHERE `ds` = '2008-04-08' STAGE DEPENDENCIES: @@ -1155,7 +1155,7 @@ POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=11 POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS STRING) AS `ds`, `hr` +OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds`, `hr` FROM `default`.`srcpart` WHERE `ds` = '2008-04-08' AND `key` < 200 STAGE DEPENDENCIES: @@ -1717,7 +1717,7 @@ POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=11 POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS STRING) AS `ds`, `hr` +OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds`, `hr` FROM `default`.`srcpart` WHERE `ds` = '2008-04-08' AND RAND(100) < 0.1 STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/input8.q.out ql/src/test/results/clientpositive/input8.q.out index 3c533a8748..baf73bbf66 100644 --- ql/src/test/results/clientpositive/input8.q.out +++ ql/src/test/results/clientpositive/input8.q.out @@ -34,14 +34,14 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src1 - Statistics: Num rows: 25 Data size: 191 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 25 Data size: 191 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: null (type: string), UDFToInteger((UDFToDouble(key) - null)) (type: int), null (type: double) + expressions: null (type: string), null (type: int), null (type: double) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 25 Data size: 191 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 25 Data size: 96 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 25 Data size: 191 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 25 Data size: 96 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.TextInputFormat output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat @@ -50,25 +50,25 @@ STAGE PLANS: Select Operator expressions: _col0 (type: string), _col1 (type: int), _col2 (type: double) outputColumnNames: c1, c2, c3 - Statistics: Num rows: 25 Data size: 191 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 25 Data size: 96 Basic stats: COMPLETE Column stats: COMPLETE Group By Operator aggregations: compute_stats(c1, 'hll'), compute_stats(c2, 'hll'), compute_stats(c3, 'hll') mode: hash outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 1 Data size: 1288 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 1288 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator sort order: - Statistics: Num rows: 1 Data size: 1288 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 1288 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col0 (type: struct), _col1 (type: struct), _col2 (type: struct) Reduce Operator Tree: Group By Operator aggregations: compute_stats(VALUE._col0), compute_stats(VALUE._col1), compute_stats(VALUE._col2) mode: mergepartial outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 1 Data size: 1320 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 1320 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 1320 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 1320 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -142,7 +142,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@src1 POSTHOOK: Output: default@dest1_n28 POSTHOOK: Lineage: dest1_n28.c1 EXPRESSION [] -POSTHOOK: Lineage: dest1_n28.c2 EXPRESSION [(src1)src1.FieldSchema(name:key, type:string, comment:default), ] +POSTHOOK: Lineage: dest1_n28.c2 EXPRESSION [] POSTHOOK: Lineage: dest1_n28.c3 EXPRESSION [] PREHOOK: query: SELECT dest1_n28.* FROM dest1_n28 PREHOOK: type: QUERY diff --git ql/src/test/results/clientpositive/input_part1.q.out ql/src/test/results/clientpositive/input_part1.q.out index ae893c4742..041d43f1a9 100644 --- ql/src/test/results/clientpositive/input_part1.q.out +++ ql/src/test/results/clientpositive/input_part1.q.out @@ -20,7 +20,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 POSTHOOK: Output: default@dest1_n45 -OPTIMIZED SQL: SELECT `key`, `value`, CAST('12' AS STRING) AS `hr`, CAST('2008-04-08' AS STRING) AS `ds` +OPTIMIZED SQL: SELECT `key`, `value`, CAST('12' AS VARCHAR(65536)) AS `hr`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds` FROM `default`.`srcpart` WHERE `key` < 100 AND `ds` = '2008-04-08' AND `hr` = '12' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/input_part9.q.out ql/src/test/results/clientpositive/input_part9.q.out index 356c28334c..3c63dfaee5 100644 --- ql/src/test/results/clientpositive/input_part9.q.out +++ ql/src/test/results/clientpositive/input_part9.q.out @@ -12,7 +12,7 @@ POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=11 POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS STRING) AS `ds`, `hr` +OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds`, `hr` FROM `default`.`srcpart` WHERE `ds` = '2008-04-08' AND `key` IS NOT NULL STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/join_filters_overlap.q.out ql/src/test/results/clientpositive/join_filters_overlap.q.out index 331123e8ea..4ff392519f 100644 --- ql/src/test/results/clientpositive/join_filters_overlap.q.out +++ ql/src/test/results/clientpositive/join_filters_overlap.q.out @@ -18,6 +18,15 @@ POSTHOOK: query: explain extended select * from a_n4 left outer join a_n4 b on ( POSTHOOK: type: QUERY POSTHOOK: Input: default@a_n4 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `t`.`key`, `t`.`value`, `t1`.`key` AS `key1`, `t1`.`value` AS `value1`, `t3`.`key` AS `key2`, `t3`.`value` AS `value2` +FROM (SELECT `key`, `value`, `value` = 60 AS `=`, `value` = 50 AS `=3` +FROM `default`.`a_n4`) AS `t` +LEFT JOIN (SELECT `key`, CAST(50 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 50) AS `t1` ON `t`.`key` = `t1`.`key` AND `t`.`=3` +LEFT JOIN (SELECT `key`, CAST(60 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 60) AS `t3` ON `t`.`key` = `t3`.`key` AND `t`.`=` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -221,6 +230,15 @@ POSTHOOK: query: explain extended select * from a_n4 right outer join a_n4 b on POSTHOOK: type: QUERY POSTHOOK: Input: default@a_n4 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `t0`.`key`, `t0`.`value`, `t1`.`key` AS `key1`, `t1`.`value` AS `value1`, `t3`.`key` AS `key2`, `t3`.`value` AS `value2` +FROM (SELECT `key`, CAST(50 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 50) AS `t0` +RIGHT JOIN (SELECT `key`, `value`, `value` = 60 AS `=`, `value` = 50 AS `=3` +FROM `default`.`a_n4`) AS `t1` ON `t0`.`key` = `t1`.`key` AND `t1`.`=3` +LEFT JOIN (SELECT `key`, CAST(60 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 60) AS `t3` ON `t1`.`key` = `t3`.`key` AND `t1`.`=` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -424,6 +442,15 @@ POSTHOOK: query: explain extended select * from a_n4 right outer join a_n4 b on POSTHOOK: type: QUERY POSTHOOK: Input: default@a_n4 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `t0`.`key`, `t0`.`value`, `t1`.`key` AS `key1`, `t1`.`value` AS `value1`, `t3`.`key` AS `key2`, `t3`.`value` AS `value2` +FROM (SELECT `key`, CAST(50 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 50) AS `t0` +RIGHT JOIN (SELECT `key`, `value`, `value` = 60 AS `=`, `value` = 50 AS `=3` +FROM `default`.`a_n4`) AS `t1` ON `t0`.`key` = `t1`.`key` AND `t1`.`=3` +LEFT JOIN (SELECT `key`, CAST(60 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 60) AS `t3` ON `t1`.`key` = `t3`.`key` AND `t1`.`=` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -627,6 +654,17 @@ POSTHOOK: query: explain extended select * from a_n4 full outer join a_n4 b on ( POSTHOOK: type: QUERY POSTHOOK: Input: default@a_n4 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `t`.`key`, `t`.`value`, `t0`.`key` AS `key1`, `t0`.`value` AS `value1`, `t2`.`key` AS `key2`, `t2`.`value` AS `value2`, `t4`.`key` AS `key3`, `t4`.`value` AS `value3` +FROM (SELECT `key`, `value`, `value` = 40 AS `=`, `value` = 50 AS `=3` +FROM `default`.`a_n4`) AS `t` +FULL JOIN (SELECT `key`, `value`, `value` = 60 AS `=`, `value` = 50 AS `=3` +FROM `default`.`a_n4`) AS `t0` ON `t`.`key` = `t0`.`key` AND `t`.`=3` AND `t0`.`=3` +LEFT JOIN (SELECT `key`, CAST(60 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 60) AS `t2` ON `t0`.`key` = `t2`.`key` AND `t0`.`=` +LEFT JOIN (SELECT `key`, CAST(40 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 40) AS `t4` ON `t`.`key` = `t4`.`key` AND `t`.`=` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -842,6 +880,18 @@ POSTHOOK: query: explain extended select * from a_n4 left outer join a_n4 b on ( POSTHOOK: type: QUERY POSTHOOK: Input: default@a_n4 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `t`.`key`, `t`.`value`, `t1`.`key` AS `key1`, `t1`.`value` AS `value1`, `t3`.`key` AS `key2`, `t3`.`value` AS `value2`, `t5`.`key` AS `key3`, `t5`.`value` AS `value3` +FROM (SELECT `key`, `value`, `value` = 40 AS `=`, `value` = 60 AS `=3`, `value` = 50 AS `=4` +FROM `default`.`a_n4`) AS `t` +LEFT JOIN (SELECT `key`, CAST(50 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 50) AS `t1` ON `t`.`key` = `t1`.`key` AND `t`.`=4` +LEFT JOIN (SELECT `key`, CAST(60 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 60) AS `t3` ON `t`.`key` = `t3`.`key` AND `t`.`=3` +LEFT JOIN (SELECT `key`, CAST(40 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 40) AS `t5` ON `t`.`key` = `t5`.`key` AND `t`.`=` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 diff --git ql/src/test/results/clientpositive/list_bucket_dml_1.q.out ql/src/test/results/clientpositive/list_bucket_dml_1.q.out index 1ca49834c0..3a619a21ed 100644 --- ql/src/test/results/clientpositive/list_bucket_dml_1.q.out +++ ql/src/test/results/clientpositive/list_bucket_dml_1.q.out @@ -418,7 +418,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@list_bucketing_dynamic_part_n0 POSTHOOK: Input: default@list_bucketing_dynamic_part_n0@ds=2008-04-08/hr=11 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('484' AS STRING) AS `key`, `value` +OPTIMIZED SQL: SELECT CAST('484' AS VARCHAR(65536)) AS `key`, `value` FROM `default`.`list_bucketing_dynamic_part_n0` WHERE `ds` = '2008-04-08' AND `hr` = '11' AND `key` = '484' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/list_bucket_dml_11.q.out ql/src/test/results/clientpositive/list_bucket_dml_11.q.out index 3508a6ffd1..4ddfea3b56 100644 --- ql/src/test/results/clientpositive/list_bucket_dml_11.q.out +++ ql/src/test/results/clientpositive/list_bucket_dml_11.q.out @@ -296,7 +296,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@list_bucketing_static_part_n3 POSTHOOK: Input: default@list_bucketing_static_part_n3@ds=2008-04-08/hr=11 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `key`, CAST('val_466' AS STRING) AS `value` +OPTIMIZED SQL: SELECT `key`, CAST('val_466' AS VARCHAR(65536)) AS `value` FROM `default`.`list_bucketing_static_part_n3` WHERE `ds` = '2008-04-08' AND `hr` = '11' AND `value` = 'val_466' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/list_bucket_dml_12.q.out ql/src/test/results/clientpositive/list_bucket_dml_12.q.out index 406a9c1a75..18869023de 100644 --- ql/src/test/results/clientpositive/list_bucket_dml_12.q.out +++ ql/src/test/results/clientpositive/list_bucket_dml_12.q.out @@ -304,7 +304,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@list_bucketing_mul_col_n0 POSTHOOK: Input: default@list_bucketing_mul_col_n0@ds=2008-04-08/hr=11 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `col1`, CAST('466' AS STRING) AS `col2`, `col3`, CAST('val_466' AS STRING) AS `col4`, `col5`, CAST('2008-04-08' AS STRING) AS `ds`, CAST('11' AS STRING) AS `hr` +OPTIMIZED SQL: SELECT `col1`, CAST('466' AS VARCHAR(65536)) AS `col2`, `col3`, CAST('val_466' AS VARCHAR(65536)) AS `col4`, `col5`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds`, CAST('11' AS VARCHAR(65536)) AS `hr` FROM `default`.`list_bucketing_mul_col_n0` WHERE `ds` = '2008-04-08' AND `hr` = '11' AND `col2` = '466' AND `col4` = 'val_466' STAGE DEPENDENCIES: @@ -441,7 +441,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@list_bucketing_mul_col_n0 POSTHOOK: Input: default@list_bucketing_mul_col_n0@ds=2008-04-08/hr=11 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `col1`, CAST('382' AS STRING) AS `col2`, `col3`, CAST('val_382' AS STRING) AS `col4`, `col5`, CAST('2008-04-08' AS STRING) AS `ds`, CAST('11' AS STRING) AS `hr` +OPTIMIZED SQL: SELECT `col1`, CAST('382' AS VARCHAR(65536)) AS `col2`, `col3`, CAST('val_382' AS VARCHAR(65536)) AS `col4`, `col5`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds`, CAST('11' AS VARCHAR(65536)) AS `hr` FROM `default`.`list_bucketing_mul_col_n0` WHERE `ds` = '2008-04-08' AND `hr` = '11' AND `col2` = '382' AND `col4` = 'val_382' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/list_bucket_dml_13.q.out ql/src/test/results/clientpositive/list_bucket_dml_13.q.out index a383a3849c..a33d328c5e 100644 --- ql/src/test/results/clientpositive/list_bucket_dml_13.q.out +++ ql/src/test/results/clientpositive/list_bucket_dml_13.q.out @@ -304,7 +304,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@list_bucketing_mul_col POSTHOOK: Input: default@list_bucketing_mul_col@ds=2008-04-08/hr=2013-01-23+18%3A00%3A99 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `col1`, CAST('466' AS STRING) AS `col2`, `col3`, CAST('val_466' AS STRING) AS `col4`, `col5`, CAST('2008-04-08' AS STRING) AS `ds`, CAST('2013-01-23+18:00:99' AS STRING) AS `hr` +OPTIMIZED SQL: SELECT `col1`, CAST('466' AS VARCHAR(65536)) AS `col2`, `col3`, CAST('val_466' AS VARCHAR(65536)) AS `col4`, `col5`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds`, CAST('2013-01-23+18:00:99' AS VARCHAR(65536)) AS `hr` FROM `default`.`list_bucketing_mul_col` WHERE `ds` = '2008-04-08' AND `hr` = '2013-01-23+18:00:99' AND `col2` = '466' AND `col4` = 'val_466' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/list_bucket_dml_14.q.out ql/src/test/results/clientpositive/list_bucket_dml_14.q.out index 5b89cd7c11..75e6615f82 100644 --- ql/src/test/results/clientpositive/list_bucket_dml_14.q.out +++ ql/src/test/results/clientpositive/list_bucket_dml_14.q.out @@ -297,7 +297,7 @@ select key, value from list_bucketing where key = "484" POSTHOOK: type: QUERY POSTHOOK: Input: default@list_bucketing #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('484' AS STRING) AS `key`, `value` +OPTIMIZED SQL: SELECT CAST('484' AS VARCHAR(65536)) AS `key`, `value` FROM `default`.`list_bucketing` WHERE `key` = '484' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/list_bucket_dml_2.q.out ql/src/test/results/clientpositive/list_bucket_dml_2.q.out index 8f39619971..a0e10b7e59 100644 --- ql/src/test/results/clientpositive/list_bucket_dml_2.q.out +++ ql/src/test/results/clientpositive/list_bucket_dml_2.q.out @@ -375,7 +375,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@list_bucketing_static_part_n4 POSTHOOK: Input: default@list_bucketing_static_part_n4@ds=2008-04-08/hr=11 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('484' AS STRING) AS `$f0`, CAST('val_484' AS STRING) AS `$f1`, CAST('2008-04-08' AS STRING) AS `$f2`, CAST('11' AS STRING) AS `$f3` +OPTIMIZED SQL: SELECT CAST('484' AS VARCHAR(65536)) AS `$f0`, CAST('val_484' AS VARCHAR(65536)) AS `$f1`, CAST('2008-04-08' AS VARCHAR(65536)) AS `$f2`, CAST('11' AS VARCHAR(65536)) AS `$f3` FROM `default`.`list_bucketing_static_part_n4` WHERE `ds` = '2008-04-08' AND `hr` = '11' AND `key` = '484' AND `value` = 'val_484' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/list_bucket_dml_3.q.out ql/src/test/results/clientpositive/list_bucket_dml_3.q.out index fb8ff449a9..8bdd187c19 100644 --- ql/src/test/results/clientpositive/list_bucket_dml_3.q.out +++ ql/src/test/results/clientpositive/list_bucket_dml_3.q.out @@ -367,7 +367,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@list_bucketing_static_part_n1 POSTHOOK: Input: default@list_bucketing_static_part_n1@ds=2008-04-08/hr=11 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('484' AS STRING) AS `key`, `value` +OPTIMIZED SQL: SELECT CAST('484' AS VARCHAR(65536)) AS `key`, `value` FROM `default`.`list_bucketing_static_part_n1` WHERE `ds` = '2008-04-08' AND `hr` = '11' AND `key` = '484' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/list_bucket_dml_4.q.out ql/src/test/results/clientpositive/list_bucket_dml_4.q.out index 9bcc9a5fca..ad29c85d92 100644 --- ql/src/test/results/clientpositive/list_bucket_dml_4.q.out +++ ql/src/test/results/clientpositive/list_bucket_dml_4.q.out @@ -826,7 +826,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@list_bucketing_static_part_n2 POSTHOOK: Input: default@list_bucketing_static_part_n2@ds=2008-04-08/hr=11 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('484' AS STRING) AS `$f0`, CAST('val_484' AS STRING) AS `$f1`, CAST('2008-04-08' AS STRING) AS `$f2`, CAST('11' AS STRING) AS `$f3` +OPTIMIZED SQL: SELECT CAST('484' AS VARCHAR(65536)) AS `$f0`, CAST('val_484' AS VARCHAR(65536)) AS `$f1`, CAST('2008-04-08' AS VARCHAR(65536)) AS `$f2`, CAST('11' AS VARCHAR(65536)) AS `$f3` FROM `default`.`list_bucketing_static_part_n2` WHERE `ds` = '2008-04-08' AND `hr` = '11' AND `key` = '484' AND `value` = 'val_484' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/list_bucket_dml_5.q.out ql/src/test/results/clientpositive/list_bucket_dml_5.q.out index 9b6bf06790..703d0f6e54 100644 --- ql/src/test/results/clientpositive/list_bucket_dml_5.q.out +++ ql/src/test/results/clientpositive/list_bucket_dml_5.q.out @@ -425,7 +425,7 @@ POSTHOOK: Input: default@list_bucketing_dynamic_part_n1 POSTHOOK: Input: default@list_bucketing_dynamic_part_n1@ds=2008-04-08/hr=11 POSTHOOK: Input: default@list_bucketing_dynamic_part_n1@ds=2008-04-08/hr=12 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('103' AS STRING) AS `key`, CAST('val_103' AS STRING) AS `value`, CAST('2008-04-08' AS STRING) AS `ds`, `hr` +OPTIMIZED SQL: SELECT CAST('103' AS VARCHAR(65536)) AS `key`, CAST('val_103' AS VARCHAR(65536)) AS `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds`, `hr` FROM `default`.`list_bucketing_dynamic_part_n1` WHERE `ds` = '2008-04-08' AND `key` = '103' AND `value` = 'val_103' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/list_bucket_dml_6.q.out ql/src/test/results/clientpositive/list_bucket_dml_6.q.out index 76459d7729..4ca1f0d46a 100644 --- ql/src/test/results/clientpositive/list_bucket_dml_6.q.out +++ ql/src/test/results/clientpositive/list_bucket_dml_6.q.out @@ -29,7 +29,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=11 POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 -OPTIMIZED SQL: SELECT `key`, `value`, IF(MOD(CAST(`key` AS DOUBLE), CAST(100 AS DOUBLE)) = 0, 'a1', 'b1') AS `_o__c2` +OPTIMIZED SQL: SELECT `key`, `value`, IF(MOD(CAST(`key` AS DOUBLE), CAST(100 AS DOUBLE)) = CAST(0 AS DOUBLE), 'a1', 'b1') AS `_o__c2` FROM `default`.`srcpart` WHERE `ds` = '2008-04-08' STAGE DEPENDENCIES: @@ -404,7 +404,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=11 POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 -OPTIMIZED SQL: SELECT `key`, `value`, IF(MOD(CAST(`key` AS DOUBLE), CAST(100 AS DOUBLE)) = 0, 'a1', 'b1') AS `_o__c2` +OPTIMIZED SQL: SELECT `key`, `value`, IF(MOD(CAST(`key` AS DOUBLE), CAST(100 AS DOUBLE)) = CAST(0 AS DOUBLE), 'a1', 'b1') AS `_o__c2` FROM `default`.`srcpart` WHERE `ds` = '2008-04-08' STAGE DEPENDENCIES: @@ -922,7 +922,7 @@ POSTHOOK: Input: default@list_bucketing_dynamic_part_n3 POSTHOOK: Input: default@list_bucketing_dynamic_part_n3@ds=2008-04-08/hr=a1 POSTHOOK: Input: default@list_bucketing_dynamic_part_n3@ds=2008-04-08/hr=b1 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('484' AS STRING) AS `key`, CAST('val_484' AS STRING) AS `value`, `ds`, `hr` +OPTIMIZED SQL: SELECT CAST('484' AS VARCHAR(65536)) AS `key`, CAST('val_484' AS VARCHAR(65536)) AS `value`, `ds`, `hr` FROM `default`.`list_bucketing_dynamic_part_n3` WHERE `key` = '484' AND `value` = 'val_484' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/list_bucket_dml_7.q.out ql/src/test/results/clientpositive/list_bucket_dml_7.q.out index ddfa3240e3..37635f54ac 100644 --- ql/src/test/results/clientpositive/list_bucket_dml_7.q.out +++ ql/src/test/results/clientpositive/list_bucket_dml_7.q.out @@ -29,7 +29,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=11 POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 -OPTIMIZED SQL: SELECT `key`, `value`, IF(MOD(CAST(`key` AS DOUBLE), CAST(100 AS DOUBLE)) = 0, 'a1', 'b1') AS `_o__c2` +OPTIMIZED SQL: SELECT `key`, `value`, IF(MOD(CAST(`key` AS DOUBLE), CAST(100 AS DOUBLE)) = CAST(0 AS DOUBLE), 'a1', 'b1') AS `_o__c2` FROM `default`.`srcpart` WHERE `ds` = '2008-04-08' STAGE DEPENDENCIES: @@ -404,7 +404,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=11 POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 -OPTIMIZED SQL: SELECT `key`, `value`, IF(MOD(CAST(`key` AS DOUBLE), CAST(100 AS DOUBLE)) = 0, 'a1', 'b1') AS `_o__c2` +OPTIMIZED SQL: SELECT `key`, `value`, IF(MOD(CAST(`key` AS DOUBLE), CAST(100 AS DOUBLE)) = CAST(0 AS DOUBLE), 'a1', 'b1') AS `_o__c2` FROM `default`.`srcpart` WHERE `ds` = '2008-04-08' STAGE DEPENDENCIES: @@ -922,7 +922,7 @@ POSTHOOK: Input: default@list_bucketing_dynamic_part POSTHOOK: Input: default@list_bucketing_dynamic_part@ds=2008-04-08/hr=a1 POSTHOOK: Input: default@list_bucketing_dynamic_part@ds=2008-04-08/hr=b1 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('484' AS STRING) AS `key`, CAST('val_484' AS STRING) AS `value`, `ds`, `hr` +OPTIMIZED SQL: SELECT CAST('484' AS VARCHAR(65536)) AS `key`, CAST('val_484' AS VARCHAR(65536)) AS `value`, `ds`, `hr` FROM `default`.`list_bucketing_dynamic_part` WHERE `key` = '484' AND `value` = 'val_484' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/list_bucket_dml_8.q.out ql/src/test/results/clientpositive/list_bucket_dml_8.q.out index 30e75e1d32..261b45b297 100644 --- ql/src/test/results/clientpositive/list_bucket_dml_8.q.out +++ ql/src/test/results/clientpositive/list_bucket_dml_8.q.out @@ -29,7 +29,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=11 POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 -OPTIMIZED SQL: SELECT `key`, `value`, IF(MOD(CAST(`key` AS DOUBLE), CAST(100 AS DOUBLE)) = 0, 'a1', 'b1') AS `_o__c2` +OPTIMIZED SQL: SELECT `key`, `value`, IF(MOD(CAST(`key` AS DOUBLE), CAST(100 AS DOUBLE)) = CAST(0 AS DOUBLE), 'a1', 'b1') AS `_o__c2` FROM `default`.`srcpart` WHERE `ds` = '2008-04-08' STAGE DEPENDENCIES: @@ -475,7 +475,7 @@ POSTHOOK: Input: default@list_bucketing_dynamic_part_n2 POSTHOOK: Input: default@list_bucketing_dynamic_part_n2@ds=2008-04-08/hr=a1 POSTHOOK: Input: default@list_bucketing_dynamic_part_n2@ds=2008-04-08/hr=b1 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('484' AS STRING) AS `key`, CAST('val_484' AS STRING) AS `value`, `ds`, `hr` +OPTIMIZED SQL: SELECT CAST('484' AS VARCHAR(65536)) AS `key`, CAST('val_484' AS VARCHAR(65536)) AS `value`, `ds`, `hr` FROM `default`.`list_bucketing_dynamic_part_n2` WHERE `key` = '484' AND `value` = 'val_484' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/list_bucket_dml_9.q.out ql/src/test/results/clientpositive/list_bucket_dml_9.q.out index c8876b7ba9..4315270dda 100644 --- ql/src/test/results/clientpositive/list_bucket_dml_9.q.out +++ ql/src/test/results/clientpositive/list_bucket_dml_9.q.out @@ -826,7 +826,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@list_bucketing_static_part_n0 POSTHOOK: Input: default@list_bucketing_static_part_n0@ds=2008-04-08/hr=11 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('484' AS STRING) AS `$f0`, CAST('val_484' AS STRING) AS `$f1`, CAST('2008-04-08' AS STRING) AS `$f2`, CAST('11' AS STRING) AS `$f3` +OPTIMIZED SQL: SELECT CAST('484' AS VARCHAR(65536)) AS `$f0`, CAST('val_484' AS VARCHAR(65536)) AS `$f1`, CAST('2008-04-08' AS VARCHAR(65536)) AS `$f2`, CAST('11' AS VARCHAR(65536)) AS `$f3` FROM `default`.`list_bucketing_static_part_n0` WHERE `ds` = '2008-04-08' AND `hr` = '11' AND `key` = '484' AND `value` = 'val_484' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/list_bucket_query_multiskew_1.q.out ql/src/test/results/clientpositive/list_bucket_query_multiskew_1.q.out index 901b2862e6..c553d57e20 100644 --- ql/src/test/results/clientpositive/list_bucket_query_multiskew_1.q.out +++ ql/src/test/results/clientpositive/list_bucket_query_multiskew_1.q.out @@ -86,7 +86,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@fact_daily POSTHOOK: Input: default@fact_daily@ds=1/hr=4 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('484' AS STRING) AS `$f0` +OPTIMIZED SQL: SELECT CAST('484' AS VARCHAR(65536)) AS `$f0` FROM `default`.`fact_daily` WHERE `ds` = '1' AND `hr` = '4' AND `key` = '484' AND `value` = 'val_484' STAGE DEPENDENCIES: @@ -215,7 +215,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@fact_daily POSTHOOK: Input: default@fact_daily@ds=1/hr=4 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('238' AS STRING) AS `$f0`, CAST('val_238' AS STRING) AS `$f1` +OPTIMIZED SQL: SELECT CAST('238' AS VARCHAR(65536)) AS `$f0`, CAST('val_238' AS VARCHAR(65536)) AS `$f1` FROM `default`.`fact_daily` WHERE `ds` = '1' AND `hr` = '4' AND `key` = '238' AND `value` = 'val_238' STAGE DEPENDENCIES: @@ -473,7 +473,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@fact_daily POSTHOOK: Input: default@fact_daily@ds=1/hr=4 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('495' AS STRING) AS `key`, `value` +OPTIMIZED SQL: SELECT CAST('495' AS VARCHAR(65536)) AS `key`, `value` FROM `default`.`fact_daily` WHERE `ds` = '1' AND `hr` = '4' AND `key` = '495' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/list_bucket_query_multiskew_2.q.out ql/src/test/results/clientpositive/list_bucket_query_multiskew_2.q.out index ba28d50307..96cbbadfd9 100644 --- ql/src/test/results/clientpositive/list_bucket_query_multiskew_2.q.out +++ ql/src/test/results/clientpositive/list_bucket_query_multiskew_2.q.out @@ -86,7 +86,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@fact_daily_n2 POSTHOOK: Input: default@fact_daily_n2@ds=1/hr=4 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `key`, CAST('val_484' AS STRING) AS `value` +OPTIMIZED SQL: SELECT `key`, CAST('val_484' AS VARCHAR(65536)) AS `value` FROM `default`.`fact_daily_n2` WHERE `ds` = '1' AND `hr` = '4' AND `value` = 'val_484' STAGE DEPENDENCIES: @@ -265,7 +265,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@fact_daily_n2 POSTHOOK: Input: default@fact_daily_n2@ds=1/hr=4 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('406' AS STRING) AS `$f0` +OPTIMIZED SQL: SELECT CAST('406' AS VARCHAR(65536)) AS `$f0` FROM `default`.`fact_daily_n2` WHERE `ds` = '1' AND `hr` = '4' AND `key` = '406' STAGE DEPENDENCIES: @@ -397,6 +397,9 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@fact_daily_n2 POSTHOOK: Input: default@fact_daily_n2@ds=1/hr=4 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value` +FROM `default`.`fact_daily_n2` +WHERE ROW(`key`, `value`) IN (ROW('484', 'val_484'), ROW('238', 'val_238')) AND `ds` = '1' AND `hr` = '4' STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 diff --git ql/src/test/results/clientpositive/list_bucket_query_multiskew_3.q.out ql/src/test/results/clientpositive/list_bucket_query_multiskew_3.q.out index 75c4aba78a..c5a1723778 100644 --- ql/src/test/results/clientpositive/list_bucket_query_multiskew_3.q.out +++ ql/src/test/results/clientpositive/list_bucket_query_multiskew_3.q.out @@ -196,7 +196,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@fact_daily_n3 POSTHOOK: Input: default@fact_daily_n3@ds=1/hr=1 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('145' AS STRING) AS `key`, `value`, CAST('1' AS STRING) AS `ds`, CAST('1' AS STRING) AS `hr` +OPTIMIZED SQL: SELECT CAST('145' AS VARCHAR(65536)) AS `key`, `value`, CAST('1' AS VARCHAR(65536)) AS `ds`, CAST('1' AS VARCHAR(65536)) AS `hr` FROM `default`.`fact_daily_n3` WHERE `ds` = '1' AND `hr` = '1' AND `key` = '145' STAGE DEPENDENCIES: @@ -359,7 +359,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@fact_daily_n3 POSTHOOK: Input: default@fact_daily_n3@ds=1/hr=2 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('484' AS STRING) AS `$f0`, CAST('val_484' AS STRING) AS `$f1`, CAST('1' AS STRING) AS `$f2`, CAST('2' AS STRING) AS `$f3` +OPTIMIZED SQL: SELECT CAST('484' AS VARCHAR(65536)) AS `$f0`, CAST('val_484' AS VARCHAR(65536)) AS `$f1`, CAST('1' AS VARCHAR(65536)) AS `$f2`, CAST('2' AS VARCHAR(65536)) AS `$f3` FROM `default`.`fact_daily_n3` WHERE `ds` = '1' AND `hr` = '2' AND `key` = '484' AND `value` = 'val_484' STAGE DEPENDENCIES: @@ -490,7 +490,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@fact_daily_n3 POSTHOOK: Input: default@fact_daily_n3@ds=1/hr=3 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('327' AS STRING) AS `$f0`, CAST('val_327' AS STRING) AS `$f1`, CAST('1' AS STRING) AS `$f2`, CAST('3' AS STRING) AS `$f3` +OPTIMIZED SQL: SELECT CAST('327' AS VARCHAR(65536)) AS `$f0`, CAST('val_327' AS VARCHAR(65536)) AS `$f1`, CAST('1' AS VARCHAR(65536)) AS `$f2`, CAST('3' AS VARCHAR(65536)) AS `$f3` FROM `default`.`fact_daily_n3` WHERE `ds` = '1' AND `hr` = '3' AND `key` = '327' AND `value` = 'val_327' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/llap/auto_sortmerge_join_12.q.out ql/src/test/results/clientpositive/llap/auto_sortmerge_join_12.q.out index 79620126a8..38ced46ffe 100644 --- ql/src/test/results/clientpositive/llap/auto_sortmerge_join_12.q.out +++ ql/src/test/results/clientpositive/llap/auto_sortmerge_join_12.q.out @@ -134,7 +134,7 @@ POSTHOOK: query: load data local inpath '../../data/files/auto_sortmerge_join/sm POSTHOOK: type: LOAD #### A masked pattern was here #### POSTHOOK: Output: default@bucket_medium@ds=2008-04-08 -Warning: Shuffle Join MERGEJOIN[54][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3]] in Stage 'Reducer 2' is a cross product +Warning: Shuffle Join MERGEJOIN[57][tables = [$hdt$_0, $hdt$_1]] in Stage 'Reducer 2' is a cross product PREHOOK: query: explain extended select count(*) FROM bucket_small_n15 a JOIN bucket_medium b ON a.key = b.key JOIN bucket_big_n15 c ON c.key = b.key JOIN bucket_medium d ON c.key = b.key PREHOOK: type: QUERY PREHOOK: Input: default@bucket_big_n15 @@ -156,17 +156,20 @@ POSTHOOK: Input: default@bucket_small_n15 POSTHOOK: Input: default@bucket_small_n15@ds=2008-04-08 #### A masked pattern was here #### OPTIMIZED SQL: SELECT COUNT(*) AS `$f0` +FROM (SELECT 0 AS `DUMMY` +FROM `default`.`bucket_medium`) AS `t`, +(SELECT 0 AS `DUMMY` +FROM (SELECT `t5`.`key`, `t3`.`key` AS `key0`, `t1`.`key` AS `key1` FROM (SELECT `key` FROM `default`.`bucket_big_n15` -WHERE `key` IS NOT NULL) AS `t0` +WHERE `key` IS NOT NULL) AS `t1` INNER JOIN (SELECT `key` FROM `default`.`bucket_medium` -WHERE `key` IS NOT NULL) AS `t2` ON `t0`.`key` = `t2`.`key` +WHERE `key` IS NOT NULL) AS `t3` ON `t1`.`key` = `t3`.`key` INNER JOIN (SELECT `key` FROM `default`.`bucket_small_n15` -WHERE `key` IS NOT NULL) AS `t4` ON `t2`.`key` = `t4`.`key`, -(SELECT 0 AS `DUMMY` -FROM `default`.`bucket_medium`) AS `t5` +WHERE `key` IS NOT NULL) AS `t5` ON `t3`.`key` = `t5`.`key`) AS `t6` +WHERE `t6`.`key1` = `t6`.`key0`) AS `t8` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -176,13 +179,84 @@ STAGE PLANS: Tez #### A masked pattern was here #### Edges: - Reducer 2 <- Map 1 (XPROD_EDGE), Map 6 (XPROD_EDGE) + Reducer 2 <- Map 1 (XPROD_EDGE), Map 4 (XPROD_EDGE) Reducer 3 <- Reducer 2 (CUSTOM_SIMPLE_EDGE) #### A masked pattern was here #### Vertices: Map 1 Map Operator Tree: TableScan + alias: d + Statistics: Num rows: 3 Data size: 1724 Basic stats: PARTIAL Column stats: COMPLETE + GatherStats: false + Select Operator + Statistics: Num rows: 3 Data size: 1724 Basic stats: PARTIAL Column stats: COMPLETE + Reduce Output Operator + null sort order: + sort order: + Statistics: Num rows: 3 Data size: 1724 Basic stats: PARTIAL Column stats: COMPLETE + tag: 0 + auto parallelism: false + Execution mode: vectorized, llap + LLAP IO: no inputs + Path -> Alias: +#### A masked pattern was here #### + Path -> Partition: +#### A masked pattern was here #### + Partition + base file name: ds=2008-04-08 + input format: org.apache.hadoop.mapred.TextInputFormat + output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat + partition values: + ds 2008-04-08 + properties: + bucket_count 3 + bucket_field_name key + column.name.delimiter , + columns key,value + columns.comments + columns.types string:string +#### A masked pattern was here #### + name default.bucket_medium + numFiles 3 + numRows 0 + partition_columns ds + partition_columns.types string + rawDataSize 0 + serialization.ddl struct bucket_medium { string key, string value} + serialization.format 1 + serialization.lib org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + totalSize 170 +#### A masked pattern was here #### + serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + + input format: org.apache.hadoop.mapred.TextInputFormat + output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat + properties: + SORTBUCKETCOLSPREFIX TRUE + bucket_count 3 + bucket_field_name key + bucketing_version 2 + column.name.delimiter , + columns key,value + columns.comments + columns.types string:string +#### A masked pattern was here #### + name default.bucket_medium + partition_columns ds + partition_columns.types string + serialization.ddl struct bucket_medium { string key, string value} + serialization.format 1 + serialization.lib org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe +#### A masked pattern was here #### + serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + name: default.bucket_medium + name: default.bucket_medium + Truncated Path -> Alias: + /bucket_medium/ds=2008-04-08 [d] + Map 4 + Map Operator Tree: + TableScan alias: b filterExpr: key is not null (type: boolean) Statistics: Num rows: 3 Data size: 552 Basic stats: PARTIAL Column stats: NONE @@ -339,14 +413,25 @@ STAGE PLANS: 0 _col0 (type: string) 1 _col0 (type: string) 2 _col0 (type: string) + outputColumnNames: _col0, _col1 Position of Big Table: 0 Statistics: Num rows: 464 Data size: 75446 Basic stats: PARTIAL Column stats: NONE - Reduce Output Operator - null sort order: - sort order: + Select Operator + expressions: _col1 (type: string), _col0 (type: string) + outputColumnNames: _col1, _col2 Statistics: Num rows: 464 Data size: 75446 Basic stats: PARTIAL Column stats: NONE - tag: 0 - auto parallelism: false + Filter Operator + isSamplingPred: false + predicate: (_col2 = _col1) (type: boolean) + Statistics: Num rows: 232 Data size: 37723 Basic stats: PARTIAL Column stats: NONE + Select Operator + Statistics: Num rows: 232 Data size: 37723 Basic stats: PARTIAL Column stats: NONE + Reduce Output Operator + null sort order: + sort order: + Statistics: Num rows: 232 Data size: 37723 Basic stats: PARTIAL Column stats: NONE + tag: 1 + auto parallelism: false Execution mode: llap Path -> Alias: #### A masked pattern was here #### @@ -452,77 +537,6 @@ STAGE PLANS: Truncated Path -> Alias: /bucket_big_n15/ds=2008-04-08 [c] /bucket_big_n15/ds=2008-04-09 [c] - Map 6 - Map Operator Tree: - TableScan - alias: d - Statistics: Num rows: 3 Data size: 1724 Basic stats: PARTIAL Column stats: COMPLETE - GatherStats: false - Select Operator - Statistics: Num rows: 3 Data size: 1724 Basic stats: PARTIAL Column stats: COMPLETE - Reduce Output Operator - null sort order: - sort order: - Statistics: Num rows: 3 Data size: 1724 Basic stats: PARTIAL Column stats: COMPLETE - tag: 1 - auto parallelism: false - Execution mode: vectorized, llap - LLAP IO: no inputs - Path -> Alias: -#### A masked pattern was here #### - Path -> Partition: -#### A masked pattern was here #### - Partition - base file name: ds=2008-04-08 - input format: org.apache.hadoop.mapred.TextInputFormat - output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat - partition values: - ds 2008-04-08 - properties: - bucket_count 3 - bucket_field_name key - column.name.delimiter , - columns key,value - columns.comments - columns.types string:string -#### A masked pattern was here #### - name default.bucket_medium - numFiles 3 - numRows 0 - partition_columns ds - partition_columns.types string - rawDataSize 0 - serialization.ddl struct bucket_medium { string key, string value} - serialization.format 1 - serialization.lib org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe - totalSize 170 -#### A masked pattern was here #### - serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe - - input format: org.apache.hadoop.mapred.TextInputFormat - output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat - properties: - SORTBUCKETCOLSPREFIX TRUE - bucket_count 3 - bucket_field_name key - bucketing_version 2 - column.name.delimiter , - columns key,value - columns.comments - columns.types string:string -#### A masked pattern was here #### - name default.bucket_medium - partition_columns ds - partition_columns.types string - serialization.ddl struct bucket_medium { string key, string value} - serialization.format 1 - serialization.lib org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe -#### A masked pattern was here #### - serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe - name: default.bucket_medium - name: default.bucket_medium - Truncated Path -> Alias: - /bucket_medium/ds=2008-04-08 [d] Reducer 2 Execution mode: llap Needs Tagging: false @@ -534,7 +548,7 @@ STAGE PLANS: 0 1 Position of Big Table: 0 - Statistics: Num rows: 1392 Data size: 1027666 Basic stats: PARTIAL Column stats: NONE + Statistics: Num rows: 696 Data size: 513833 Basic stats: PARTIAL Column stats: NONE Group By Operator aggregations: count() mode: hash @@ -585,7 +599,7 @@ STAGE PLANS: Processor Tree: ListSink -Warning: Shuffle Join MERGEJOIN[54][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3]] in Stage 'Reducer 2' is a cross product +Warning: Shuffle Join MERGEJOIN[57][tables = [$hdt$_0, $hdt$_1]] in Stage 'Reducer 2' is a cross product PREHOOK: query: select count(*) FROM bucket_small_n15 a JOIN bucket_medium b ON a.key = b.key JOIN bucket_big_n15 c ON c.key = b.key JOIN bucket_medium d ON c.key = b.key PREHOOK: type: QUERY PREHOOK: Input: default@bucket_big_n15 diff --git ql/src/test/results/clientpositive/llap/auto_sortmerge_join_16.q.out ql/src/test/results/clientpositive/llap/auto_sortmerge_join_16.q.out index 2c6d7cafa7..4e156926d6 100644 --- ql/src/test/results/clientpositive/llap/auto_sortmerge_join_16.q.out +++ ql/src/test/results/clientpositive/llap/auto_sortmerge_join_16.q.out @@ -222,7 +222,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: bucket_small_n17 - filterExpr: pri BETWEEN 1 AND 2 (type: boolean) + filterExpr: pri BETWEEN 1L AND 2L (type: boolean) Statistics: Num rows: 236 Data size: 45636 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: key (type: bigint), value (type: string) @@ -370,7 +370,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: bucket_small_n17 - filterExpr: pri BETWEEN 1 AND 2 (type: boolean) + filterExpr: pri BETWEEN 1L AND 2L (type: boolean) Statistics: Num rows: 236 Data size: 45636 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: key (type: bigint), value (type: string) @@ -626,7 +626,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: bucket_small_n17 - filterExpr: pri BETWEEN 1 AND 2 (type: boolean) + filterExpr: pri BETWEEN 1L AND 2L (type: boolean) Statistics: Num rows: 236 Data size: 45636 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: key (type: bigint), value (type: string) diff --git ql/src/test/results/clientpositive/llap/bucket_map_join_tez2.q.out ql/src/test/results/clientpositive/llap/bucket_map_join_tez2.q.out index 5de5a69f87..bf015e1171 100644 --- ql/src/test/results/clientpositive/llap/bucket_map_join_tez2.q.out +++ ql/src/test/results/clientpositive/llap/bucket_map_join_tez2.q.out @@ -2358,6 +2358,13 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@my_dim POSTHOOK: Input: default@my_fact #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `t0`.`bucket_col`, `t2`.`join_col` AS `account1`, `t0`.`accounting_period` +FROM (SELECT `bucket_col`, `join_col`, `accounting_period` +FROM `default`.`my_fact` +WHERE `fiscal_year` = '2015' AND `accounting_period` = 10 AND `join_col` IS NOT NULL) AS `t0` +INNER JOIN (SELECT `join_col` +FROM `default`.`my_dim` +WHERE `filter_col` IN ('VAL1', 'VAL2') AND `join_col` IS NOT NULL) AS `t2` ON `t0`.`join_col` = `t2`.`join_col` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 diff --git ql/src/test/results/clientpositive/llap/bucketpruning1.q.out ql/src/test/results/clientpositive/llap/bucketpruning1.q.out index 934b383af5..1548267a38 100644 --- ql/src/test/results/clientpositive/llap/bucketpruning1.q.out +++ ql/src/test/results/clientpositive/llap/bucketpruning1.q.out @@ -369,7 +369,7 @@ select * from srcbucket_pruned where key = 1 and ds='2008-04-08' POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST(1 AS INTEGER) AS `key`, `value`, CAST('2008-04-08' AS STRING) AS `ds` +OPTIMIZED SQL: SELECT CAST(1 AS INTEGER) AS `key`, `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds` FROM `default`.`srcbucket_pruned` WHERE `key` = 1 AND `ds` = '2008-04-08' STAGE DEPENDENCIES: @@ -438,7 +438,7 @@ select * from srcbucket_pruned where key = 1 and ds='2008-04-08' and value='One' POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST(1 AS INTEGER) AS `$f0`, CAST('One' AS STRING) AS `$f1`, CAST('2008-04-08' AS STRING) AS `$f2` +OPTIMIZED SQL: SELECT CAST(1 AS INTEGER) AS `$f0`, CAST('One' AS VARCHAR(65536)) AS `$f1`, CAST('2008-04-08' AS VARCHAR(65536)) AS `$f2` FROM `default`.`srcbucket_pruned` WHERE `key` = 1 AND `ds` = '2008-04-08' AND `value` = 'One' STAGE DEPENDENCIES: @@ -507,7 +507,7 @@ select * from srcbucket_pruned where value='One' and key = 1 and ds='2008-04-08' POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST(1 AS INTEGER) AS `$f0`, CAST('One' AS STRING) AS `$f1`, CAST('2008-04-08' AS STRING) AS `$f2` +OPTIMIZED SQL: SELECT CAST(1 AS INTEGER) AS `$f0`, CAST('One' AS VARCHAR(65536)) AS `$f1`, CAST('2008-04-08' AS VARCHAR(65536)) AS `$f2` FROM `default`.`srcbucket_pruned` WHERE `value` = 'One' AND `key` = 1 AND `ds` = '2008-04-08' STAGE DEPENDENCIES: @@ -576,6 +576,9 @@ select * from srcbucket_pruned where key in (2,3) POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, `ds` +FROM `default`.`srcbucket_pruned` +WHERE `key` IN (2, 3) STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -642,6 +645,9 @@ select * from srcbucket_pruned where key in (2,3) and ds='2008-04-08' POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds` +FROM `default`.`srcbucket_pruned` +WHERE `key` IN (2, 3) AND `ds` = '2008-04-08' STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -708,6 +714,9 @@ select * from srcbucket_pruned where key in (2,3) and ds='2008-04-08' and value= POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, CAST('One' AS VARCHAR(65536)) AS `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds` +FROM `default`.`srcbucket_pruned` +WHERE `key` IN (2, 3) AND `ds` = '2008-04-08' AND `value` = 'One' STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -774,6 +783,9 @@ select * from srcbucket_pruned where value='One' and key in (2,3) and ds='2008-0 POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, CAST('One' AS VARCHAR(65536)) AS `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds` +FROM `default`.`srcbucket_pruned` +WHERE `key` IN (2, 3) AND `value` = 'One' AND `ds` = '2008-04-08' STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -840,6 +852,9 @@ select * from srcbucket_pruned where (key=1 or key=2) and ds='2008-04-08' POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds` +FROM `default`.`srcbucket_pruned` +WHERE `key` IN (1, 2) AND `ds` = '2008-04-08' STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -906,6 +921,9 @@ select * from srcbucket_pruned where (key=1 or key=2) and value = 'One' and ds=' POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, CAST('One' AS VARCHAR(65536)) AS `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds` +FROM `default`.`srcbucket_pruned` +WHERE `key` IN (1, 2) AND `value` = 'One' AND `ds` = '2008-04-08' STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1041,6 +1059,9 @@ select * from srcbucket_pruned where key in (1,2,3,4,5,6,7,8,9,10,11,12,13,14,15 POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, `ds` +FROM `default`.`srcbucket_pruned` +WHERE `key` IN (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17) STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1107,6 +1128,9 @@ select * from srcbucket_pruned where key in (1,2,3,4,5,6,7,8,9,10,11,12,13,14,15 POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds` +FROM `default`.`srcbucket_pruned` +WHERE `key` IN (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17) AND `ds` = '2008-04-08' STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1173,6 +1197,9 @@ select * from srcbucket_pruned where key in (1,2,3,4,5,6,7,8,9,10,11,12,13,14,15 POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, CAST('One' AS VARCHAR(65536)) AS `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds` +FROM `default`.`srcbucket_pruned` +WHERE `key` IN (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17) AND `ds` = '2008-04-08' AND `value` = 'One' STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1239,6 +1266,9 @@ select * from srcbucket_pruned where value='One' and key in (1,2,3,4,5,6,7,8,9,1 POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, CAST('One' AS VARCHAR(65536)) AS `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds` +FROM `default`.`srcbucket_pruned` +WHERE `key` IN (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17) AND `value` = 'One' AND `ds` = '2008-04-08' STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1373,6 +1403,9 @@ select * from srcbucket_pruned where key = 1 and ds='2008-04-08' and (value='One POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### +OPTIMIZED SQL: SELECT CAST(1 AS INTEGER) AS `key`, `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds` +FROM `default`.`srcbucket_pruned` +WHERE `value` IN ('One', 'Two') AND `key` = 1 AND `ds` = '2008-04-08' STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1509,7 +1542,7 @@ POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### OPTIMIZED SQL: SELECT `key`, `value`, `ds` FROM `default`.`srcbucket_pruned` -WHERE NULL +WHERE FALSE STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1642,6 +1675,9 @@ select * from srcbucket_pruned where key = 1 or value = "One" or key = 2 POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_pruned #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, `ds` +FROM `default`.`srcbucket_pruned` +WHERE `key` IN (1, 2) OR `value` = 'One' STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1707,6 +1743,9 @@ select * from srcbucket_unpruned where key in (3, 5) POSTHOOK: type: QUERY POSTHOOK: Input: default@srcbucket_unpruned #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, `ds` +FROM `default`.`srcbucket_unpruned` +WHERE `key` IN (3, 5) STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 diff --git ql/src/test/results/clientpositive/llap/cbo_simple_select.q.out ql/src/test/results/clientpositive/llap/cbo_simple_select.q.out index acf91bf178..3aa929d13c 100644 --- ql/src/test/results/clientpositive/llap/cbo_simple_select.q.out +++ ql/src/test/results/clientpositive/llap/cbo_simple_select.q.out @@ -761,9 +761,9 @@ STAGE PLANS: Processor Tree: TableScan alias: cbo_t2 - filterExpr: (c_int = c_int) (type: boolean) + filterExpr: c_int is not null (type: boolean) Filter Operator - predicate: (c_int = c_int) (type: boolean) + predicate: c_int is not null (type: boolean) Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 @@ -821,9 +821,9 @@ STAGE PLANS: Processor Tree: TableScan alias: cbo_t2 - filterExpr: (c_int = c_int) (type: boolean) + filterExpr: c_int is not null (type: boolean) Filter Operator - predicate: (c_int = c_int) (type: boolean) + predicate: c_int is not null (type: boolean) Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 @@ -833,13 +833,11 @@ PREHOOK: query: -- c_int is not null EXPLAIN select * from cbo_t2 where (cbo_t2.c_int) IN (NULL) PREHOOK: type: QUERY PREHOOK: Input: default@cbo_t2 -PREHOOK: Input: default@cbo_t2@dt=2014 #### A masked pattern was here #### POSTHOOK: query: -- c_int is not null EXPLAIN select * from cbo_t2 where (cbo_t2.c_int) IN (NULL) POSTHOOK: type: QUERY POSTHOOK: Input: default@cbo_t2 -POSTHOOK: Input: default@cbo_t2@dt=2014 #### A masked pattern was here #### STAGE DEPENDENCIES: Stage-0 is a root stage @@ -851,11 +849,10 @@ STAGE PLANS: Processor Tree: TableScan alias: cbo_t2 - filterExpr: (c_int = null) (type: boolean) Filter Operator - predicate: (c_int = null) (type: boolean) + predicate: false (type: boolean) Select Operator - expressions: key (type: string), value (type: string), null (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) + expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 ListSink @@ -881,9 +878,9 @@ STAGE PLANS: Processor Tree: TableScan alias: cbo_t2 - filterExpr: ((c_int = c_int) or (c_int = (2 * c_int))) (type: boolean) + filterExpr: (c_int is not null or (c_int = (2 * c_int))) (type: boolean) Filter Operator - predicate: ((c_int = (2 * c_int)) or (c_int = c_int)) (type: boolean) + predicate: ((c_int = (2 * c_int)) or c_int is not null) (type: boolean) Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 @@ -911,9 +908,9 @@ STAGE PLANS: Processor Tree: TableScan alias: cbo_t2 - filterExpr: ((c_int = c_int) or (c_int = 0)) (type: boolean) + filterExpr: (c_int is not null or (c_int = 0)) (type: boolean) Filter Operator - predicate: ((c_int = 0) or (c_int = c_int)) (type: boolean) + predicate: ((c_int = 0) or c_int is not null) (type: boolean) Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 diff --git ql/src/test/results/clientpositive/llap/constraints_optimization.q.out ql/src/test/results/clientpositive/llap/constraints_optimization.q.out index f7ed9f58a8..7bdf1f6a4f 100644 --- ql/src/test/results/clientpositive/llap/constraints_optimization.q.out +++ ql/src/test/results/clientpositive/llap/constraints_optimization.q.out @@ -2526,7 +2526,7 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(d_date_sk=[$0]) HiveFilter(condition=[AND(=($6, 2002), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject($f0=[$0]) + HiveProject(customer_id=[$0]) HiveFilter(condition=[>($1, 0)]) HiveAggregate(group=[{1}], agg#0=[sum($10)]) HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/llap/count.q.out ql/src/test/results/clientpositive/llap/count.q.out index 047d948887..ba0d4078dd 100644 --- ql/src/test/results/clientpositive/llap/count.q.out +++ ql/src/test/results/clientpositive/llap/count.q.out @@ -378,7 +378,7 @@ STAGE PLANS: Statistics: Num rows: 1 Data size: 336 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: $f0 (type: bigint), $f0 (type: bigint), $f1 (type: bigint), $f2 (type: bigint), $f3 (type: bigint), $f4 (type: bigint), $f5 (type: bigint), $f6 (type: bigint), $f7 (type: bigint), $f8 (type: bigint), $f9 (type: bigint), $f10 (type: bigint), $f11 (type: bigint), $f12 (type: bigint), $f13 (type: bigint), $f14 (type: bigint), $f15 (type: bigint), $f16 (type: bigint), $f17 (type: bigint), $f18 (type: bigint), $f19 (type: bigint) - outputColumnNames: $f0, $f00, $f1, $f2, $f3, $f4, $f5, $f6, $f7, $f8, $f9, $f10, $f11, $f12, $f13, $f14, $f15, $f16, $f17, $f18, $f19 + outputColumnNames: _o__c0, _o__c1, _o__c2, _o__c3, _o__c4, _o__c5, _o__c6, _o__c7, _o__c8, _o__c9, _o__c10, _o__c11, _o__c12, _o__c13, _o__c14, _o__c15, _o__c16, _o__c17, _o__c18, _o__c19, _o__c20 Statistics: Num rows: 1 Data size: 336 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false @@ -943,7 +943,7 @@ STAGE PLANS: Statistics: Num rows: 1 Data size: 176 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: $f0 (type: bigint), $f0 (type: bigint), $f1 (type: bigint), $f2 (type: bigint), $f3 (type: bigint), $f4 (type: bigint), $f5 (type: bigint), $f6 (type: bigint), $f7 (type: bigint), $f8 (type: bigint), $f9 (type: bigint), $f10 (type: bigint), $f11 (type: bigint), $f12 (type: bigint), $f13 (type: bigint), $f14 (type: bigint), $f15 (type: bigint), $f16 (type: bigint), $f17 (type: bigint), $f18 (type: bigint), $f19 (type: bigint) - outputColumnNames: $f0, $f00, $f1, $f2, $f3, $f4, $f5, $f6, $f7, $f8, $f9, $f10, $f11, $f12, $f13, $f14, $f15, $f16, $f17, $f18, $f19 + outputColumnNames: _o__c0, _o__c1, _o__c2, _o__c3, _o__c4, _o__c5, _o__c6, _o__c7, _o__c8, _o__c9, _o__c10, _o__c11, _o__c12, _o__c13, _o__c14, _o__c15, _o__c16, _o__c17, _o__c18, _o__c19, _o__c20 Statistics: Num rows: 1 Data size: 176 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false diff --git ql/src/test/results/clientpositive/llap/current_date_timestamp.q.out ql/src/test/results/clientpositive/llap/current_date_timestamp.q.out index 280ffb07e1..6dbca90c61 100644 --- ql/src/test/results/clientpositive/llap/current_date_timestamp.q.out +++ ql/src/test/results/clientpositive/llap/current_date_timestamp.q.out @@ -47,7 +47,7 @@ POSTHOOK: query: explain extended select current_timestamp() from alltypesorc POSTHOOK: type: QUERY POSTHOOK: Input: default@alltypesorc #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CURRENT_TIMESTAMP() AS `$f0` +OPTIMIZED SQL: SELECT CURRENT_TIMESTAMP() AS `_o__c0` FROM `default`.`alltypesorc` STAGE DEPENDENCIES: Stage-0 is a root stage diff --git ql/src/test/results/clientpositive/llap/explainuser_1.q.out ql/src/test/results/clientpositive/llap/explainuser_1.q.out index 2bb6352a7e..83a2808f97 100644 --- ql/src/test/results/clientpositive/llap/explainuser_1.q.out +++ ql/src/test/results/clientpositive/llap/explainuser_1.q.out @@ -1859,7 +1859,7 @@ Stage-0 Group By Operator [GBY_3] (rows=1 width=101) Output:["_col0","_col1","_col2","_col3"],aggregations:["sum(c_int)"],keys:key, c_int, c_float Filter Operator [FIL_41] (rows=1 width=93) - predicate:((((c_int + 1) + 1) >= 0) and (((c_int + 1) > 0) or (UDFToDouble(key) >= 0.0D)) and ((UDFToFloat(c_int) + c_float) >= 0) and ((c_int + 1) >= 0) and ((c_int > 0) or c_float is not null) and ((c_int >= 1) or (c_float >= 1.0)) and (UDFToDouble(key) > 0.0D) and (c_float > 0.0)) + predicate:((((c_int + 1) + 1) >= 0) and ((UDFToFloat(c_int) + c_float) >= 0) and ((c_int + 1) >= 0) and ((c_int > 0) or c_float is not null) and ((c_int >= 1) or (c_float >= 1.0)) and (UDFToDouble(key) > 0.0D) and (c_float > 0.0)) TableScan [TS_0] (rows=20 width=88) default@cbo_t1,cbo_t1,Tbl:COMPLETE,Col:COMPLETE,Output:["key","c_int","c_float"] <-Reducer 7 [SIMPLE_EDGE] llap @@ -2553,7 +2553,7 @@ Stage-0 Select Operator [SEL_24] (rows=631 width=178) Output:["_col0","_col1"] Filter Operator [FIL_23] (rows=631 width=194) - predicate:((_col2 = 0L) or (_col5 is null and _col0 is not null and (_col3 >= _col2))) + predicate:(((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col0 is null) and (_col0 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) Select Operator [SEL_22] (rows=631 width=194) Output:["_col0","_col1","_col2","_col3","_col5"] Merge Join Operator [MERGEJOIN_37] (rows=631 width=194) @@ -2631,10 +2631,10 @@ Stage-0 Stage-1 Reducer 3 llap File Output Operator [FS_24] - Select Operator [SEL_23] (rows=19 width=223) + Select Operator [SEL_23] (rows=38 width=223) Output:["_col0","_col1","_col2"] - Filter Operator [FIL_22] (rows=19 width=234) - predicate:CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END + Filter Operator [FIL_22] (rows=38 width=234) + predicate:(((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col0 is null) and (_col0 is not null or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) Merge Join Operator [MERGEJOIN_45] (rows=38 width=234) Conds:RS_19._col0, _col1=RS_20._col0, _col1(Left Outer),Output:["_col0","_col1","_col2","_col4","_col5","_col8"] <-Reducer 2 [SIMPLE_EDGE] llap @@ -2723,7 +2723,7 @@ Stage-0 Select Operator [SEL_29] (rows=27 width=125) Output:["_col0","_col1"] Filter Operator [FIL_28] (rows=27 width=141) - predicate:((_col2 = 0L) or (_col5 is null and _col1 is not null and (_col3 >= _col2))) + predicate:(((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col1 is null) and (_col1 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) Select Operator [SEL_27] (rows=27 width=141) Output:["_col0","_col1","_col2","_col3","_col5"] Merge Join Operator [MERGEJOIN_38] (rows=27 width=141) @@ -2803,14 +2803,14 @@ Stage-0 Stage-1 Reducer 5 llap File Output Operator [FS_36] - Select Operator [SEL_35] (rows=3 width=106) + Select Operator [SEL_35] (rows=7 width=106) Output:["_col0","_col1"] <-Reducer 4 [SIMPLE_EDGE] llap SHUFFLE [RS_34] - Select Operator [SEL_33] (rows=3 width=106) + Select Operator [SEL_33] (rows=7 width=106) Output:["_col0","_col1"] - Filter Operator [FIL_32] (rows=3 width=118) - predicate:CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END + Filter Operator [FIL_32] (rows=7 width=114) + predicate:(((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col0 is null) and (_col0 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) Merge Join Operator [MERGEJOIN_48] (rows=7 width=114) Conds:RS_29._col0, _col1=RS_30._col0, _col1(Left Outer),Output:["_col0","_col1","_col3","_col4","_col7"] <-Reducer 3 [SIMPLE_EDGE] llap diff --git ql/src/test/results/clientpositive/llap/join_constraints_optimization.q.out ql/src/test/results/clientpositive/llap/join_constraints_optimization.q.out index 1098bb41f3..087db3c842 100644 --- ql/src/test/results/clientpositive/llap/join_constraints_optimization.q.out +++ ql/src/test/results/clientpositive/llap/join_constraints_optimization.q.out @@ -694,28 +694,27 @@ STAGE PLANS: Tez #### A masked pattern was here #### Edges: - Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 4 (SIMPLE_EDGE) - Reducer 3 <- Map 5 (SIMPLE_EDGE), Reducer 2 (SIMPLE_EDGE) + Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 3 (SIMPLE_EDGE) #### A masked pattern was here #### Vertices: Map 1 Map Operator Tree: TableScan alias: lineorder_removal_n0 - Statistics: Num rows: 1 Data size: 20 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 12 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: lo_linenumber (type: int), lo_custkey (type: bigint), lo_orderdate (type: bigint) - outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 1 Data size: 20 Basic stats: COMPLETE Column stats: NONE + expressions: lo_linenumber (type: int), lo_orderdate (type: bigint) + outputColumnNames: _col0, _col1 + Statistics: Num rows: 1 Data size: 12 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator - key expressions: _col2 (type: bigint) + key expressions: _col1 (type: bigint) sort order: + - Map-reduce partition columns: _col2 (type: bigint) - Statistics: Num rows: 1 Data size: 20 Basic stats: COMPLETE Column stats: NONE - value expressions: _col0 (type: int), _col1 (type: bigint) + Map-reduce partition columns: _col1 (type: bigint) + Statistics: Num rows: 1 Data size: 12 Basic stats: COMPLETE Column stats: NONE + value expressions: _col0 (type: int) Execution mode: vectorized, llap LLAP IO: no inputs - Map 4 + Map 3 Map Operator Tree: TableScan alias: dates_removal_n0 @@ -731,22 +730,6 @@ STAGE PLANS: Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE Execution mode: vectorized, llap LLAP IO: no inputs - Map 5 - Map Operator Tree: - TableScan - alias: customer_removal_n0 - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE - Select Operator - expressions: c_custkey (type: bigint) - outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: bigint) - sort order: + - Map-reduce partition columns: _col0 (type: bigint) - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE - Execution mode: vectorized, llap - LLAP IO: no inputs Reducer 2 Execution mode: llap Reduce Operator Tree: @@ -754,30 +737,13 @@ STAGE PLANS: condition map: Left Outer Join 0 to 1 keys: - 0 _col2 (type: bigint) - 1 _col0 (type: bigint) - outputColumnNames: _col0, _col1 - Statistics: Num rows: 1 Data size: 22 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col1 (type: bigint) - sort order: + - Map-reduce partition columns: _col1 (type: bigint) - Statistics: Num rows: 1 Data size: 22 Basic stats: COMPLETE Column stats: NONE - value expressions: _col0 (type: int) - Reducer 3 - Execution mode: llap - Reduce Operator Tree: - Merge Join Operator - condition map: - Left Outer Join 0 to 1 - keys: 0 _col1 (type: bigint) 1 _col0 (type: bigint) outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 24 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 13 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 24 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 13 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat diff --git ql/src/test/results/clientpositive/llap/kryo.q.out ql/src/test/results/clientpositive/llap/kryo.q.out index 5d556f46c0..fbefbfdd22 100644 --- ql/src/test/results/clientpositive/llap/kryo.q.out +++ ql/src/test/results/clientpositive/llap/kryo.q.out @@ -49,24 +49,24 @@ STAGE PLANS: TableScan alias: datetime_ filterExpr: (id) IN (1, 2, 3, 4, 5, 6) (type: boolean) - Statistics: Num rows: 1 Data size: 372 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 556 Basic stats: COMPLETE Column stats: NONE Filter Operator predicate: (id) IN (1, 2, 3, 4, 5, 6) (type: boolean) - Statistics: Num rows: 1 Data size: 372 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 556 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: if((id) IN (1, 2), if((id = 1), date_, date_), if((id = 3), CASE WHEN ((date_ is null or to_date(CAST( datetime AS TIMESTAMP)) is null)) THEN (null) WHEN ((CAST( date_ AS DATE) > to_date(CAST( datetime AS TIMESTAMP)))) THEN (date_) ELSE (CAST( to_date(CAST( datetime AS TIMESTAMP)) AS STRING)) END, null)) (type: string), id (type: int), CASE WHEN ((id = 6)) THEN (CASE WHEN ((concat(date_, ' 00:00:00') is null or datetime is null)) THEN (null) WHEN ((concat(date_, ' 00:00:00') > datetime)) THEN (concat(date_, ' 00:00:00')) ELSE (datetime) END) WHEN ((id = 5)) THEN (CASE WHEN ((date_ is null or datetime is null)) THEN (null) WHEN ((date_ > datetime)) THEN (date_) ELSE (datetime) END) WHEN ((id = 3)) THEN (concat(date_, ' 00:00:00')) WHEN ((id = 4)) THEN (concat(date_, ' 00:00:00')) WHEN ((id = 1)) THEN (date_) WHEN ((id = 2)) THEN (date_) ELSE (null) END (type: string) + expressions: if((id) IN (1, 2), if((id = 1), CASE WHEN (true) THEN (date_) WHEN (false) THEN (CAST( to_date(CAST( datetime AS TIMESTAMP)) AS STRING)) ELSE (null) END, CASE WHEN (true) THEN (date_) WHEN (false) THEN (CAST( to_date(CAST( datetime AS TIMESTAMP)) AS STRING)) ELSE (CAST( to_date(CAST( time AS TIMESTAMP)) AS STRING)) END), if((id = 3), CASE WHEN ((date_ is null or to_date(CAST( datetime AS TIMESTAMP)) is null)) THEN (null) WHEN ((CAST( date_ AS DATE) > to_date(CAST( datetime AS TIMESTAMP)))) THEN (date_) ELSE (CAST( to_date(CAST( datetime AS TIMESTAMP)) AS STRING)) END, null)) (type: string), id (type: int), CASE WHEN ((id = 6)) THEN (CASE WHEN ((concat(date_, ' 00:00:00') is null or datetime is null)) THEN (null) WHEN ((concat(date_, ' 00:00:00') > datetime)) THEN (concat(date_, ' 00:00:00')) ELSE (datetime) END) WHEN ((id = 5)) THEN (CASE WHEN ((date_ is null or datetime is null)) THEN (null) WHEN ((date_ > datetime)) THEN (date_) ELSE (datetime) END) WHEN ((id) IN (3, 4)) THEN (concat(date_, ' 00:00:00')) WHEN ((id) IN (1, 2)) THEN (date_) ELSE (null) END (type: string) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 1 Data size: 372 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 556 Basic stats: COMPLETE Column stats: NONE Group By Operator keys: _col0 (type: string), _col1 (type: int), _col2 (type: string) mode: hash outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 1 Data size: 372 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 556 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string), _col1 (type: int), _col2 (type: string) sort order: +++ Map-reduce partition columns: _col0 (type: string), _col1 (type: int), _col2 (type: string) - Statistics: Num rows: 1 Data size: 372 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 556 Basic stats: COMPLETE Column stats: NONE Execution mode: vectorized, llap LLAP IO: all inputs Reducer 2 @@ -76,10 +76,10 @@ STAGE PLANS: keys: KEY._col0 (type: string), KEY._col1 (type: int), KEY._col2 (type: string) mode: mergepartial outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 1 Data size: 372 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 556 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 372 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 556 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat diff --git ql/src/test/results/clientpositive/llap/lineage2.q.out ql/src/test/results/clientpositive/llap/lineage2.q.out index 8f266f8f25..76cb71adac 100644 --- ql/src/test/results/clientpositive/llap/lineage2.q.out +++ ql/src/test/results/clientpositive/llap/lineage2.q.out @@ -119,7 +119,7 @@ PREHOOK: type: QUERY PREHOOK: Input: default@src1 PREHOOK: Input: default@src2 #### A masked pattern was here #### -{"version":"1.0","engine":"tez","database":"default","hash":"8a689d34ce64f6ede5c3f5665fb5c3e7","queryText":"select key k from src1 union select key2 from src2 order by k","edges":[{"sources":[1,2],"targets":[0],"expression":"key","edgeType":"PROJECTION"}],"vertices":[{"id":0,"vertexType":"COLUMN","vertexId":"k"},{"id":1,"vertexType":"COLUMN","vertexId":"default.src1.key"},{"id":2,"vertexType":"COLUMN","vertexId":"default.src2.key2"}]} +{"version":"1.0","engine":"tez","database":"default","hash":"8a689d34ce64f6ede5c3f5665fb5c3e7","queryText":"select key k from src1 union select key2 from src2 order by k","edges":[{"sources":[1,2],"targets":[0],"expression":"k","edgeType":"PROJECTION"}],"vertices":[{"id":0,"vertexType":"COLUMN","vertexId":"k"},{"id":1,"vertexType":"COLUMN","vertexId":"default.src1.key"},{"id":2,"vertexType":"COLUMN","vertexId":"default.src2.key2"}]} 128 146 diff --git ql/src/test/results/clientpositive/llap/lineage3.q.out ql/src/test/results/clientpositive/llap/lineage3.q.out index 11e6904a12..121f1e7fc3 100644 --- ql/src/test/results/clientpositive/llap/lineage3.q.out +++ ql/src/test/results/clientpositive/llap/lineage3.q.out @@ -135,7 +135,7 @@ and x.ctinyint + length(c.cstring2) < 1000 PREHOOK: type: QUERY PREHOOK: Input: default@alltypesorc #### A masked pattern was here #### -{"version":"1.0","engine":"tez","database":"default","hash":"15e00f9e88c1ad6b2f53a33a0c147f0e","queryText":"select x.ctinyint, x.cint, c.cbigint-100, c.cstring1\nfrom alltypesorc c\njoin (\n select a.ctinyint ctinyint, b.cint cint\n from (select * from alltypesorc a where cboolean1=false) a\n join alltypesorc b on (a.cint = b.cbigint - 224870380)\n ) x on (x.cint = c.cint)\nwhere x.ctinyint > 10\nand x.cint < 4.5\nand x.ctinyint + length(c.cstring2) < 1000","edges":[{"sources":[4],"targets":[0],"edgeType":"PROJECTION"},{"sources":[5],"targets":[1],"edgeType":"PROJECTION"},{"sources":[6],"targets":[2],"expression":"(c.cbigint - 100L)","edgeType":"PROJECTION"},{"sources":[7],"targets":[3],"edgeType":"PROJECTION"},{"sources":[5],"targets":[0,1,2,3],"expression":"(CAST( c.cint AS decimal(11,1)) < 4.5)","edgeType":"PREDICATE"},{"sources":[5],"targets":[0,1,2,3],"expression":"(c.cint = b.cint)","edgeType":"PREDICATE"},{"sources":[5,6],"targets":[0,1,2,3],"expression":"((CAST( b.cint AS decimal(11,1)) < 4.5) and b.cbigint is not null)","edgeType":"PREDICATE"},{"sources":[6,5],"targets":[0,1,2,3],"expression":"((b.cbigint - 224870380) = UDFToLong(a.cint))","edgeType":"PREDICATE"},{"sources":[8,4,5],"targets":[0,1,2,3],"expression":"((a.cboolean1 = false) and (a.ctinyint > 10Y) and a.cint is not null)","edgeType":"PREDICATE"}],"vertices":[{"id":0,"vertexType":"COLUMN","vertexId":"x.ctinyint"},{"id":1,"vertexType":"COLUMN","vertexId":"x.cint"},{"id":2,"vertexType":"COLUMN","vertexId":"_c2"},{"id":3,"vertexType":"COLUMN","vertexId":"c.cstring1"},{"id":4,"vertexType":"COLUMN","vertexId":"default.alltypesorc.ctinyint"},{"id":5,"vertexType":"COLUMN","vertexId":"default.alltypesorc.cint"},{"id":6,"vertexType":"COLUMN","vertexId":"default.alltypesorc.cbigint"},{"id":7,"vertexType":"COLUMN","vertexId":"default.alltypesorc.cstring1"},{"id":8,"vertexType":"COLUMN","vertexId":"default.alltypesorc.cboolean1"}]} +{"version":"1.0","engine":"tez","database":"default","hash":"15e00f9e88c1ad6b2f53a33a0c147f0e","queryText":"select x.ctinyint, x.cint, c.cbigint-100, c.cstring1\nfrom alltypesorc c\njoin (\n select a.ctinyint ctinyint, b.cint cint\n from (select * from alltypesorc a where cboolean1=false) a\n join alltypesorc b on (a.cint = b.cbigint - 224870380)\n ) x on (x.cint = c.cint)\nwhere x.ctinyint > 10\nand x.cint < 4.5\nand x.ctinyint + length(c.cstring2) < 1000","edges":[{"sources":[4],"targets":[0],"edgeType":"PROJECTION"},{"sources":[5],"targets":[1],"edgeType":"PROJECTION"},{"sources":[6],"targets":[2],"expression":"(c.cbigint - 100L)","edgeType":"PROJECTION"},{"sources":[7],"targets":[3],"edgeType":"PROJECTION"},{"sources":[5],"targets":[0,1,2,3],"expression":"(CAST( c.cint AS decimal(11,1)) < 4.5)","edgeType":"PREDICATE"},{"sources":[5],"targets":[0,1,2,3],"expression":"(c.cint = b.cint)","edgeType":"PREDICATE"},{"sources":[5,6],"targets":[0,1,2,3],"expression":"((CAST( b.cint AS decimal(11,1)) < 4.5) and b.cbigint is not null)","edgeType":"PREDICATE"},{"sources":[6,5],"targets":[0,1,2,3],"expression":"((b.cbigint - 224870380L) = UDFToLong(a.cint))","edgeType":"PREDICATE"},{"sources":[8,4,5],"targets":[0,1,2,3],"expression":"((a.cboolean1 = false) and (a.ctinyint > 10Y) and a.cint is not null)","edgeType":"PREDICATE"}],"vertices":[{"id":0,"vertexType":"COLUMN","vertexId":"x.ctinyint"},{"id":1,"vertexType":"COLUMN","vertexId":"x.cint"},{"id":2,"vertexType":"COLUMN","vertexId":"_c2"},{"id":3,"vertexType":"COLUMN","vertexId":"c.cstring1"},{"id":4,"vertexType":"COLUMN","vertexId":"default.alltypesorc.ctinyint"},{"id":5,"vertexType":"COLUMN","vertexId":"default.alltypesorc.cint"},{"id":6,"vertexType":"COLUMN","vertexId":"default.alltypesorc.cbigint"},{"id":7,"vertexType":"COLUMN","vertexId":"default.alltypesorc.cstring1"},{"id":8,"vertexType":"COLUMN","vertexId":"default.alltypesorc.cboolean1"}]} 11 -654374827 857266369 OEfPnHnIYueoup PREHOOK: query: select c1, x2, x3 from ( @@ -186,7 +186,7 @@ where key not in (select key+18 from src1) order by key PREHOOK: type: QUERY PREHOOK: Input: default@src1 #### A masked pattern was here #### -{"version":"1.0","engine":"tez","database":"default","hash":"cbc4367150807328dda0f1cf4c74b811","queryText":"select key, value from src1\nwhere key not in (select key+18 from src1) order by key","edges":[{"sources":[2],"targets":[0],"edgeType":"PROJECTION"},{"sources":[3],"targets":[1],"edgeType":"PROJECTION"},{"sources":[2],"targets":[0,1],"expression":"(UDFToDouble(src1.key) = (UDFToDouble(src1.key) + 18.0D))","edgeType":"PREDICATE"},{"sources":[4,2],"targets":[0,1],"expression":"((count(*) = 0L) or (true is null and src1.key is not null and (count((UDFToDouble(src1.key) + 18.0D)) >= count(*))))","edgeType":"PREDICATE"}],"vertices":[{"id":0,"vertexType":"COLUMN","vertexId":"key"},{"id":1,"vertexType":"COLUMN","vertexId":"value"},{"id":2,"vertexType":"COLUMN","vertexId":"default.src1.key"},{"id":3,"vertexType":"COLUMN","vertexId":"default.src1.value"},{"id":4,"vertexType":"TABLE","vertexId":"default.src1"}]} +{"version":"1.0","engine":"tez","database":"default","hash":"cbc4367150807328dda0f1cf4c74b811","queryText":"select key, value from src1\nwhere key not in (select key+18 from src1) order by key","edges":[{"sources":[2],"targets":[0],"edgeType":"PROJECTION"},{"sources":[3],"targets":[1],"edgeType":"PROJECTION"},{"sources":[2],"targets":[0,1],"expression":"(UDFToDouble(src1.key) = (UDFToDouble(src1.key) + 18.0D))","edgeType":"PREDICATE"},{"sources":[4,2],"targets":[0,1],"expression":"((true is null or (count(*) = 0L)) and (src1.key is not null or (count(*) = 0L) or true is not null) and ((count((UDFToDouble(src1.key) + 18.0D)) >= count(*)) or (count(*) = 0L) or true is not null or src1.key is null))","edgeType":"PREDICATE"}],"vertices":[{"id":0,"vertexType":"COLUMN","vertexId":"key"},{"id":1,"vertexType":"COLUMN","vertexId":"value"},{"id":2,"vertexType":"COLUMN","vertexId":"default.src1.key"},{"id":3,"vertexType":"COLUMN","vertexId":"default.src1.value"},{"id":4,"vertexType":"TABLE","vertexId":"default.src1"}]} PREHOOK: query: select * from src1 a where not exists (select cint from alltypesorc b diff --git ql/src/test/results/clientpositive/llap/mapjoin_hint.q.out ql/src/test/results/clientpositive/llap/mapjoin_hint.q.out index 46e211d26a..673b7780a5 100644 --- ql/src/test/results/clientpositive/llap/mapjoin_hint.q.out +++ ql/src/test/results/clientpositive/llap/mapjoin_hint.q.out @@ -446,7 +446,7 @@ POSTHOOK: Lineage: part_null_n1.p_partkey SCRIPT [] POSTHOOK: Lineage: part_null_n1.p_retailprice SCRIPT [] POSTHOOK: Lineage: part_null_n1.p_size SCRIPT [] POSTHOOK: Lineage: part_null_n1.p_type SCRIPT [] -Warning: Shuffle Join MERGEJOIN[24][tables = [$hdt$_1, $hdt$_2, $hdt$_0]] in Stage 'Reducer 3' is a cross product +Warning: Shuffle Join MERGEJOIN[23][tables = [$hdt$_0, $hdt$_1, $hdt$_2]] in Stage 'Reducer 2' is a cross product PREHOOK: query: explain select /*+ mapjoin(None)*/ * from part where p_name = (select p_name from part_null_n1 where p_name is null) PREHOOK: type: QUERY PREHOOK: Input: default@part @@ -466,71 +466,53 @@ STAGE PLANS: Tez #### A masked pattern was here #### Edges: - Reducer 2 <- Map 1 (CUSTOM_SIMPLE_EDGE) - Reducer 3 <- Map 1 (XPROD_EDGE), Map 4 (XPROD_EDGE), Reducer 2 (XPROD_EDGE) + Reducer 2 <- Map 1 (XPROD_EDGE), Map 3 (XPROD_EDGE), Reducer 4 (XPROD_EDGE) + Reducer 4 <- Map 3 (CUSTOM_SIMPLE_EDGE) #### A masked pattern was here #### Vertices: Map 1 Map Operator Tree: TableScan - alias: part_null_n1 - filterExpr: p_name is null (type: boolean) - Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE + alias: part + Statistics: Num rows: 26 Data size: 16094 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: p_name is null (type: boolean) - Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE + predicate: false (type: boolean) + Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE - Group By Operator - aggregations: count() - mode: hash - outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - sort order: - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - value expressions: _col0 (type: bigint) + expressions: p_partkey (type: int), p_name (type: string), p_mfgr (type: string), p_brand (type: string), p_type (type: string), p_size (type: int), p_container (type: string), p_retailprice (type: double), p_comment (type: string) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 + Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator sort order: - Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE + value expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) Execution mode: vectorized, llap LLAP IO: no inputs - Map 4 + Map 3 Map Operator Tree: TableScan - alias: part - filterExpr: (p_name = null) (type: boolean) - Statistics: Num rows: 26 Data size: 16094 Basic stats: COMPLETE Column stats: COMPLETE - Filter Operator - predicate: (p_name = null) (type: boolean) - Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE - Select Operator - expressions: p_partkey (type: int), p_mfgr (type: string), p_brand (type: string), p_type (type: string), p_size (type: int), p_container (type: string), p_retailprice (type: double), p_comment (type: string) - outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7 - Statistics: Num rows: 1 Data size: 498 Basic stats: COMPLETE Column stats: COMPLETE + alias: part_null_n1 + Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: COMPLETE + Select Operator + Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: COMPLETE + Filter Operator + predicate: false (type: boolean) + Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: COMPLETE + Group By Operator + aggregations: count(0) + mode: hash + outputColumnNames: _col0 + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + sort order: + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + value expressions: _col0 (type: bigint) Reduce Output Operator sort order: - Statistics: Num rows: 1 Data size: 498 Basic stats: COMPLETE Column stats: COMPLETE - value expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: string), _col6 (type: double), _col7 (type: string) + Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: COMPLETE Execution mode: vectorized, llap LLAP IO: no inputs Reducer 2 - Execution mode: vectorized, llap - Reduce Operator Tree: - Group By Operator - aggregations: count(VALUE._col0) - mode: mergepartial - outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - Filter Operator - predicate: (sq_count_check(_col0) <= 1) (type: boolean) - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - Select Operator - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - sort order: - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - Reducer 3 Execution mode: llap Reduce Operator Tree: Merge Join Operator @@ -541,19 +523,28 @@ STAGE PLANS: 0 1 2 - outputColumnNames: _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9 - Statistics: Num rows: 1 Data size: 875 Basic stats: COMPLETE Column stats: NONE + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 + Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE + File Output Operator + compressed: false + Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE + table: + input format: org.apache.hadoop.mapred.SequenceFileInputFormat + output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat + serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + Reducer 4 + Execution mode: vectorized, llap + Reduce Operator Tree: + Group By Operator + aggregations: count(VALUE._col0) + mode: mergepartial + outputColumnNames: _col0 + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: _col2 (type: int), null (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 (type: int), _col7 (type: string), _col8 (type: double), _col9 (type: string) - outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 1 Data size: 875 Basic stats: COMPLETE Column stats: NONE - File Output Operator - compressed: false - Statistics: Num rows: 1 Data size: 875 Basic stats: COMPLETE Column stats: NONE - table: - input format: org.apache.hadoop.mapred.SequenceFileInputFormat - output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat - serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + sort order: + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE Stage: Stage-0 Fetch Operator @@ -561,7 +552,7 @@ STAGE PLANS: Processor Tree: ListSink -Warning: Map Join MAPJOIN[24][bigTable=?] in task 'Map 3' is a cross product +Warning: Map Join MAPJOIN[23][bigTable=?] in task 'Map 1' is a cross product PREHOOK: query: explain select * from part where p_name = (select p_name from part_null_n1 where p_name is null) PREHOOK: type: QUERY PREHOOK: Input: default@part @@ -581,48 +572,22 @@ STAGE PLANS: Tez #### A masked pattern was here #### Edges: - Map 3 <- Map 1 (BROADCAST_EDGE), Reducer 2 (BROADCAST_EDGE) - Reducer 2 <- Map 1 (CUSTOM_SIMPLE_EDGE) + Map 1 <- Map 2 (BROADCAST_EDGE), Reducer 3 (BROADCAST_EDGE) + Reducer 3 <- Map 2 (CUSTOM_SIMPLE_EDGE) #### A masked pattern was here #### Vertices: Map 1 Map Operator Tree: TableScan - alias: part_null_n1 - filterExpr: p_name is null (type: boolean) - Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE - Filter Operator - predicate: p_name is null (type: boolean) - Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE - Select Operator - Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE - Group By Operator - aggregations: count() - mode: hash - outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - sort order: - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - value expressions: _col0 (type: bigint) - Reduce Output Operator - sort order: - Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE - Execution mode: vectorized, llap - LLAP IO: no inputs - Map 3 - Map Operator Tree: - TableScan alias: part - filterExpr: (p_name = null) (type: boolean) Statistics: Num rows: 26 Data size: 16094 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: (p_name = null) (type: boolean) + predicate: false (type: boolean) Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: p_partkey (type: int), p_mfgr (type: string), p_brand (type: string), p_type (type: string), p_size (type: int), p_container (type: string), p_retailprice (type: double), p_comment (type: string) - outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7 - Statistics: Num rows: 1 Data size: 498 Basic stats: COMPLETE Column stats: COMPLETE + expressions: p_partkey (type: int), p_name (type: string), p_mfgr (type: string), p_brand (type: string), p_type (type: string), p_size (type: int), p_container (type: string), p_retailprice (type: double), p_comment (type: string) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 + Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE Map Join Operator condition map: Inner Join 0 to 1 @@ -631,40 +596,57 @@ STAGE PLANS: 0 1 2 - outputColumnNames: _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9 + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 input vertices: - 0 Reducer 2 - 1 Map 1 - Statistics: Num rows: 1 Data size: 875 Basic stats: COMPLETE Column stats: NONE - Select Operator - expressions: _col2 (type: int), null (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 (type: int), _col7 (type: string), _col8 (type: double), _col9 (type: string) - outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 1 Data size: 875 Basic stats: COMPLETE Column stats: NONE - File Output Operator - compressed: false - Statistics: Num rows: 1 Data size: 875 Basic stats: COMPLETE Column stats: NONE - table: - input format: org.apache.hadoop.mapred.SequenceFileInputFormat - output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat - serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + 1 Reducer 3 + 2 Map 2 + Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE + File Output Operator + compressed: false + Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE + table: + input format: org.apache.hadoop.mapred.SequenceFileInputFormat + output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat + serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe Execution mode: vectorized, llap LLAP IO: no inputs - Reducer 2 + Map 2 + Map Operator Tree: + TableScan + alias: part_null_n1 + Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: COMPLETE + Select Operator + Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: COMPLETE + Filter Operator + predicate: false (type: boolean) + Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: COMPLETE + Group By Operator + aggregations: count(0) + mode: hash + outputColumnNames: _col0 + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + sort order: + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + value expressions: _col0 (type: bigint) + Reduce Output Operator + sort order: + Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: COMPLETE + Execution mode: vectorized, llap + LLAP IO: no inputs + Reducer 3 Execution mode: vectorized, llap Reduce Operator Tree: Group By Operator aggregations: count(VALUE._col0) mode: mergepartial outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - Filter Operator - predicate: (sq_count_check(_col0) <= 1) (type: boolean) - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - Select Operator - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - sort order: - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + Select Operator + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + sort order: + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE Stage: Stage-0 Fetch Operator diff --git ql/src/test/results/clientpositive/llap/mergejoin.q.out ql/src/test/results/clientpositive/llap/mergejoin.q.out index 7c1bc565af..e6d4432242 100644 --- ql/src/test/results/clientpositive/llap/mergejoin.q.out +++ ql/src/test/results/clientpositive/llap/mergejoin.q.out @@ -4037,7 +4037,7 @@ POSTHOOK: Input: default@tab_part_n10@ds=2008-04-08 #### A masked pattern was here #### NULL NULL NULL 98 val_98 2008-04-08 NULL NULL NULL 98 val_98 2008-04-08 -Warning: Shuffle Join MERGEJOIN[18][tables = [$hdt$_0, $hdt$_1, $hdt$_2]] in Stage 'Reducer 2' is a cross product +Warning: Shuffle Join MERGEJOIN[23][tables = [$hdt$_0, $hdt$_1]] in Stage 'Reducer 2' is a cross product PREHOOK: query: select * from (select * from tab_n9 where tab_n9.key = 0)a full outer join @@ -4606,8 +4606,7 @@ NULL NULL NULL NULL NULL NULL 97 val_97 2008-04-08 NULL NULL NULL NULL NULL NULL 97 val_97 2008-04-08 NULL NULL NULL NULL NULL NULL 98 val_98 2008-04-08 NULL NULL NULL NULL NULL NULL 98 val_98 2008-04-08 -Warning: Shuffle Join MERGEJOIN[19][tables = [$hdt$_1, $hdt$_2]] in Stage 'Reducer 4' is a cross product -Warning: Shuffle Join MERGEJOIN[20][tables = [$hdt$_0, $hdt$_1]] in Stage 'Reducer 2' is a cross product +Warning: Shuffle Join MERGEJOIN[18][tables = [$hdt$_0, $hdt$_1]] in Stage 'Reducer 2' is a cross product PREHOOK: query: select * from (select * from tab_n9 where tab_n9.key = 0)a join diff --git ql/src/test/results/clientpositive/llap/ppd_union_view.q.out ql/src/test/results/clientpositive/llap/ppd_union_view.q.out index cba24342f8..c294e83a31 100644 --- ql/src/test/results/clientpositive/llap/ppd_union_view.q.out +++ ql/src/test/results/clientpositive/llap/ppd_union_view.q.out @@ -150,7 +150,7 @@ POSTHOOK: Input: default@t1_new_n0 POSTHOOK: Input: default@t1_old POSTHOOK: Input: default@t1_old@ds=2011-10-13 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `key`, `value`, CAST('2011-10-13' AS STRING) AS `ds` +OPTIMIZED SQL: SELECT `key`, `value`, CAST('2011-10-13' AS VARCHAR(65536)) AS `ds` FROM (SELECT `key`, `value` FROM `default`.`t1_new_n0` WHERE `ds` = '2011-10-13' @@ -492,7 +492,7 @@ POSTHOOK: Input: default@t1_new_n0 POSTHOOK: Input: default@t1_new_n0@ds=2011-10-15 POSTHOOK: Input: default@t1_old #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `key`, `value`, CAST('2011-10-15' AS STRING) AS `ds` +OPTIMIZED SQL: SELECT `key`, `value`, CAST('2011-10-15' AS VARCHAR(65536)) AS `ds` FROM (SELECT `key`, `value` FROM `default`.`t1_new_n0` WHERE `ds` = '2011-10-15' diff --git ql/src/test/results/clientpositive/llap/results_cache_2.q.out ql/src/test/results/clientpositive/llap/results_cache_2.q.out index a042a68e74..4365f46548 100644 --- ql/src/test/results/clientpositive/llap/results_cache_2.q.out +++ ql/src/test/results/clientpositive/llap/results_cache_2.q.out @@ -156,15 +156,15 @@ STAGE PLANS: Statistics: Num rows: 166 Data size: 14442 Basic stats: COMPLETE Column stats: COMPLETE Group By Operator aggregations: count() - keys: true (type: boolean) + keys: TIMESTAMP'2012-01-01 09:02:03' (type: timestamp) mode: hash outputColumnNames: _col0, _col1 - Statistics: Num rows: 1 Data size: 12 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 1 Data size: 48 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator - key expressions: _col0 (type: boolean) + key expressions: _col0 (type: timestamp) sort order: + - Map-reduce partition columns: _col0 (type: boolean) - Statistics: Num rows: 1 Data size: 12 Basic stats: COMPLETE Column stats: COMPLETE + Map-reduce partition columns: _col0 (type: timestamp) + Statistics: Num rows: 1 Data size: 48 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col1 (type: bigint) Execution mode: vectorized, llap LLAP IO: no inputs @@ -173,21 +173,24 @@ STAGE PLANS: Reduce Operator Tree: Group By Operator aggregations: count(VALUE._col0) - keys: KEY._col0 (type: boolean) + keys: KEY._col0 (type: timestamp) mode: mergepartial outputColumnNames: _col0, _col1 +<<<<<<< HEAD + Statistics: Num rows: 1 Data size: 48 Basic stats: COMPLETE Column stats: COMPLETE + File Output Operator + compressed: false +======= Statistics: Num rows: 1 Data size: 12 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: TIMESTAMP'2012-01-01 01:02:03' (type: timestamp), _col1 (type: bigint) outputColumnNames: _col0, _col1 +>>>>>>> asf/master Statistics: Num rows: 1 Data size: 48 Basic stats: COMPLETE Column stats: COMPLETE - File Output Operator - compressed: false - Statistics: Num rows: 1 Data size: 48 Basic stats: COMPLETE Column stats: COMPLETE - table: - input format: org.apache.hadoop.mapred.SequenceFileInputFormat - output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat - serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + table: + input format: org.apache.hadoop.mapred.SequenceFileInputFormat + output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat + serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe Stage: Stage-0 Fetch Operator diff --git ql/src/test/results/clientpositive/llap/semijoin6.q.out ql/src/test/results/clientpositive/llap/semijoin6.q.out index 139471970a..6f7262c4cc 100644 --- ql/src/test/results/clientpositive/llap/semijoin6.q.out +++ ql/src/test/results/clientpositive/llap/semijoin6.q.out @@ -759,7 +759,7 @@ STAGE PLANS: 0 _col0 (type: int) 1 _col0 (type: int) outputColumnNames: _col0, _col1, _col3 - residual filter predicates: {((_col0 + _col3) > 400)} {(CASE WHEN ((_col0 > 3)) THEN (true) WHEN ((_col3 > 1900)) THEN (true) ELSE (false) END or ((COALESCE(_col0) + COALESCE(_col3)) > 1900))} + residual filter predicates: {((_col0 + _col3) > 400)} {(((_col0 > 3) or (_col3 > 1900)) is true or ((COALESCE(_col0) + COALESCE(_col3)) > 1900))} Statistics: Num rows: 1 Data size: 12 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int), _col1 (type: int) diff --git ql/src/test/results/clientpositive/llap/subquery_in.q.out ql/src/test/results/clientpositive/llap/subquery_in.q.out index 07cc4dbabc..747b590dea 100644 --- ql/src/test/results/clientpositive/llap/subquery_in.q.out +++ ql/src/test/results/clientpositive/llap/subquery_in.q.out @@ -2128,9 +2128,7 @@ STAGE PLANS: Tez #### A masked pattern was here #### Edges: - Reducer 2 <- Map 1 (SIMPLE_EDGE), Reducer 4 (SIMPLE_EDGE) - Reducer 4 <- Map 3 (SIMPLE_EDGE), Reducer 6 (SIMPLE_EDGE) - Reducer 6 <- Map 5 (SIMPLE_EDGE) + Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 3 (SIMPLE_EDGE) #### A masked pattern was here #### Vertices: Map 1 @@ -2158,42 +2156,25 @@ STAGE PLANS: Map Operator Tree: TableScan alias: p - filterExpr: (p_size is not null and p_partkey is not null and p_name is not null) (type: boolean) + filterExpr: (((p_size + 121150) = p_partkey) and p_size is not null and p_name is not null) (type: boolean) Statistics: Num rows: 26 Data size: 3354 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: (p_name is not null and p_partkey is not null and p_size is not null) (type: boolean) - Statistics: Num rows: 26 Data size: 3354 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((p_size + 121150) = p_partkey) and p_name is not null and p_size is not null) (type: boolean) + Statistics: Num rows: 13 Data size: 1677 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: p_partkey (type: int), p_name (type: string), p_size (type: int) - outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 26 Data size: 3354 Basic stats: COMPLETE Column stats: COMPLETE - Reduce Output Operator - key expressions: _col2 (type: int), _col0 (type: int) - sort order: ++ - Map-reduce partition columns: _col2 (type: int), _col0 (type: int) - Statistics: Num rows: 26 Data size: 3354 Basic stats: COMPLETE Column stats: COMPLETE - value expressions: _col1 (type: string) - Execution mode: vectorized, llap - LLAP IO: no inputs - Map 5 - Map Operator Tree: - TableScan - alias: part - filterExpr: p_size is not null (type: boolean) - Statistics: Num rows: 26 Data size: 104 Basic stats: COMPLETE Column stats: COMPLETE - Filter Operator - predicate: p_size is not null (type: boolean) - Statistics: Num rows: 26 Data size: 104 Basic stats: COMPLETE Column stats: COMPLETE - Group By Operator - keys: p_size (type: int) - mode: hash - outputColumnNames: _col0 - Statistics: Num rows: 13 Data size: 52 Basic stats: COMPLETE Column stats: COMPLETE - Reduce Output Operator - key expressions: _col0 (type: int) - sort order: + - Map-reduce partition columns: _col0 (type: int) - Statistics: Num rows: 13 Data size: 52 Basic stats: COMPLETE Column stats: COMPLETE + expressions: p_name (type: string), p_size (type: int) + outputColumnNames: _col0, _col1 + Statistics: Num rows: 13 Data size: 1625 Basic stats: COMPLETE Column stats: COMPLETE + Group By Operator + keys: _col0 (type: string), _col1 (type: int) + mode: hash + outputColumnNames: _col0, _col1 + Statistics: Num rows: 6 Data size: 750 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: int) + sort order: ++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: int) + Statistics: Num rows: 6 Data size: 750 Basic stats: COMPLETE Column stats: COMPLETE Execution mode: vectorized, llap LLAP IO: no inputs Reducer 2 @@ -2214,48 +2195,6 @@ STAGE PLANS: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe - Reducer 4 - Execution mode: llap - Reduce Operator Tree: - Merge Join Operator - condition map: - Inner Join 0 to 1 - keys: - 0 _col2 (type: int), _col0 (type: int) - 1 _col0 (type: int), _col1 (type: int) - outputColumnNames: _col1, _col3 - Statistics: Num rows: 13 Data size: 1625 Basic stats: COMPLETE Column stats: COMPLETE - Select Operator - expressions: _col1 (type: string), _col3 (type: int) - outputColumnNames: _col0, _col1 - Statistics: Num rows: 13 Data size: 1625 Basic stats: COMPLETE Column stats: COMPLETE - Group By Operator - keys: _col0 (type: string), _col1 (type: int) - mode: hash - outputColumnNames: _col0, _col1 - Statistics: Num rows: 6 Data size: 750 Basic stats: COMPLETE Column stats: COMPLETE - Reduce Output Operator - key expressions: _col0 (type: string), _col1 (type: int) - sort order: ++ - Map-reduce partition columns: _col0 (type: string), _col1 (type: int) - Statistics: Num rows: 6 Data size: 750 Basic stats: COMPLETE Column stats: COMPLETE - Reducer 6 - Execution mode: vectorized, llap - Reduce Operator Tree: - Group By Operator - keys: KEY._col0 (type: int) - mode: mergepartial - outputColumnNames: _col0 - Statistics: Num rows: 13 Data size: 52 Basic stats: COMPLETE Column stats: COMPLETE - Select Operator - expressions: _col0 (type: int), (_col0 + 121150) (type: int) - outputColumnNames: _col0, _col1 - Statistics: Num rows: 13 Data size: 104 Basic stats: COMPLETE Column stats: COMPLETE - Reduce Output Operator - key expressions: _col0 (type: int), _col1 (type: int) - sort order: ++ - Map-reduce partition columns: _col0 (type: int), _col1 (type: int) - Statistics: Num rows: 13 Data size: 104 Basic stats: COMPLETE Column stats: COMPLETE Stage: Stage-0 Fetch Operator @@ -5023,7 +4962,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col14 Statistics: Num rows: 13 Data size: 8307 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col10 = 0L)) THEN (true) WHEN (_col10 is null) THEN (true) WHEN (_col14 is not null) THEN (false) WHEN (_col5 is null) THEN (null) WHEN ((_col11 < _col10)) THEN (false) ELSE (true) END (type: boolean) + predicate: (((_col11 < _col10) is not true or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null or _col5 is null) and (_col14 is null or ((_col10 = 0L) or _col10 is null) is true) and (_col5 is not null or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null)) (type: boolean) Statistics: Num rows: 6 Data size: 3834 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) @@ -5275,7 +5214,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col14 Statistics: Num rows: 13 Data size: 8307 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col10 = 0L)) THEN (true) WHEN (_col10 is null) THEN (true) WHEN (_col14 is not null) THEN (false) WHEN (_col5 is null) THEN (null) WHEN ((_col11 < _col10)) THEN (false) ELSE (true) END (type: boolean) + predicate: (((_col11 < _col10) is not true or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null or _col5 is null) and (_col14 is null or ((_col10 = 0L) or _col10 is null) is true) and (_col5 is not null or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null)) (type: boolean) Statistics: Num rows: 6 Data size: 3834 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) diff --git ql/src/test/results/clientpositive/llap/subquery_in_having.q.out ql/src/test/results/clientpositive/llap/subquery_in_having.q.out index 3839696882..bc5abf3237 100644 --- ql/src/test/results/clientpositive/llap/subquery_in_having.q.out +++ ql/src/test/results/clientpositive/llap/subquery_in_having.q.out @@ -1803,7 +1803,7 @@ STAGE PLANS: 1 Reducer 9 Statistics: Num rows: 1 Data size: 668 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN (_col2 is null) THEN (null) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END (type: boolean) + predicate: (((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col2 is null) and (_col2 is not null or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) (type: boolean) Statistics: Num rows: 1 Data size: 668 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: string), _col2 (type: bigint) diff --git ql/src/test/results/clientpositive/llap/subquery_multi.q.out ql/src/test/results/clientpositive/llap/subquery_multi.q.out index 7b00d69754..02c8fe5190 100644 --- ql/src/test/results/clientpositive/llap/subquery_multi.q.out +++ ql/src/test/results/clientpositive/llap/subquery_multi.q.out @@ -381,7 +381,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col13 Statistics: Num rows: 1 Data size: 1355 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col10 = 0L) or (_col13 is null and _col3 is not null and (_col11 >= _col10))) (type: boolean) + predicate: (((_col11 >= _col10) or (_col10 = 0L) or _col13 is not null or _col3 is null) and (_col13 is null or (_col10 = 0L)) and (_col3 is not null or (_col10 = 0L) or _col13 is not null)) (type: boolean) Statistics: Num rows: 1 Data size: 1355 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) @@ -600,7 +600,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col13 Statistics: Num rows: 1 Data size: 1355 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col10 = 0L) or (_col13 is null and _col3 is not null and (_col11 >= _col10))) (type: boolean) + predicate: (((_col11 >= _col10) or (_col10 = 0L) or _col13 is not null or _col3 is null) and (_col13 is null or (_col10 = 0L)) and (_col3 is not null or (_col10 = 0L) or _col13 is not null)) (type: boolean) Statistics: Num rows: 1 Data size: 1355 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) @@ -714,7 +714,7 @@ POSTHOOK: Input: default@part_null 85768 almond antique chartreuse lavender yellow Manufacturer#1 Brand#12 LARGE BRUSHED STEEL 34 SM BAG 1753.76 refull 86428 almond aquamarine burnished black steel Manufacturer#1 Brand#12 STANDARD ANODIZED STEEL 28 WRAP BAG 1414.42 arefully 90681 almond antique chartreuse khaki white Manufacturer#3 Brand#31 MEDIUM BURNISHED TIN 17 SM CASE 1671.68 are slyly after the sl -Warning: Shuffle Join MERGEJOIN[55][tables = [$hdt$_2, $hdt$_3]] in Stage 'Reducer 6' is a cross product +Warning: Shuffle Join MERGEJOIN[56][tables = [$hdt$_2, $hdt$_3]] in Stage 'Reducer 6' is a cross product PREHOOK: query: explain select * from part_null where p_brand IN (select p_brand from part_null) AND p_brand NOT IN (select p_name from part_null) PREHOOK: type: QUERY PREHOOK: Input: default@part_null @@ -764,21 +764,24 @@ STAGE PLANS: Map Operator Tree: TableScan alias: part_null - filterExpr: p_name is not null (type: boolean) Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE - Filter Operator - predicate: p_name is not null (type: boolean) + Select Operator + expressions: p_name (type: string) + outputColumnNames: _col0 Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE - Group By Operator - keys: p_name (type: string) - mode: hash - outputColumnNames: _col0 + Filter Operator + predicate: _col0 is not null (type: boolean) Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: string) - sort order: + - Map-reduce partition columns: _col0 (type: string) + Group By Operator + keys: _col0 (type: string) + mode: hash + outputColumnNames: _col0 Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: p_name (type: string) outputColumnNames: p_name @@ -833,15 +836,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col13 Statistics: Num rows: 2 Data size: 2464 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col10 = 0L) or (_col13 is null and (_col11 >= _col10))) (type: boolean) - Statistics: Num rows: 1 Data size: 1232 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col11 >= _col10) or (_col10 = 0L) or _col13 is not null or _col3 is null) and (_col13 is null or (_col10 = 0L))) (type: boolean) + Statistics: Num rows: 2 Data size: 2464 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 1 Data size: 1232 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 2464 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 1232 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 2464 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -912,7 +915,7 @@ STAGE PLANS: Processor Tree: ListSink -Warning: Shuffle Join MERGEJOIN[55][tables = [$hdt$_2, $hdt$_3]] in Stage 'Reducer 6' is a cross product +Warning: Shuffle Join MERGEJOIN[56][tables = [$hdt$_2, $hdt$_3]] in Stage 'Reducer 6' is a cross product PREHOOK: query: select * from part_null where p_brand IN (select p_brand from part_null) AND p_brand NOT IN (select p_name from part_null) PREHOOK: type: QUERY PREHOOK: Input: default@part_null @@ -1055,7 +1058,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 1 Data size: 1335 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col12 is null and _col1 is not null and (_col10 >= _col9)) or (_col9 = 0L)) (type: boolean) + predicate: (((_col10 >= _col9) or (_col9 = 0L) or _col12 is not null or _col1 is null) and (_col1 is not null or (_col9 = 0L) or _col12 is not null) and (_col12 is null or (_col9 = 0L))) (type: boolean) Statistics: Num rows: 1 Data size: 1335 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) @@ -1734,12 +1737,14 @@ STAGE PLANS: #### A masked pattern was here #### Edges: Reducer 10 <- Reducer 9 (SIMPLE_EDGE) + Reducer 12 <- Map 11 (SIMPLE_EDGE), Reducer 14 (ONE_TO_ONE_EDGE) + Reducer 14 <- Map 13 (SIMPLE_EDGE) Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 5 (SIMPLE_EDGE) Reducer 3 <- Reducer 2 (SIMPLE_EDGE), Reducer 8 (ONE_TO_ONE_EDGE) Reducer 4 <- Reducer 10 (ONE_TO_ONE_EDGE), Reducer 3 (SIMPLE_EDGE) - Reducer 7 <- Map 11 (SIMPLE_EDGE), Map 6 (SIMPLE_EDGE) + Reducer 7 <- Map 6 (SIMPLE_EDGE), Reducer 12 (SIMPLE_EDGE) Reducer 8 <- Reducer 7 (SIMPLE_EDGE) - Reducer 9 <- Map 11 (SIMPLE_EDGE), Map 6 (SIMPLE_EDGE) + Reducer 9 <- Map 6 (SIMPLE_EDGE), Reducer 12 (SIMPLE_EDGE) #### A masked pattern was here #### Vertices: Map 1 @@ -1773,24 +1778,36 @@ STAGE PLANS: predicate: (p_brand is not null and p_type is not null) (type: boolean) Statistics: Num rows: 26 Data size: 5096 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: p_type (type: string), p_brand (type: string) + expressions: p_brand (type: string), p_type (type: string) outputColumnNames: _col0, _col1 Statistics: Num rows: 26 Data size: 5096 Basic stats: COMPLETE Column stats: COMPLETE - Group By Operator - keys: _col0 (type: string), _col1 (type: string) - mode: hash - outputColumnNames: _col0, _col1 - Statistics: Num rows: 13 Data size: 2548 Basic stats: COMPLETE Column stats: COMPLETE - Reduce Output Operator - key expressions: _col0 (type: string), _col1 (type: string) - sort order: ++ - Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 13 Data size: 2548 Basic stats: COMPLETE Column stats: COMPLETE - Reduce Output Operator - key expressions: _col0 (type: string), _col1 (type: string) - sort order: ++ - Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 13 Data size: 2548 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + key expressions: _col1 (type: string) + sort order: + + Map-reduce partition columns: _col1 (type: string) + Statistics: Num rows: 26 Data size: 5096 Basic stats: COMPLETE Column stats: COMPLETE + value expressions: _col0 (type: string) + Execution mode: vectorized, llap + LLAP IO: no inputs + Map 13 + Map Operator Tree: + TableScan + alias: part + filterExpr: p_type is not null (type: boolean) + Statistics: Num rows: 26 Data size: 2704 Basic stats: COMPLETE Column stats: COMPLETE + Filter Operator + predicate: p_type is not null (type: boolean) + Statistics: Num rows: 26 Data size: 2704 Basic stats: COMPLETE Column stats: COMPLETE + Group By Operator + keys: p_type (type: string) + mode: hash + outputColumnNames: _col0 + Statistics: Num rows: 13 Data size: 1352 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 13 Data size: 1352 Basic stats: COMPLETE Column stats: COMPLETE Execution mode: vectorized, llap LLAP IO: no inputs Map 5 @@ -1859,17 +1876,60 @@ STAGE PLANS: keys: KEY._col0 (type: string), KEY._col1 (type: string) mode: mergepartial outputColumnNames: _col0, _col1 - Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 3 Data size: 588 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string), _col1 (type: string), true (type: boolean) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 7 Data size: 1400 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 3 Data size: 600 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: string), _col1 (type: string) sort order: ++ Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 7 Data size: 1400 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 3 Data size: 600 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col2 (type: boolean) + Reducer 12 + Execution mode: llap + Reduce Operator Tree: + Merge Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col1 (type: string) + 1 _col0 (type: string) + outputColumnNames: _col0, _col2 + Statistics: Num rows: 14 Data size: 2744 Basic stats: COMPLETE Column stats: COMPLETE + Select Operator + expressions: _col2 (type: string), _col0 (type: string) + outputColumnNames: _col0, _col1 + Statistics: Num rows: 14 Data size: 2744 Basic stats: COMPLETE Column stats: COMPLETE + Group By Operator + keys: _col0 (type: string), _col1 (type: string) + mode: hash + outputColumnNames: _col0, _col1 + Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: string) + sort order: ++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: string) + Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: string) + sort order: ++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: string) + Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE + Reducer 14 + Execution mode: vectorized, llap + Reduce Operator Tree: + Group By Operator + keys: KEY._col0 (type: string) + mode: mergepartial + outputColumnNames: _col0 + Statistics: Num rows: 13 Data size: 1352 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 13 Data size: 1352 Basic stats: COMPLETE Column stats: COMPLETE Reducer 2 Execution mode: llap Reduce Operator Tree: @@ -1916,15 +1976,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col14 Statistics: Num rows: 16 Data size: 3891 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col10 = 0L)) THEN (true) WHEN (_col10 is null) THEN (true) WHEN (_col14 is not null) THEN (false) WHEN (_col3 is null) THEN (null) WHEN ((_col11 < _col10)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 8 Data size: 1945 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col11 < _col10) is not true or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null or _col3 is null) and (_col14 is null or ((_col10 = 0L) or _col10 is null) is true) and (_col3 is not null or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null)) (type: boolean) + Statistics: Num rows: 16 Data size: 3891 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 8 Data size: 1945 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 16 Data size: 3891 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 8 Data size: 1945 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 16 Data size: 3891 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -1939,18 +1999,18 @@ STAGE PLANS: 0 _col1 (type: string), _col0 (type: string) 1 _col0 (type: string), _col1 (type: string) outputColumnNames: _col1, _col2 - Statistics: Num rows: 14 Data size: 2744 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE Group By Operator aggregations: count(), count(_col2) keys: _col1 (type: string) mode: hash outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 7 Data size: 840 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 2 Data size: 240 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 7 Data size: 840 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 2 Data size: 240 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col1 (type: bigint), _col2 (type: bigint) Reducer 8 Execution mode: vectorized, llap @@ -1960,12 +2020,12 @@ STAGE PLANS: keys: KEY._col0 (type: string) mode: mergepartial outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 7 Data size: 840 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 2 Data size: 240 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 7 Data size: 840 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 2 Data size: 240 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col1 (type: bigint), _col2 (type: bigint) Reducer 9 Execution mode: llap @@ -1977,17 +2037,17 @@ STAGE PLANS: 0 _col1 (type: string), _col0 (type: string) 1 _col0 (type: string), _col1 (type: string) outputColumnNames: _col1, _col2 - Statistics: Num rows: 14 Data size: 2744 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE Group By Operator keys: _col2 (type: string), _col1 (type: string) mode: hash outputColumnNames: _col0, _col1 - Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 3 Data size: 588 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: string), _col1 (type: string) sort order: ++ Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 3 Data size: 588 Basic stats: COMPLETE Column stats: COMPLETE Stage: Stage-0 Fetch Operator @@ -2237,12 +2297,14 @@ STAGE PLANS: #### A masked pattern was here #### Edges: Reducer 10 <- Reducer 9 (SIMPLE_EDGE) + Reducer 12 <- Map 11 (SIMPLE_EDGE), Reducer 14 (ONE_TO_ONE_EDGE) + Reducer 14 <- Map 13 (SIMPLE_EDGE) Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 5 (SIMPLE_EDGE) Reducer 3 <- Reducer 2 (SIMPLE_EDGE), Reducer 8 (ONE_TO_ONE_EDGE) Reducer 4 <- Reducer 10 (ONE_TO_ONE_EDGE), Reducer 3 (SIMPLE_EDGE) - Reducer 7 <- Map 11 (SIMPLE_EDGE), Map 6 (SIMPLE_EDGE) + Reducer 7 <- Map 6 (SIMPLE_EDGE), Reducer 12 (SIMPLE_EDGE) Reducer 8 <- Reducer 7 (SIMPLE_EDGE) - Reducer 9 <- Map 11 (SIMPLE_EDGE), Map 6 (SIMPLE_EDGE) + Reducer 9 <- Map 6 (SIMPLE_EDGE), Reducer 12 (SIMPLE_EDGE) #### A masked pattern was here #### Vertices: Map 1 @@ -2276,24 +2338,36 @@ STAGE PLANS: predicate: (p_brand is not null and p_type is not null) (type: boolean) Statistics: Num rows: 26 Data size: 5096 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: p_type (type: string), p_brand (type: string) + expressions: p_brand (type: string), p_type (type: string) outputColumnNames: _col0, _col1 Statistics: Num rows: 26 Data size: 5096 Basic stats: COMPLETE Column stats: COMPLETE - Group By Operator - keys: _col0 (type: string), _col1 (type: string) - mode: hash - outputColumnNames: _col0, _col1 - Statistics: Num rows: 13 Data size: 2548 Basic stats: COMPLETE Column stats: COMPLETE - Reduce Output Operator - key expressions: _col0 (type: string), _col1 (type: string) - sort order: ++ - Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 13 Data size: 2548 Basic stats: COMPLETE Column stats: COMPLETE - Reduce Output Operator - key expressions: _col0 (type: string), _col1 (type: string) - sort order: ++ - Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 13 Data size: 2548 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + key expressions: _col1 (type: string) + sort order: + + Map-reduce partition columns: _col1 (type: string) + Statistics: Num rows: 26 Data size: 5096 Basic stats: COMPLETE Column stats: COMPLETE + value expressions: _col0 (type: string) + Execution mode: vectorized, llap + LLAP IO: no inputs + Map 13 + Map Operator Tree: + TableScan + alias: part + filterExpr: p_type is not null (type: boolean) + Statistics: Num rows: 26 Data size: 2704 Basic stats: COMPLETE Column stats: COMPLETE + Filter Operator + predicate: p_type is not null (type: boolean) + Statistics: Num rows: 26 Data size: 2704 Basic stats: COMPLETE Column stats: COMPLETE + Group By Operator + keys: p_type (type: string) + mode: hash + outputColumnNames: _col0 + Statistics: Num rows: 13 Data size: 1352 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 13 Data size: 1352 Basic stats: COMPLETE Column stats: COMPLETE Execution mode: vectorized, llap LLAP IO: no inputs Map 5 @@ -2362,17 +2436,60 @@ STAGE PLANS: keys: KEY._col0 (type: string), KEY._col1 (type: string) mode: mergepartial outputColumnNames: _col0, _col1 - Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 3 Data size: 588 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string), _col1 (type: string), true (type: boolean) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 7 Data size: 1400 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 3 Data size: 600 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: string), _col1 (type: string) sort order: ++ Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 7 Data size: 1400 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 3 Data size: 600 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col2 (type: boolean) + Reducer 12 + Execution mode: llap + Reduce Operator Tree: + Merge Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col1 (type: string) + 1 _col0 (type: string) + outputColumnNames: _col0, _col2 + Statistics: Num rows: 14 Data size: 2744 Basic stats: COMPLETE Column stats: COMPLETE + Select Operator + expressions: _col2 (type: string), _col0 (type: string) + outputColumnNames: _col0, _col1 + Statistics: Num rows: 14 Data size: 2744 Basic stats: COMPLETE Column stats: COMPLETE + Group By Operator + keys: _col0 (type: string), _col1 (type: string) + mode: hash + outputColumnNames: _col0, _col1 + Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: string) + sort order: ++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: string) + Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: string) + sort order: ++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: string) + Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE + Reducer 14 + Execution mode: vectorized, llap + Reduce Operator Tree: + Group By Operator + keys: KEY._col0 (type: string) + mode: mergepartial + outputColumnNames: _col0 + Statistics: Num rows: 13 Data size: 1352 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 13 Data size: 1352 Basic stats: COMPLETE Column stats: COMPLETE Reducer 2 Execution mode: llap Reduce Operator Tree: @@ -2419,15 +2536,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col14 Statistics: Num rows: 16 Data size: 5484 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col10 = 0L)) THEN (true) WHEN (_col10 is null) THEN (true) WHEN (_col14 is not null) THEN (false) WHEN (_col3 is null) THEN (null) WHEN ((_col11 < _col10)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 8 Data size: 2742 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col11 < _col10) is not true or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null or _col3 is null) and (_col14 is null or ((_col10 = 0L) or _col10 is null) is true) and (_col3 is not null or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null)) (type: boolean) + Statistics: Num rows: 16 Data size: 5484 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 8 Data size: 2742 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 16 Data size: 5484 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 8 Data size: 2742 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 16 Data size: 5484 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -2442,18 +2559,18 @@ STAGE PLANS: 0 _col1 (type: string), _col0 (type: string) 1 _col0 (type: string), _col1 (type: string) outputColumnNames: _col1, _col2 - Statistics: Num rows: 14 Data size: 2744 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE Group By Operator aggregations: count(), count(_col2) keys: _col1 (type: string) mode: hash outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 7 Data size: 840 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 2 Data size: 240 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 7 Data size: 840 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 2 Data size: 240 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col1 (type: bigint), _col2 (type: bigint) Reducer 8 Execution mode: vectorized, llap @@ -2463,12 +2580,12 @@ STAGE PLANS: keys: KEY._col0 (type: string) mode: mergepartial outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 7 Data size: 840 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 2 Data size: 240 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 7 Data size: 840 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 2 Data size: 240 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col1 (type: bigint), _col2 (type: bigint) Reducer 9 Execution mode: llap @@ -2480,17 +2597,17 @@ STAGE PLANS: 0 _col1 (type: string), _col0 (type: string) 1 _col0 (type: string), _col1 (type: string) outputColumnNames: _col1, _col2 - Statistics: Num rows: 14 Data size: 2744 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE Group By Operator keys: _col2 (type: string), _col1 (type: string) mode: hash outputColumnNames: _col0, _col1 - Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 3 Data size: 588 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: string), _col1 (type: string) sort order: ++ Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 7 Data size: 1372 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 3 Data size: 588 Basic stats: COMPLETE Column stats: COMPLETE Stage: Stage-0 Fetch Operator @@ -2688,15 +2805,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col14 Statistics: Num rows: 16 Data size: 3891 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col10 = 0L)) THEN (true) WHEN (_col10 is null) THEN (true) WHEN (_col14 is not null) THEN (false) WHEN (_col3 is null) THEN (null) WHEN ((_col11 < _col10)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 8 Data size: 1945 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col11 < _col10) is not true or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null or _col3 is null) and (_col14 is null or ((_col10 = 0L) or _col10 is null) is true) and (_col3 is not null or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null)) (type: boolean) + Statistics: Num rows: 16 Data size: 3891 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 8 Data size: 1945 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 16 Data size: 3891 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 8 Data size: 1945 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 16 Data size: 3891 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -3145,7 +3262,7 @@ STAGE PLANS: outputColumnNames: _col0, _col2, _col4, _col5, _col7 Statistics: Num rows: 2 Data size: 64 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col4 = 0L) or (_col7 is null and _col2 is not null and (_col5 >= _col4))) (type: boolean) + predicate: (((_col5 >= _col4) or (_col4 = 0L) or _col7 is not null or _col2 is null) and (_col2 is not null or (_col4 = 0L) or _col7 is not null) and (_col7 is null or (_col4 = 0L))) (type: boolean) Statistics: Num rows: 2 Data size: 64 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int), 1 (type: int) @@ -4058,15 +4175,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 27 Data size: 17153 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col0 = 3) or CASE WHEN ((_col9 = 0L)) THEN (true) WHEN (_col12 is not null) THEN (false) WHEN (_col5 is null) THEN (null) WHEN ((_col10 < _col9)) THEN (null) ELSE (true) END) (type: boolean) - Statistics: Num rows: 14 Data size: 8898 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((_col9 <> 0L) and _col12 is null and (_col10 >= _col9) and _col5 is not null) or (_col0 = 3) or (_col9 = 0L)) (type: boolean) + Statistics: Num rows: 27 Data size: 17153 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 14 Data size: 8666 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 27 Data size: 16713 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 14 Data size: 8666 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 27 Data size: 16713 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -4278,7 +4395,7 @@ STAGE PLANS: outputColumnNames: _col1, _col2, _col4, _col5 Statistics: Num rows: 631 Data size: 65521 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col4 is not null and (_col2 <> 0L)) or _col1 is not null or _col5 is not null) (type: boolean) + predicate: (((_col2 <> 0L) and _col4 is not null) or _col1 is not null or _col5 is not null) (type: boolean) Statistics: Num rows: 631 Data size: 65521 Basic stats: COMPLETE Column stats: COMPLETE Select Operator Statistics: Num rows: 631 Data size: 65521 Basic stats: COMPLETE Column stats: COMPLETE diff --git ql/src/test/results/clientpositive/llap/subquery_notin.q.out ql/src/test/results/clientpositive/llap/subquery_notin.q.out index 29d8bbfb48..1f4b99b56f 100644 --- ql/src/test/results/clientpositive/llap/subquery_notin.q.out +++ ql/src/test/results/clientpositive/llap/subquery_notin.q.out @@ -115,7 +115,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col5 Statistics: Num rows: 631 Data size: 122942 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col2 = 0L) or (_col5 is null and _col0 is not null and (_col3 >= _col2))) (type: boolean) + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col0 is null) and (_col0 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) Statistics: Num rows: 631 Data size: 122942 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string), _col1 (type: string) @@ -404,15 +404,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col4, _col5, _col8 Statistics: Num rows: 38 Data size: 8914 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 19 Data size: 4457 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col0 is null) and (_col0 is not null or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) (type: boolean) + Statistics: Num rows: 38 Data size: 8914 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col1 (type: string), _col0 (type: string), _col2 (type: int) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 19 Data size: 4237 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 38 Data size: 8474 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 19 Data size: 4237 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 38 Data size: 8474 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -687,7 +687,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col5 Statistics: Num rows: 27 Data size: 3815 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col2 = 0L) or (_col5 is null and _col1 is not null and (_col3 >= _col2))) (type: boolean) + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col1 is null) and (_col1 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) Statistics: Num rows: 27 Data size: 3815 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string), _col1 (type: int) @@ -999,15 +999,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col4, _col5, _col8 Statistics: Num rows: 15 Data size: 3605 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN (_col2 is null) THEN (null) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 7 Data size: 1685 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col2 is null) and (_col2 is not null or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) (type: boolean) + Statistics: Num rows: 15 Data size: 3605 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col1 (type: string), _col0 (type: string), _col2 (type: int) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 7 Data size: 1561 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 15 Data size: 3345 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 7 Data size: 1561 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 15 Data size: 3345 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -1476,7 +1476,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: ((key < '11') or ((key < '11') and CASE WHEN ((key > '104')) THEN (null) ELSE ((key < '11')) END)) (type: boolean) + filterExpr: ((key < '11') or ((key < '11') and (((key > '104') is true and null) or (key is not null and (key > '104') is not true)))) (type: boolean) properties: insideView TRUE Statistics: Num rows: 500 Data size: 43500 Basic stats: COMPLETE Column stats: COMPLETE @@ -1493,22 +1493,22 @@ STAGE PLANS: Map-reduce partition columns: _col0 (type: string) Statistics: Num rows: 166 Data size: 14442 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((key < '11') and CASE WHEN ((key > '104')) THEN (null) ELSE ((key < '11')) END) (type: boolean) - Statistics: Num rows: 83 Data size: 7221 Basic stats: COMPLETE Column stats: COMPLETE + predicate: ((((key > '104') is true and null) or (key is not null and (key > '104') is not true)) and (key < '11')) (type: boolean) + Statistics: Num rows: 166 Data size: 14442 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: CASE WHEN ((key > '104')) THEN (null) ELSE (key) END (type: string) outputColumnNames: _col0 - Statistics: Num rows: 83 Data size: 7221 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 166 Data size: 14442 Basic stats: COMPLETE Column stats: COMPLETE Group By Operator keys: _col0 (type: string) mode: hash outputColumnNames: _col0 - Statistics: Num rows: 41 Data size: 7544 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 83 Data size: 15272 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 41 Data size: 7544 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 83 Data size: 15272 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator predicate: (key < '11') (type: boolean) Statistics: Num rows: 166 Data size: 14442 Basic stats: COMPLETE Column stats: COMPLETE @@ -1537,10 +1537,10 @@ STAGE PLANS: 0 _col0 (type: string) 1 _col0 (type: string) outputColumnNames: _col0, _col2 - Statistics: Num rows: 230 Data size: 20270 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 297 Data size: 26367 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator sort order: - Statistics: Num rows: 230 Data size: 20270 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 297 Data size: 26367 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col0 (type: string), _col2 (type: boolean) Reducer 3 Execution mode: llap @@ -1552,21 +1552,21 @@ STAGE PLANS: 0 1 outputColumnNames: _col0, _col2, _col3, _col4 - Statistics: Num rows: 230 Data size: 23950 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 297 Data size: 31119 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string), _col3 (type: bigint), _col4 (type: bigint), _col2 (type: boolean) outputColumnNames: _col0, _col1, _col2, _col4 - Statistics: Num rows: 230 Data size: 23950 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 297 Data size: 31119 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col1 = 0L) or (_col4 is null and _col0 is not null and (_col2 >= _col1))) (type: boolean) - Statistics: Num rows: 230 Data size: 23950 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((_col2 >= _col1) or (_col1 = 0L) or _col4 is not null or _col0 is null) and (_col0 is not null or (_col1 = 0L) or _col4 is not null) and (_col4 is null or (_col1 = 0L))) (type: boolean) + Statistics: Num rows: 297 Data size: 31119 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string) outputColumnNames: _col0 - Statistics: Num rows: 230 Data size: 20010 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 297 Data size: 25839 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 230 Data size: 20010 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 297 Data size: 25839 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -1578,16 +1578,16 @@ STAGE PLANS: keys: KEY._col0 (type: string) mode: mergepartial outputColumnNames: _col0 - Statistics: Num rows: 41 Data size: 7544 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 83 Data size: 15272 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string), true (type: boolean) outputColumnNames: _col0, _col1 - Statistics: Num rows: 41 Data size: 7708 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 83 Data size: 15604 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 41 Data size: 7708 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 83 Data size: 15604 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col1 (type: boolean) Reducer 5 Execution mode: vectorized, llap @@ -1740,15 +1740,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col14 Statistics: Num rows: 64 Data size: 40340 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col10 = 0L)) THEN (true) WHEN (_col10 is null) THEN (true) WHEN (_col14 is not null) THEN (false) WHEN (_col5 is null) THEN (null) WHEN ((_col11 < _col10)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 32 Data size: 20180 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((_col11 < _col10) is not true or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null or _col5 is null) and (_col14 is null or ((_col10 = 0L) or _col10 is null) is true) and (_col5 is not null or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null)) (type: boolean) + Statistics: Num rows: 64 Data size: 40340 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 32 Data size: 19808 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 64 Data size: 39616 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 32 Data size: 19808 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 64 Data size: 39616 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -1921,7 +1921,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 33 Data size: 20987 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col12 is null and _col5 is not null and (_col10 >= _col9)) or (_col9 = 0L)) (type: boolean) + predicate: (((_col10 >= _col9) or (_col9 = 0L) or _col12 is not null or _col5 is null) and (_col12 is null or (_col9 = 0L)) and (_col5 is not null or (_col9 = 0L) or _col12 is not null)) (type: boolean) Statistics: Num rows: 33 Data size: 20987 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) @@ -2136,7 +2136,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 32 Data size: 20348 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col12 is null and _col0 is not null and _col5 is not null and (_col10 >= _col9)) or (_col9 = 0L)) (type: boolean) + predicate: (((_col0 is not null and _col5 is not null) or (_col9 = 0L) or _col12 is not null) and ((_col10 >= _col9) or (_col9 = 0L) or _col12 is not null or _col0 is null or _col5 is null) and (_col12 is null or (_col9 = 0L))) (type: boolean) Statistics: Num rows: 32 Data size: 20348 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) @@ -2395,10 +2395,10 @@ STAGE PLANS: outputColumnNames: _col1, _col3, _col4, _col7 Statistics: Num rows: 48 Data size: 660 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN ((_col1 + 100) is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 24 Data size: 340 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col1 is null) and (_col1 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 48 Data size: 660 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - Statistics: Num rows: 24 Data size: 340 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 48 Data size: 660 Basic stats: COMPLETE Column stats: COMPLETE Group By Operator aggregations: count() mode: hash @@ -2585,7 +2585,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 32 Data size: 20348 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col12 is null and _col7 is not null and (_col10 >= _col9)) or (_col9 = 0L)) (type: boolean) + predicate: (((_col10 >= _col9) or (_col9 = 0L) or _col12 is not null or _col7 is null) and (_col12 is null or (_col9 = 0L)) and (_col7 is not null or (_col9 = 0L) or _col12 is not null)) (type: boolean) Statistics: Num rows: 32 Data size: 20348 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) @@ -2694,13 +2694,10 @@ STAGE PLANS: Tez #### A masked pattern was here #### Edges: - Reducer 10 <- Map 9 (SIMPLE_EDGE) - Reducer 2 <- Map 1 (SIMPLE_EDGE), Reducer 6 (ONE_TO_ONE_EDGE) - Reducer 3 <- Reducer 2 (SIMPLE_EDGE), Reducer 8 (ONE_TO_ONE_EDGE) - Reducer 5 <- Map 4 (SIMPLE_EDGE), Reducer 10 (SIMPLE_EDGE) - Reducer 6 <- Reducer 5 (SIMPLE_EDGE) - Reducer 7 <- Map 4 (SIMPLE_EDGE), Reducer 10 (SIMPLE_EDGE) - Reducer 8 <- Reducer 7 (SIMPLE_EDGE) + Reducer 2 <- Map 1 (SIMPLE_EDGE), Reducer 5 (ONE_TO_ONE_EDGE) + Reducer 3 <- Reducer 2 (SIMPLE_EDGE), Reducer 6 (ONE_TO_ONE_EDGE) + Reducer 5 <- Map 4 (SIMPLE_EDGE) + Reducer 6 <- Map 4 (SIMPLE_EDGE) #### A masked pattern was here #### Vertices: Map 1 @@ -2724,79 +2721,46 @@ STAGE PLANS: Map Operator Tree: TableScan alias: p - filterExpr: ((p_size is not null and p_partkey is not null) or (p_size is not null and p_partkey is not null and p_name is not null)) (type: boolean) + filterExpr: ((((p_size + 121150) = p_partkey) and p_size is not null) or (((p_size + 121150) = p_partkey) and p_size is not null and p_name is not null)) (type: boolean) Statistics: Num rows: 26 Data size: 3354 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: (p_partkey is not null and p_size is not null) (type: boolean) - Statistics: Num rows: 26 Data size: 3354 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((p_size + 121150) = p_partkey) and p_size is not null) (type: boolean) + Statistics: Num rows: 13 Data size: 1677 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: p_partkey (type: int), p_name (type: string), p_size (type: int) - outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 26 Data size: 3354 Basic stats: COMPLETE Column stats: COMPLETE - Reduce Output Operator - key expressions: _col2 (type: int), _col0 (type: int) - sort order: ++ - Map-reduce partition columns: _col2 (type: int), _col0 (type: int) - Statistics: Num rows: 26 Data size: 3354 Basic stats: COMPLETE Column stats: COMPLETE - value expressions: _col1 (type: string) + expressions: p_name (type: string), p_size (type: int) + outputColumnNames: p_name, p_size + Statistics: Num rows: 13 Data size: 1677 Basic stats: COMPLETE Column stats: COMPLETE + Group By Operator + aggregations: count(), count(p_name) + keys: p_size (type: int) + mode: hash + outputColumnNames: _col0, _col1, _col2 + Statistics: Num rows: 6 Data size: 120 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + key expressions: _col0 (type: int) + sort order: + + Map-reduce partition columns: _col0 (type: int) + Statistics: Num rows: 6 Data size: 120 Basic stats: COMPLETE Column stats: COMPLETE + value expressions: _col1 (type: bigint), _col2 (type: bigint) Filter Operator - predicate: (p_name is not null and p_partkey is not null and p_size is not null) (type: boolean) - Statistics: Num rows: 26 Data size: 3354 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((p_size + 121150) = p_partkey) and p_name is not null and p_size is not null) (type: boolean) + Statistics: Num rows: 13 Data size: 1677 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: p_partkey (type: int), p_name (type: string), p_size (type: int) - outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 26 Data size: 3354 Basic stats: COMPLETE Column stats: COMPLETE - Reduce Output Operator - key expressions: _col2 (type: int), _col0 (type: int) - sort order: ++ - Map-reduce partition columns: _col2 (type: int), _col0 (type: int) - Statistics: Num rows: 26 Data size: 3354 Basic stats: COMPLETE Column stats: COMPLETE - value expressions: _col1 (type: string) - Execution mode: vectorized, llap - LLAP IO: no inputs - Map 9 - Map Operator Tree: - TableScan - alias: part - filterExpr: p_size is not null (type: boolean) - Statistics: Num rows: 26 Data size: 104 Basic stats: COMPLETE Column stats: COMPLETE - Filter Operator - predicate: p_size is not null (type: boolean) - Statistics: Num rows: 26 Data size: 104 Basic stats: COMPLETE Column stats: COMPLETE - Group By Operator - keys: p_size (type: int) - mode: hash - outputColumnNames: _col0 - Statistics: Num rows: 13 Data size: 52 Basic stats: COMPLETE Column stats: COMPLETE - Reduce Output Operator - key expressions: _col0 (type: int) - sort order: + - Map-reduce partition columns: _col0 (type: int) - Statistics: Num rows: 13 Data size: 52 Basic stats: COMPLETE Column stats: COMPLETE + expressions: p_name (type: string), p_size (type: int) + outputColumnNames: p_name, p_size + Statistics: Num rows: 13 Data size: 1677 Basic stats: COMPLETE Column stats: COMPLETE + Group By Operator + keys: p_name (type: string), p_size (type: int) + mode: hash + outputColumnNames: _col0, _col1 + Statistics: Num rows: 6 Data size: 750 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: int) + sort order: ++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: int) + Statistics: Num rows: 6 Data size: 750 Basic stats: COMPLETE Column stats: COMPLETE Execution mode: vectorized, llap LLAP IO: no inputs - Reducer 10 - Execution mode: vectorized, llap - Reduce Operator Tree: - Group By Operator - keys: KEY._col0 (type: int) - mode: mergepartial - outputColumnNames: _col0 - Statistics: Num rows: 13 Data size: 52 Basic stats: COMPLETE Column stats: COMPLETE - Select Operator - expressions: _col0 (type: int), (_col0 + 121150) (type: int) - outputColumnNames: _col0, _col1 - Statistics: Num rows: 13 Data size: 104 Basic stats: COMPLETE Column stats: COMPLETE - Reduce Output Operator - key expressions: _col0 (type: int), _col1 (type: int) - sort order: ++ - Map-reduce partition columns: _col0 (type: int), _col1 (type: int) - Statistics: Num rows: 13 Data size: 104 Basic stats: COMPLETE Column stats: COMPLETE - Reduce Output Operator - key expressions: _col0 (type: int), _col1 (type: int) - sort order: ++ - Map-reduce partition columns: _col0 (type: int), _col1 (type: int) - Statistics: Num rows: 13 Data size: 104 Basic stats: COMPLETE Column stats: COMPLETE Reducer 2 Execution mode: llap Reduce Operator Tree: @@ -2826,43 +2790,20 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col14 Statistics: Num rows: 40 Data size: 25032 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col10 = 0L)) THEN (true) WHEN (_col10 is null) THEN (true) WHEN (_col14 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col11 < _col10)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 20 Data size: 12524 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((_col11 < _col10) is not true or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null or _col1 is null) and (_col1 is not null or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null) and (_col14 is null or ((_col10 = 0L) or _col10 is null) is true)) (type: boolean) + Statistics: Num rows: 40 Data size: 25032 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 20 Data size: 12380 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 40 Data size: 24760 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 20 Data size: 12380 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 40 Data size: 24760 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe Reducer 5 - Execution mode: llap - Reduce Operator Tree: - Merge Join Operator - condition map: - Inner Join 0 to 1 - keys: - 0 _col2 (type: int), _col0 (type: int) - 1 _col0 (type: int), _col1 (type: int) - outputColumnNames: _col1, _col3 - Statistics: Num rows: 13 Data size: 1625 Basic stats: COMPLETE Column stats: COMPLETE - Group By Operator - aggregations: count(), count(_col1) - keys: _col3 (type: int) - mode: hash - outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 6 Data size: 120 Basic stats: COMPLETE Column stats: COMPLETE - Reduce Output Operator - key expressions: _col0 (type: int) - sort order: + - Map-reduce partition columns: _col0 (type: int) - Statistics: Num rows: 6 Data size: 120 Basic stats: COMPLETE Column stats: COMPLETE - value expressions: _col1 (type: bigint), _col2 (type: bigint) - Reducer 6 Execution mode: vectorized, llap Reduce Operator Tree: Group By Operator @@ -2877,28 +2818,7 @@ STAGE PLANS: Map-reduce partition columns: _col0 (type: int) Statistics: Num rows: 6 Data size: 120 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col1 (type: bigint), _col2 (type: bigint) - Reducer 7 - Execution mode: llap - Reduce Operator Tree: - Merge Join Operator - condition map: - Inner Join 0 to 1 - keys: - 0 _col2 (type: int), _col0 (type: int) - 1 _col0 (type: int), _col1 (type: int) - outputColumnNames: _col1, _col3 - Statistics: Num rows: 13 Data size: 1625 Basic stats: COMPLETE Column stats: COMPLETE - Group By Operator - keys: _col1 (type: string), _col3 (type: int) - mode: hash - outputColumnNames: _col0, _col1 - Statistics: Num rows: 6 Data size: 750 Basic stats: COMPLETE Column stats: COMPLETE - Reduce Output Operator - key expressions: _col0 (type: string), _col1 (type: int) - sort order: ++ - Map-reduce partition columns: _col0 (type: string), _col1 (type: int) - Statistics: Num rows: 6 Data size: 750 Basic stats: COMPLETE Column stats: COMPLETE - Reducer 8 + Reducer 6 Execution mode: vectorized, llap Reduce Operator Tree: Group By Operator @@ -3060,15 +2980,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col11, _col12, _col16 Statistics: Num rows: 59 Data size: 37149 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col11 = 0L)) THEN (true) WHEN (_col11 is null) THEN (true) WHEN (_col16 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col12 < _col11)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 29 Data size: 18267 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((_col12 < _col11) is not true or ((_col11 = 0L) or _col11 is null) is true or _col16 is not null or _col1 is null) and (_col1 is not null or ((_col11 = 0L) or _col11 is null) is true or _col16 is not null) and (_col16 is null or ((_col11 = 0L) or _col11 is null) is true)) (type: boolean) + Statistics: Num rows: 59 Data size: 37149 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 29 Data size: 17951 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 59 Data size: 36521 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 29 Data size: 17951 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 59 Data size: 36521 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -3234,15 +3154,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col4, _col5, _col8 Statistics: Num rows: 58 Data size: 13682 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 29 Data size: 6849 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col1 is null) and (_col1 is not null or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) (type: boolean) + Statistics: Num rows: 58 Data size: 13682 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string) outputColumnNames: _col0 - Statistics: Num rows: 29 Data size: 3509 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 58 Data size: 7018 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 29 Data size: 3509 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 58 Data size: 7018 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -3470,15 +3390,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col4, _col5, _col8 Statistics: Num rows: 46 Data size: 10734 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 23 Data size: 5375 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col1 is null) and (_col1 is not null or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) (type: boolean) + Statistics: Num rows: 46 Data size: 10734 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string) outputColumnNames: _col0 - Statistics: Num rows: 23 Data size: 2783 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 46 Data size: 5566 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 23 Data size: 2783 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 46 Data size: 5566 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -3723,7 +3643,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col5 Statistics: Num rows: 907 Data size: 177590 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col2 = 0L) or (_col5 is null and _col1 is not null and (_col3 >= _col2))) (type: boolean) + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col1 is null) and (_col1 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) Statistics: Num rows: 907 Data size: 177590 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string) @@ -4017,12 +3937,12 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col3, _col4, _col7 Statistics: Num rows: 1623 Data size: 309794 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 811 Data size: 154810 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col1 is null) and (_col1 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 1623 Data size: 309794 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string) outputColumnNames: _col0 - Statistics: Num rows: 811 Data size: 154810 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 1623 Data size: 309794 Basic stats: COMPLETE Column stats: COMPLETE Group By Operator aggregations: count() keys: _col0 (type: string) @@ -4277,7 +4197,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 33 Data size: 20987 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col12 is null and _col5 is not null and (_col10 >= _col9)) or (_col9 = 0L)) (type: boolean) + predicate: (((_col10 >= _col9) or (_col9 = 0L) or _col12 is not null or _col5 is null) and (_col12 is null or (_col9 = 0L)) and (_col5 is not null or (_col9 = 0L) or _col12 is not null)) (type: boolean) Statistics: Num rows: 33 Data size: 20987 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) @@ -4493,7 +4413,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 33 Data size: 20987 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col12 is null and _col5 is not null and (_col10 >= _col9)) or (_col9 = 0L)) (type: boolean) + predicate: (((_col10 >= _col9) or (_col9 = 0L) or _col12 is not null or _col5 is null) and (_col12 is null or (_col9 = 0L)) and (_col5 is not null or (_col9 = 0L) or _col12 is not null)) (type: boolean) Statistics: Num rows: 33 Data size: 20987 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) @@ -4776,7 +4696,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col5 Statistics: Num rows: 539 Data size: 104726 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col2 = 0L) or (_col5 is null and _col0 is not null and (_col3 >= _col2))) (type: boolean) + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col0 is null) and (_col0 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) Statistics: Num rows: 539 Data size: 104726 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string), _col1 (type: string) @@ -5472,10 +5392,10 @@ STAGE PLANS: outputColumnNames: _col1, _col3, _col4, _col7 Statistics: Num rows: 53 Data size: 780 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN ((_col1 + 100) is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 26 Data size: 388 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col1 is null) and (_col1 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 50 Data size: 728 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - Statistics: Num rows: 26 Data size: 388 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 50 Data size: 728 Basic stats: COMPLETE Column stats: COMPLETE Group By Operator aggregations: count() mode: hash @@ -5704,7 +5624,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col4 Statistics: Num rows: 5 Data size: 108 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col1 = 0L) or (_col4 is null and _col0 is not null and (_col2 >= _col1))) (type: boolean) + predicate: (((_col2 >= _col1) or (_col1 = 0L) or _col4 is not null or _col0 is null) and (_col0 is not null or (_col1 = 0L) or _col4 is not null) and (_col4 is null or (_col1 = 0L))) (type: boolean) Statistics: Num rows: 5 Data size: 108 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int) @@ -5880,15 +5800,15 @@ STAGE PLANS: outputColumnNames: _col0, _col3, _col4, _col7 Statistics: Num rows: 6 Data size: 80 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 3 Data size: 48 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col0 is null) and (_col0 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 6 Data size: 80 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int) outputColumnNames: _col0 - Statistics: Num rows: 3 Data size: 12 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 6 Data size: 24 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 3 Data size: 12 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 6 Data size: 24 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -6157,7 +6077,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col3, _col4, _col7 Statistics: Num rows: 3 Data size: 84 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col1 is null) and (_col1 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) Statistics: Num rows: 1 Data size: 28 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int) @@ -6386,7 +6306,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col3, _col4, _col6 Statistics: Num rows: 1 Data size: 28 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col6 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col6 is not null or _col1 is null) and (_col1 is not null or ((_col3 = 0L) or _col3 is null) is true or _col6 is not null) and (_col6 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) Statistics: Num rows: 1 Data size: 28 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int), _col1 (type: int) @@ -6618,7 +6538,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col3, _col4, _col6 Statistics: Num rows: 1 Data size: 28 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col6 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col6 is not null or _col1 is null) and (_col1 is not null or ((_col3 = 0L) or _col3 is null) is true or _col6 is not null) and (_col6 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) Statistics: Num rows: 1 Data size: 28 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int) @@ -6809,15 +6729,15 @@ STAGE PLANS: outputColumnNames: _col0, _col3, _col4, _col7 Statistics: Num rows: 4 Data size: 88 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 2 Data size: 44 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col0 is null) and (_col0 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 4 Data size: 88 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int) outputColumnNames: _col0 - Statistics: Num rows: 2 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 4 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 2 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 4 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -6973,7 +6893,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col5 Statistics: Num rows: 3 Data size: 84 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col2 = 0L) or (_col5 is null and _col1 is not null and (_col3 >= _col2))) (type: boolean) + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col1 is null) and (_col1 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) Statistics: Num rows: 3 Data size: 84 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int) @@ -7146,7 +7066,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col4 Statistics: Num rows: 4 Data size: 88 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: ((_col1 = 0L) or (_col4 is null and _col0 is not null and (_col2 >= _col1))) (type: boolean) + predicate: (((_col2 >= _col1) or (_col1 = 0L) or _col4 is not null or _col0 is null) and (_col0 is not null or (_col1 = 0L) or _col4 is not null) and (_col4 is null or (_col1 = 0L))) (type: boolean) Statistics: Num rows: 4 Data size: 88 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int) @@ -7317,15 +7237,15 @@ STAGE PLANS: residual filter predicates: {(_col1 > _col6)} Statistics: Num rows: 1145 Data size: 236851 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 572 Data size: 118384 Basic stats: COMPLETE Column stats: COMPLETE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col0 is null) and (_col0 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 1145 Data size: 236851 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string), _col1 (type: string) outputColumnNames: _col0, _col1 - Statistics: Num rows: 572 Data size: 101816 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 1145 Data size: 203810 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 572 Data size: 101816 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 1145 Data size: 203810 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat diff --git ql/src/test/results/clientpositive/llap/subquery_null_agg.q.out ql/src/test/results/clientpositive/llap/subquery_null_agg.q.out index 4591ff8460..f00934515e 100644 --- ql/src/test/results/clientpositive/llap/subquery_null_agg.q.out +++ ql/src/test/results/clientpositive/llap/subquery_null_agg.q.out @@ -6,8 +6,8 @@ POSTHOOK: query: CREATE TABLE table_7 (int_col INT) POSTHOOK: type: CREATETABLE POSTHOOK: Output: database:default POSTHOOK: Output: default@table_7 -Warning: Shuffle Join MERGEJOIN[29][tables = [$hdt$_0, $hdt$_1]] in Stage 'Reducer 2' is a cross product -Warning: Shuffle Join MERGEJOIN[30][tables = [$hdt$_0, $hdt$_1, $hdt$_2]] in Stage 'Reducer 3' is a cross product +Warning: Shuffle Join MERGEJOIN[24][tables = [$hdt$_0, $hdt$_1]] in Stage 'Reducer 2' is a cross product +Warning: Shuffle Join MERGEJOIN[25][tables = [$hdt$_0, $hdt$_1, $hdt$_2]] in Stage 'Reducer 3' is a cross product PREHOOK: query: explain SELECT (t1.int_col) * (t1.int_col) AS int_col @@ -59,10 +59,9 @@ STAGE PLANS: Tez #### A masked pattern was here #### Edges: - Reducer 2 <- Map 1 (CUSTOM_SIMPLE_EDGE), Reducer 4 (CUSTOM_SIMPLE_EDGE) - Reducer 3 <- Reducer 2 (XPROD_EDGE), Reducer 5 (XPROD_EDGE) - Reducer 4 <- Map 1 (SIMPLE_EDGE) - Reducer 5 <- Map 1 (CUSTOM_SIMPLE_EDGE) + Reducer 2 <- Map 1 (CUSTOM_SIMPLE_EDGE), Map 5 (CUSTOM_SIMPLE_EDGE) + Reducer 3 <- Reducer 2 (XPROD_EDGE), Reducer 4 (XPROD_EDGE) + Reducer 4 <- Map 1 (CUSTOM_SIMPLE_EDGE) #### A masked pattern was here #### Vertices: Map 1 @@ -79,27 +78,34 @@ STAGE PLANS: predicate: false (type: boolean) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE Group By Operator - keys: true (type: boolean) + aggregations: count() mode: hash outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE + Statistics: Num rows: 1 Data size: 8 Basic stats: PARTIAL Column stats: COMPLETE Reduce Output Operator - key expressions: _col0 (type: boolean) - sort order: + - Map-reduce partition columns: _col0 (type: boolean) - Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE + sort order: + Statistics: Num rows: 1 Data size: 8 Basic stats: PARTIAL Column stats: COMPLETE + value expressions: _col0 (type: bigint) + Execution mode: vectorized, llap + LLAP IO: no inputs + Map 5 + Map Operator Tree: + TableScan + alias: table_7 + Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE + Select Operator + Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE Filter Operator predicate: false (type: boolean) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE - Group By Operator - aggregations: count() - mode: hash + Select Operator + expressions: true (type: boolean) outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 8 Basic stats: PARTIAL Column stats: COMPLETE + Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE Reduce Output Operator sort order: - Statistics: Num rows: 1 Data size: 8 Basic stats: PARTIAL Column stats: COMPLETE - value expressions: _col0 (type: bigint) + Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE + value expressions: _col0 (type: boolean) Execution mode: vectorized, llap LLAP IO: no inputs Reducer 2 @@ -126,14 +132,14 @@ STAGE PLANS: keys: 0 1 - outputColumnNames: _col1, _col2 + outputColumnNames: _col1, _col2, _col3 Statistics: Num rows: 1 Data size: 10 Basic stats: PARTIAL Column stats: NONE Select Operator - expressions: _col2 (type: bigint), _col1 (type: boolean) - outputColumnNames: _col1, _col2 + expressions: _col2 (type: bigint), _col3 (type: bigint), _col1 (type: boolean) + outputColumnNames: _col1, _col2, _col3 Statistics: Num rows: 1 Data size: 10 Basic stats: PARTIAL Column stats: NONE Filter Operator - predicate: ((_col1 = 0L) or _col2 is null) (type: boolean) + predicate: ((_col1 = 0L) or (_col3 is null and (_col2 >= _col1))) (type: boolean) Statistics: Num rows: 1 Data size: 10 Basic stats: PARTIAL Column stats: NONE Select Operator expressions: null (type: void) @@ -150,30 +156,18 @@ STAGE PLANS: Execution mode: vectorized, llap Reduce Operator Tree: Group By Operator - keys: KEY._col0 (type: boolean) - mode: mergepartial - outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE - Select Operator - expressions: true (type: boolean) - outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE - Reduce Output Operator - sort order: - Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE - value expressions: _col0 (type: boolean) - Reducer 5 - Execution mode: vectorized, llap - Reduce Operator Tree: - Group By Operator aggregations: count(VALUE._col0) mode: mergepartial outputColumnNames: _col0 Statistics: Num rows: 1 Data size: 8 Basic stats: PARTIAL Column stats: COMPLETE - Reduce Output Operator - sort order: + Select Operator + expressions: _col0 (type: bigint), _col0 (type: bigint) + outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 8 Basic stats: PARTIAL Column stats: COMPLETE - value expressions: _col0 (type: bigint) + Reduce Output Operator + sort order: + Statistics: Num rows: 1 Data size: 8 Basic stats: PARTIAL Column stats: COMPLETE + value expressions: _col0 (type: bigint), _col1 (type: bigint) Stage: Stage-0 Fetch Operator diff --git ql/src/test/results/clientpositive/llap/subquery_scalar.q.out ql/src/test/results/clientpositive/llap/subquery_scalar.q.out index 1cf281afbd..bc3672aba9 100644 --- ql/src/test/results/clientpositive/llap/subquery_scalar.q.out +++ ql/src/test/results/clientpositive/llap/subquery_scalar.q.out @@ -337,7 +337,7 @@ STAGE PLANS: Processor Tree: ListSink -Warning: Shuffle Join MERGEJOIN[24][tables = [$hdt$_1, $hdt$_2, $hdt$_0]] in Stage 'Reducer 3' is a cross product +Warning: Shuffle Join MERGEJOIN[23][tables = [$hdt$_0, $hdt$_1, $hdt$_2]] in Stage 'Reducer 2' is a cross product PREHOOK: query: explain select * from part where p_name = (select p_name from part_null_n0 where p_name is null) PREHOOK: type: QUERY PREHOOK: Input: default@part @@ -357,71 +357,53 @@ STAGE PLANS: Tez #### A masked pattern was here #### Edges: - Reducer 2 <- Map 1 (CUSTOM_SIMPLE_EDGE) - Reducer 3 <- Map 1 (XPROD_EDGE), Map 4 (XPROD_EDGE), Reducer 2 (XPROD_EDGE) + Reducer 2 <- Map 1 (XPROD_EDGE), Map 3 (XPROD_EDGE), Reducer 4 (XPROD_EDGE) + Reducer 4 <- Map 3 (CUSTOM_SIMPLE_EDGE) #### A masked pattern was here #### Vertices: Map 1 Map Operator Tree: TableScan - alias: part_null_n0 - filterExpr: p_name is null (type: boolean) - Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE + alias: part + Statistics: Num rows: 26 Data size: 16094 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: p_name is null (type: boolean) - Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE + predicate: false (type: boolean) + Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE - Group By Operator - aggregations: count() - mode: hash - outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - sort order: - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - value expressions: _col0 (type: bigint) + expressions: p_partkey (type: int), p_name (type: string), p_mfgr (type: string), p_brand (type: string), p_type (type: string), p_size (type: int), p_container (type: string), p_retailprice (type: double), p_comment (type: string) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 + Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator sort order: - Statistics: Num rows: 1 Data size: 184 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE + value expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) Execution mode: vectorized, llap LLAP IO: no inputs - Map 4 + Map 3 Map Operator Tree: TableScan - alias: part - filterExpr: (p_name = null) (type: boolean) - Statistics: Num rows: 26 Data size: 16094 Basic stats: COMPLETE Column stats: COMPLETE - Filter Operator - predicate: (p_name = null) (type: boolean) - Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE - Select Operator - expressions: p_partkey (type: int), p_mfgr (type: string), p_brand (type: string), p_type (type: string), p_size (type: int), p_container (type: string), p_retailprice (type: double), p_comment (type: string) - outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7 - Statistics: Num rows: 1 Data size: 498 Basic stats: COMPLETE Column stats: COMPLETE + alias: part_null_n0 + Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: COMPLETE + Select Operator + Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: COMPLETE + Filter Operator + predicate: false (type: boolean) + Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: COMPLETE + Group By Operator + aggregations: count(0) + mode: hash + outputColumnNames: _col0 + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + sort order: + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + value expressions: _col0 (type: bigint) Reduce Output Operator sort order: - Statistics: Num rows: 1 Data size: 498 Basic stats: COMPLETE Column stats: COMPLETE - value expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: string), _col6 (type: double), _col7 (type: string) + Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: COMPLETE Execution mode: vectorized, llap LLAP IO: no inputs Reducer 2 - Execution mode: vectorized, llap - Reduce Operator Tree: - Group By Operator - aggregations: count(VALUE._col0) - mode: mergepartial - outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - Filter Operator - predicate: (sq_count_check(_col0) <= 1) (type: boolean) - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - Select Operator - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - sort order: - Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE - Reducer 3 Execution mode: llap Reduce Operator Tree: Merge Join Operator @@ -432,19 +414,28 @@ STAGE PLANS: 0 1 2 - outputColumnNames: _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9 - Statistics: Num rows: 1 Data size: 875 Basic stats: COMPLETE Column stats: NONE + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 + Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE + File Output Operator + compressed: false + Statistics: Num rows: 1 Data size: 619 Basic stats: COMPLETE Column stats: COMPLETE + table: + input format: org.apache.hadoop.mapred.SequenceFileInputFormat + output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat + serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + Reducer 4 + Execution mode: vectorized, llap + Reduce Operator Tree: + Group By Operator + aggregations: count(VALUE._col0) + mode: mergepartial + outputColumnNames: _col0 + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: _col2 (type: int), null (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 (type: int), _col7 (type: string), _col8 (type: double), _col9 (type: string) - outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 1 Data size: 875 Basic stats: COMPLETE Column stats: NONE - File Output Operator - compressed: false - Statistics: Num rows: 1 Data size: 875 Basic stats: COMPLETE Column stats: NONE - table: - input format: org.apache.hadoop.mapred.SequenceFileInputFormat - output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat - serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + sort order: + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE Stage: Stage-0 Fetch Operator @@ -452,7 +443,7 @@ STAGE PLANS: Processor Tree: ListSink -Warning: Shuffle Join MERGEJOIN[24][tables = [$hdt$_1, $hdt$_2, $hdt$_0]] in Stage 'Reducer 3' is a cross product +Warning: Shuffle Join MERGEJOIN[23][tables = [$hdt$_0, $hdt$_1, $hdt$_2]] in Stage 'Reducer 2' is a cross product PREHOOK: query: select * from part where p_name = (select p_name from part_null_n0 where p_name is null) PREHOOK: type: QUERY PREHOOK: Input: default@part @@ -3488,15 +3479,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col13 Statistics: Num rows: 7 Data size: 3595 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col10 = 0L) or (_col13 is null and _col3 is not null and (_col11 >= _col10))) (type: boolean) - Statistics: Num rows: 4 Data size: 2054 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col11 >= _col10) or (_col10 = 0L) or _col13 is not null or _col3 is null) and (_col13 is null or (_col10 = 0L)) and (_col3 is not null or (_col10 = 0L) or _col13 is not null)) (type: boolean) + Statistics: Num rows: 6 Data size: 3081 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 4 Data size: 2054 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 6 Data size: 3081 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 4 Data size: 2054 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 6 Data size: 3081 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -3735,17 +3726,17 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 14 Data size: 2025 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col12 is null and _col3 is not null and (_col10 >= _col9)) or (_col9 = 0L)) (type: boolean) - Statistics: Num rows: 9 Data size: 1301 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col10 >= _col9) or (_col9 = 0L) or _col12 is not null or _col3 is null) and (_col12 is null or (_col9 = 0L)) and (_col3 is not null or (_col9 = 0L) or _col12 is not null)) (type: boolean) + Statistics: Num rows: 14 Data size: 2025 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 9 Data size: 1301 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 14 Data size: 2025 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col4 (type: string) sort order: + Map-reduce partition columns: _col4 (type: string) - Statistics: Num rows: 9 Data size: 1301 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 14 Data size: 2025 Basic stats: COMPLETE Column stats: NONE value expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) Reducer 5 Execution mode: llap @@ -3758,14 +3749,14 @@ STAGE PLANS: 1 _col1 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9 residual filter predicates: {(not (_col1 like _col9))} - Statistics: Num rows: 5 Data size: 795 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 8 Data size: 1187 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 5 Data size: 795 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 8 Data size: 1187 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 5 Data size: 795 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 8 Data size: 1187 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -6372,15 +6363,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3 Statistics: Num rows: 2 Data size: 40 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN (_col3 is null) THEN (true) ELSE ((_col2 = 0L)) END (type: boolean) - Statistics: Num rows: 1 Data size: 20 Basic stats: COMPLETE Column stats: COMPLETE + predicate: ((_col2 = 0L) or _col3 is null) (type: boolean) + Statistics: Num rows: 2 Data size: 40 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int), _col1 (type: int) outputColumnNames: _col0, _col1 - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 2 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 2 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -6713,15 +6704,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3 Statistics: Num rows: 2 Data size: 17 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN (_col3 is null) THEN (true) ELSE ((_col2 = 0L)) END (type: boolean) - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE + predicate: ((_col2 = 0L) or _col3 is null) (type: boolean) + Statistics: Num rows: 2 Data size: 17 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: int) outputColumnNames: _col0, _col1 - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 17 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 17 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -7215,7 +7206,7 @@ HiveProject(ss_sold_date_sk=[$0], ss_quantity=[$1], ss_list_price=[$2]) HiveJoin(condition=[>($2, $3)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(ss_sold_date_sk=[$0], ss_quantity=[$1], ss_list_price=[$2]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(average_sales=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($0)], agg#1=[count($0)]) HiveProject($f0=[*(CAST($1):DECIMAL(10, 0), $2)]) HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) @@ -7259,7 +7250,7 @@ HiveProject(ss_sold_date_sk=[$0], ss_quantity=[$1], ss_list_price=[$2]) HiveJoin(condition=[>($2, $3)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(ss_sold_date_sk=[$0], ss_quantity=[$1], ss_list_price=[$2]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject(avg_window_0=[avg(*(CAST($1):DECIMAL(10, 0), $2)) OVER (PARTITION BY $2 ORDER BY $2 NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)]) + HiveProject(average_sales=[avg(*(CAST($1):DECIMAL(10, 0), $2)) OVER (PARTITION BY $2 ORDER BY $2 NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)]) HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(ss_sold_date_sk=[$0], ss_quantity=[$1], ss_list_price=[$2]) HiveFilter(condition=[IS NOT NULL($0)]) diff --git ql/src/test/results/clientpositive/llap/subquery_select.q.out ql/src/test/results/clientpositive/llap/subquery_select.q.out index 6255abdd70..44eaee958d 100644 --- ql/src/test/results/clientpositive/llap/subquery_select.q.out +++ ql/src/test/results/clientpositive/llap/subquery_select.q.out @@ -96,7 +96,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col3, _col4, _col5 Statistics: Num rows: 27 Data size: 440 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: _col0 (type: int), CASE WHEN (_col4) THEN (false) WHEN (_col3 is not null) THEN (true) WHEN (_col1) THEN (null) WHEN (_col5) THEN (null) ELSE (false) END (type: boolean) + expressions: _col0 (type: int), ((_col3 is not null and _col4) or ((_col1 or _col5) and null and _col4 and _col3 is null)) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 27 Data size: 216 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator @@ -138,7 +138,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: (_col0 = 0L) (type: boolean), (_col1 < _col0) (type: boolean) + expressions: (_col0 <> 0L) (type: boolean), (_col1 < _col0) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator @@ -294,7 +294,7 @@ STAGE PLANS: outputColumnNames: _col1, _col2, _col4, _col5, _col6, _col9 Statistics: Num rows: 48 Data size: 852 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: _col1 (type: int), CASE WHEN (_col5) THEN (false) WHEN (_col4 is null) THEN (false) WHEN (_col9 is not null) THEN (true) WHEN (_col2) THEN (null) WHEN (_col6) THEN (null) ELSE (false) END (type: boolean) + expressions: _col1 (type: int), ((_col9 is not null and (_col5 or _col4 is null) is not true) or ((_col2 or _col6) is true and null and (_col5 or _col4 is null) is not true and _col9 is null)) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 48 Data size: 384 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator @@ -430,15 +430,15 @@ STAGE PLANS: alias: part Statistics: Num rows: 26 Data size: 104 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: p_size (type: int), p_size is null (type: boolean) - outputColumnNames: _col0, _col1 - Statistics: Num rows: 26 Data size: 208 Basic stats: COMPLETE Column stats: COMPLETE + expressions: p_size (type: int), p_size is null (type: boolean), p_size is not null (type: boolean) + outputColumnNames: _col0, _col1, _col2 + Statistics: Num rows: 26 Data size: 312 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: int) sort order: + Map-reduce partition columns: _col0 (type: int) - Statistics: Num rows: 26 Data size: 208 Basic stats: COMPLETE Column stats: COMPLETE - value expressions: _col1 (type: boolean) + Statistics: Num rows: 26 Data size: 312 Basic stats: COMPLETE Column stats: COMPLETE + value expressions: _col1 (type: boolean), _col2 (type: boolean) Select Operator expressions: p_size (type: int) outputColumnNames: p_size @@ -476,12 +476,12 @@ STAGE PLANS: keys: 0 _col0 (type: int) 1 _col0 (type: int) - outputColumnNames: _col0, _col1, _col3 - Statistics: Num rows: 27 Data size: 224 Basic stats: COMPLETE Column stats: COMPLETE + outputColumnNames: _col0, _col1, _col2, _col4 + Statistics: Num rows: 27 Data size: 332 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator sort order: - Statistics: Num rows: 27 Data size: 224 Basic stats: COMPLETE Column stats: COMPLETE - value expressions: _col0 (type: int), _col1 (type: boolean), _col3 (type: boolean) + Statistics: Num rows: 27 Data size: 332 Basic stats: COMPLETE Column stats: COMPLETE + value expressions: _col0 (type: int), _col1 (type: boolean), _col2 (type: boolean), _col4 (type: boolean) Reducer 3 Execution mode: llap Reduce Operator Tree: @@ -491,10 +491,10 @@ STAGE PLANS: keys: 0 1 - outputColumnNames: _col0, _col1, _col3, _col4, _col5 - Statistics: Num rows: 27 Data size: 440 Basic stats: COMPLETE Column stats: COMPLETE + outputColumnNames: _col0, _col1, _col2, _col4, _col5, _col6, _col7, _col8 + Statistics: Num rows: 27 Data size: 764 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: _col0 (type: int), CASE WHEN (_col4) THEN (true) WHEN (_col3 is not null) THEN (false) WHEN (_col1) THEN (null) WHEN (_col5) THEN (null) ELSE (true) END (type: boolean) + expressions: _col0 (type: int), (_col5 or ((_col1 or _col6) and null and _col7 and _col4 is null) or (_col7 and _col4 is null and _col2 and _col8)) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 27 Data size: 216 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator @@ -536,13 +536,13 @@ STAGE PLANS: outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: (_col0 = 0L) (type: boolean), (_col1 < _col0) (type: boolean) - outputColumnNames: _col0, _col1 - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + expressions: (_col0 = 0L) (type: boolean), (_col1 < _col0) (type: boolean), (_col0 <> 0L) (type: boolean), (_col1 >= _col0) (type: boolean) + outputColumnNames: _col0, _col1, _col2, _col3 + Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator sort order: - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE - value expressions: _col0 (type: boolean), _col1 (type: boolean) + Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE + value expressions: _col0 (type: boolean), _col1 (type: boolean), _col2 (type: boolean), _col3 (type: boolean) Stage: Stage-0 Fetch Operator @@ -760,7 +760,7 @@ STAGE PLANS: outputColumnNames: _col1, _col2, _col4, _col5, _col6, _col9 Statistics: Num rows: 13 Data size: 364 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: _col1 (type: int), CASE WHEN (_col5) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col9 is not null) THEN (false) WHEN (_col2) THEN (null) WHEN (_col6) THEN (null) ELSE (true) END (type: boolean) + expressions: _col1 (type: int), ((_col5 or _col4 is null) is true or ((_col2 or _col6) is true and null and (_col5 or _col4 is null) is not true and _col9 is null) or ((_col5 or _col4 is null) is not true and _col9 is null and (_col2 or _col6) is not true)) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 13 Data size: 104 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator @@ -2307,7 +2307,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col3, _col4, _col5 Statistics: Num rows: 27 Data size: 440 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: _col0 (type: int), CASE WHEN (_col4) THEN (false) WHEN (_col3 is not null) THEN (true) WHEN (_col1) THEN (null) WHEN (_col5) THEN (null) ELSE (false) END (type: boolean) + expressions: _col0 (type: int), ((_col3 is not null and _col4) or ((_col1 or _col5) and null and _col4 and _col3 is null)) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 27 Data size: 216 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator @@ -2344,7 +2344,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: (_col0 = 0L) (type: boolean), (_col1 < _col0) (type: boolean) + expressions: (_col0 <> 0L) (type: boolean), (_col1 < _col0) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator @@ -2889,7 +2889,7 @@ STAGE PLANS: outputColumnNames: _col1, _col2, _col3 Statistics: Num rows: 36 Data size: 324 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: _col1 (type: int), CASE WHEN (_col3 is null) THEN (false) ELSE (_col2 is null) END (type: boolean) + expressions: _col1 (type: int), (_col2 is null and _col3 is not null) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 36 Data size: 288 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator @@ -3320,7 +3320,7 @@ STAGE PLANS: outputColumnNames: _col2, _col3, _col4, _col6, _col7, _col8, _col11, _col13, _col14, _col15 Statistics: Num rows: 49 Data size: 1476 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: _col2 (type: int), (CASE WHEN (_col7) THEN (false) WHEN (_col6 is null) THEN (false) WHEN (_col11 is not null) THEN (true) WHEN (_col3) THEN (null) WHEN (_col8) THEN (null) ELSE (false) END and CASE WHEN (_col14) THEN (false) WHEN (_col13 is not null) THEN (true) WHEN (_col4) THEN (null) WHEN (_col15) THEN (null) ELSE (false) END) (type: boolean) + expressions: _col2 (type: int), (((_col11 is not null and (_col7 or _col6 is null) is not true) or ((_col3 or _col8) is true and null and (_col7 or _col6 is null) is not true and _col11 is null)) and ((_col13 is not null and _col14) or ((_col4 or _col15) and null and _col14 and _col13 is null))) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 49 Data size: 392 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator @@ -3392,7 +3392,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: (_col0 = 0L) (type: boolean), (_col1 < _col0) (type: boolean) + expressions: (_col0 <> 0L) (type: boolean), (_col1 < _col0) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator @@ -3691,7 +3691,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col3, _col4, _col5 Statistics: Num rows: 27 Data size: 440 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: _col0 (type: int), CASE WHEN (_col4) THEN (false) WHEN (_col3 is not null) THEN (true) WHEN (_col1) THEN (null) WHEN (_col5) THEN (null) ELSE (false) END (type: boolean) + expressions: _col0 (type: int), ((_col3 is not null and _col4) or ((_col1 or _col5) and null and _col4 and _col3 is null)) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 27 Data size: 216 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator @@ -3771,7 +3771,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: (_col0 = 0L) (type: boolean), (_col1 < _col0) (type: boolean) + expressions: (_col0 <> 0L) (type: boolean), (_col1 < _col0) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator diff --git ql/src/test/results/clientpositive/llap/subquery_views.q.out ql/src/test/results/clientpositive/llap/subquery_views.q.out index aa50b468c3..e1a39c5fb4 100644 --- ql/src/test/results/clientpositive/llap/subquery_views.q.out +++ ql/src/test/results/clientpositive/llap/subquery_views.q.out @@ -245,7 +245,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col4, _col5, _col8 Statistics: Num rows: 27 Data size: 5346 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END (type: boolean) + predicate: (((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col0 is null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) (type: boolean) Statistics: Num rows: 13 Data size: 2574 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string), _col1 (type: string) @@ -345,7 +345,7 @@ STAGE PLANS: outputColumnNames: _col0, _col4, _col5, _col8 Statistics: Num rows: 27 Data size: 2889 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END (type: boolean) + predicate: (((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col0 is null) and (_col0 is not null or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) (type: boolean) Statistics: Num rows: 13 Data size: 1391 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string) diff --git ql/src/test/results/clientpositive/llap/tez_smb_reduce_side.q.out ql/src/test/results/clientpositive/llap/tez_smb_reduce_side.q.out index 5f8cbafb2d..4612122dfe 100644 --- ql/src/test/results/clientpositive/llap/tez_smb_reduce_side.q.out +++ ql/src/test/results/clientpositive/llap/tez_smb_reduce_side.q.out @@ -675,7 +675,7 @@ STAGE PLANS: outputColumnNames: _col0, _col2, _col3, _col5 Statistics: Num rows: 1 Data size: 24 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col2 = 0L)) THEN (true) WHEN (_col2 is null) THEN (true) WHEN (_col5 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col3 < _col2)) THEN (false) ELSE (true) END (type: boolean) + predicate: (((_col3 < _col2) is not true or ((_col2 = 0L) or _col2 is null) is true or _col5 is not null or _col0 is null) and (_col0 is not null or ((_col2 = 0L) or _col2 is null) is true or _col5 is not null) and (_col5 is null or ((_col2 = 0L) or _col2 is null) is true)) (type: boolean) Statistics: Num rows: 1 Data size: 24 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int) @@ -879,7 +879,7 @@ STAGE PLANS: outputColumnNames: _col0, _col2, _col3, _col5 Statistics: Num rows: 1 Data size: 24 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: CASE WHEN ((_col2 = 0L)) THEN (true) WHEN (_col2 is null) THEN (true) WHEN (_col5 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col3 < _col2)) THEN (false) ELSE (true) END (type: boolean) + predicate: (((_col3 < _col2) is not true or ((_col2 = 0L) or _col2 is null) is true or _col5 is not null or _col0 is null) and (_col0 is not null or ((_col2 = 0L) or _col2 is null) is true or _col5 is not null) and (_col5 is null or ((_col2 = 0L) or _col2 is null) is true)) (type: boolean) Statistics: Num rows: 1 Data size: 24 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: int) diff --git ql/src/test/results/clientpositive/llap/unionDistinct_1.q.out ql/src/test/results/clientpositive/llap/unionDistinct_1.q.out index 7f2cc85392..7c487c2330 100644 --- ql/src/test/results/clientpositive/llap/unionDistinct_1.q.out +++ ql/src/test/results/clientpositive/llap/unionDistinct_1.q.out @@ -3799,6 +3799,19 @@ POSTHOOK: Input: default@dst_union22_delta_n0@ds=1 POSTHOOK: Input: default@dst_union22_n0 POSTHOOK: Input: default@dst_union22_n0@ds=1 POSTHOOK: Output: default@dst_union22_n0@ds=2 +OPTIMIZED SQL: SELECT `k1`, `k2`, `k3`, `k4` +FROM (SELECT `k1`, `k2`, `k3`, `k4` +FROM `default`.`dst_union22_delta_n0` +WHERE `ds` = '1' AND `k0` <= 50 +UNION ALL +SELECT `t2`.`k1`, `t2`.`k2`, `t4`.`k3`, `t4`.`k4` +FROM (SELECT `k1`, `k2`, `ds` = '1' AS `=` +FROM `default`.`dst_union22_n0` +WHERE `k1` > 20) AS `t2` +LEFT JOIN (SELECT `k1`, `k3`, `k4` +FROM `default`.`dst_union22_delta_n0` +WHERE `ds` = '1' AND `k0` > 50 AND `k1` > 20) AS `t4` ON `t2`.`k1` = `t4`.`k1` AND `t2`.`=`) +GROUP BY `k1`, `k2`, `k3`, `k4` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-2 depends on stages: Stage-1 diff --git ql/src/test/results/clientpositive/llap/vector_case_when_1.q.out ql/src/test/results/clientpositive/llap/vector_case_when_1.q.out index 6529758a3a..296764225f 100644 --- ql/src/test/results/clientpositive/llap/vector_case_when_1.q.out +++ ql/src/test/results/clientpositive/llap/vector_case_when_1.q.out @@ -209,14 +209,20 @@ STAGE PLANS: native: true vectorizationSchemaColumns: [0:l_orderkey:int, 1:l_partkey:int, 2:l_suppkey:int, 3:l_linenumber:int, 4:l_quantity:int, 5:l_extendedprice:double, 6:l_discount:double, 7:l_tax:decimal(10,2)/DECIMAL_64, 8:l_returnflag:char(1), 9:l_linestatus:char(1), 10:l_shipdate:date, 11:l_commitdate:date, 12:l_receiptdate:date, 13:l_shipinstruct:varchar(20), 14:l_shipmode:char(10), 15:l_comment:string, 16:ROW__ID:struct] Select Operator - expressions: l_quantity (type: int), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN (null) ELSE (null) END (type: string), if((l_shipmode = 'SHIP '), date_add(l_shipdate, 10), date_add(l_shipdate, 5)) (type: date), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END (type: double), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END (type: double), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(10,2)), if((l_partkey > 30), CAST( l_receiptdate AS TIMESTAMP), CAST( l_commitdate AS TIMESTAMP)) (type: timestamp), if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null) (type: int), if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)) (type: int), if(((l_suppkey % 500) > 100), DATE'2009-01-01', DATE'2009-12-31') (type: date) + expressions: l_quantity (type: int), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') ELSE (null) END (type: string), if((l_shipmode = 'SHIP '), date_add(l_shipdate, 10), date_add(l_shipdate, 5)) (type: date), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END (type: double), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END (type: double), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(10,2)), if((l_partkey > 30), CAST( l_receiptdate AS TIMESTAMP), CAST( l_commitdate AS TIMESTAMP)) (type: timestamp), if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null) (type: int), if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)) (type: int), if(((l_suppkey % 500) > 100), DATE'2009-01-01', DATE'2009-12-31') (type: date) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16 Select Vectorization: className: VectorSelectOperator native: true +<<<<<<< HEAD + projectedOutputColumnNums: [4, 21, 26, 30, 34, 38, 42, 44, 46, 48, 50, 52, 54, 58, 61, 64, 67] + selectExpressions: VectorUDFAdaptor(CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END)(children: LongColEqualLongScalar(col 4:int, val 1) -> 17:boolean, LongColEqualLongScalar(col 4:int, val 2) -> 18:boolean, LongColLessLongScalar(col 4:int, val 10) -> 19:boolean, LongColLessLongScalar(col 4:int, val 100) -> 20:boolean) -> 21:string, VectorUDFAdaptor(CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END)(children: LongColEqualLongScalar(col 4:int, val 1) -> 22:boolean, LongColEqualLongScalar(col 4:int, val 2) -> 23:boolean, LongColLessLongScalar(col 4:int, val 10) -> 24:boolean, LongColLessLongScalar(col 4:int, val 100) -> 25:boolean) -> 26:string, VectorUDFAdaptor(CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') ELSE (null) END)(children: LongColEqualLongScalar(col 4:int, val 1) -> 27:boolean, LongColEqualLongScalar(col 4:int, val 2) -> 28:boolean, LongColLessLongScalar(col 4:int, val 10) -> 29:boolean) -> 30:string, IfExprLongColumnLongColumn(col 31:boolean, col 32:date, col 33:date)(children: StringGroupColEqualCharScalar(col 14:char(10), val SHIP) -> 31:boolean, VectorUDFDateAddColScalar(col 10:date, val 10) -> 32:date, VectorUDFDateAddColScalar(col 10:date, val 5) -> 33:date) -> 34:date, VectorUDFAdaptor(CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 35:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 36:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 36:double) -> 37:double) -> 38:double, VectorUDFAdaptor(CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 39:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 40:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 40:double) -> 41:double) -> 42:double, VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 43:boolean) -> 44:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 45:boolean) -> 46:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 47:boolean) -> 48:decimal(12,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 49:boolean) -> 50:decimal(12,2), IfExprDecimal64ScalarDecimal64Column(col 51:boolean, decimal64Val 0, decimalVal 0, col 7:decimal(10,2)/DECIMAL_64)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 51:boolean) -> 52:decimal(10,2)/DECIMAL_64, IfExprDecimal64ColumnDecimal64Scalar(col 53:boolean, col 7:decimal(10,2)/DECIMAL_64, decimal64Val 0, decimalVal 0)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 53:boolean) -> 54:decimal(10,2)/DECIMAL_64, IfExprTimestampColumnColumn(col 55:boolean, col 56:timestampcol 57:timestamp)(children: LongColGreaterLongScalar(col 1:int, val 30) -> 55:boolean, CastDateToTimestamp(col 12:date) -> 56:timestamp, CastDateToTimestamp(col 11:date) -> 57:timestamp) -> 58:timestamp, VectorUDFAdaptor(if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null))(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 59:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 60:int) -> 61:int, VectorUDFAdaptor(if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)))(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 62:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 63:int) -> 64:int, IfExprLongScalarLongScalar(col 66:boolean, val 14245, val 14609)(children: LongColGreaterLongScalar(col 65:int, val 100)(children: LongColModuloLongScalar(col 2:int, val 500) -> 65:int) -> 66:boolean) -> 67:date + Statistics: Num rows: 101 Data size: 57327 Basic stats: COMPLETE Column stats: NONE +======= projectedOutputColumnNums: [4, 21, 26, 31, 35, 39, 43, 45, 47, 49, 51, 53, 55, 59, 62, 65, 68] selectExpressions: VectorUDFAdaptor(CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END)(children: LongColEqualLongScalar(col 4:int, val 1) -> 17:boolean, LongColEqualLongScalar(col 4:int, val 2) -> 18:boolean, LongColLessLongScalar(col 4:int, val 10) -> 19:boolean, LongColLessLongScalar(col 4:int, val 100) -> 20:boolean) -> 21:string, VectorUDFAdaptor(CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END)(children: LongColEqualLongScalar(col 4:int, val 1) -> 22:boolean, LongColEqualLongScalar(col 4:int, val 2) -> 23:boolean, LongColLessLongScalar(col 4:int, val 10) -> 24:boolean, LongColLessLongScalar(col 4:int, val 100) -> 25:boolean) -> 26:string, VectorUDFAdaptor(CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN (null) ELSE (null) END)(children: LongColEqualLongScalar(col 4:int, val 1) -> 27:boolean, LongColEqualLongScalar(col 4:int, val 2) -> 28:boolean, LongColLessLongScalar(col 4:int, val 10) -> 29:boolean, LongColLessLongScalar(col 4:int, val 100) -> 30:boolean) -> 31:string, IfExprLongColumnLongColumn(col 32:boolean, col 33:date, col 34:date)(children: StringGroupColEqualCharScalar(col 14:char(10), val SHIP) -> 32:boolean, VectorUDFDateAddColScalar(col 10:date, val 10) -> 33:date, VectorUDFDateAddColScalar(col 10:date, val 5) -> 34:date) -> 35:date, VectorUDFAdaptor(CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 36:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 37:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 37:double) -> 38:double) -> 39:double, VectorUDFAdaptor(CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 40:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 41:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 41:double) -> 42:double) -> 43:double, VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 44:boolean) -> 45:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 46:boolean) -> 47:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 48:boolean) -> 49:decimal(12,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 50:boolean) -> 51:decimal(12,2), IfExprDecimal64ScalarDecimal64Column(col 52:boolean, decimal64Val 0, decimalVal 0, col 7:decimal(10,2)/DECIMAL_64)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 52:boolean) -> 53:decimal(10,2)/DECIMAL_64, IfExprDecimal64ColumnDecimal64Scalar(col 54:boolean, col 7:decimal(10,2)/DECIMAL_64, decimal64Val 0, decimalVal 0)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 54:boolean) -> 55:decimal(10,2)/DECIMAL_64, IfExprTimestampColumnColumn(col 56:boolean, col 57:timestampcol 58:timestamp)(children: LongColGreaterLongScalar(col 1:int, val 30) -> 56:boolean, CastDateToTimestamp(col 12:date) -> 57:timestamp, CastDateToTimestamp(col 11:date) -> 58:timestamp) -> 59:timestamp, VectorUDFAdaptor(if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null))(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 60:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 61:int) -> 62:int, VectorUDFAdaptor(if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)))(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 63:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 64:int) -> 65:int, IfExprLongScalarLongScalar(col 67:boolean, val 14245, val 14609)(children: LongColGreaterLongScalar(col 66:int, val 100)(children: LongColModuloLongScalar(col 2:int, val 500) -> 66:int) -> 67:boolean) -> 68:date Statistics: Num rows: 101 Data size: 141804 Basic stats: COMPLETE Column stats: COMPLETE +>>>>>>> asf/master File Output Operator compressed: false File Sink Vectorization: @@ -243,7 +249,7 @@ STAGE PLANS: includeColumns: [1, 2, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14] dataColumns: l_orderkey:int, l_partkey:int, l_suppkey:int, l_linenumber:int, l_quantity:int, l_extendedprice:double, l_discount:double, l_tax:decimal(10,2)/DECIMAL_64, l_returnflag:char(1), l_linestatus:char(1), l_shipdate:date, l_commitdate:date, l_receiptdate:date, l_shipinstruct:varchar(20), l_shipmode:char(10), l_comment:string partitionColumnCount: 0 - scratchColumnTypeNames: [bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, double, double, double, bigint, double, double, double, bigint, decimal(10,2), bigint, decimal(10,2), bigint, decimal(12,2), bigint, decimal(12,2), bigint, decimal(10,2)/DECIMAL_64, bigint, decimal(10,2)/DECIMAL_64, bigint, timestamp, timestamp, timestamp, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint] + scratchColumnTypeNames: [bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, double, double, double, bigint, double, double, double, bigint, decimal(10,2), bigint, decimal(10,2), bigint, decimal(12,2), bigint, decimal(12,2), bigint, decimal(10,2)/DECIMAL_64, bigint, decimal(10,2)/DECIMAL_64, bigint, timestamp, timestamp, timestamp, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint] Stage: Stage-0 Fetch Operator @@ -546,14 +552,19 @@ STAGE PLANS: native: true vectorizationSchemaColumns: [0:l_orderkey:int, 1:l_partkey:int, 2:l_suppkey:int, 3:l_linenumber:int, 4:l_quantity:int, 5:l_extendedprice:double, 6:l_discount:double, 7:l_tax:decimal(10,2)/DECIMAL_64, 8:l_returnflag:char(1), 9:l_linestatus:char(1), 10:l_shipdate:date, 11:l_commitdate:date, 12:l_receiptdate:date, 13:l_shipinstruct:varchar(20), 14:l_shipmode:char(10), 15:l_comment:string, 16:ROW__ID:struct] Select Operator - expressions: l_quantity (type: int), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN (null) ELSE (null) END (type: string), if((l_shipmode = 'SHIP '), date_add(l_shipdate, 10), date_add(l_shipdate, 5)) (type: date), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END (type: double), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END (type: double), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(10,2)), if((l_partkey > 30), CAST( l_receiptdate AS TIMESTAMP), CAST( l_commitdate AS TIMESTAMP)) (type: timestamp), if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null) (type: int), if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)) (type: int), if(((l_suppkey % 500) > 100), DATE'2009-01-01', DATE'2009-12-31') (type: date) + expressions: l_quantity (type: int), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') ELSE (null) END (type: string), if((l_shipmode = 'SHIP '), date_add(l_shipdate, 10), date_add(l_shipdate, 5)) (type: date), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END (type: double), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END (type: double), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(10,2)), if((l_partkey > 30), CAST( l_receiptdate AS TIMESTAMP), CAST( l_commitdate AS TIMESTAMP)) (type: timestamp), if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null) (type: int), if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)) (type: int), if(((l_suppkey % 500) > 100), DATE'2009-01-01', DATE'2009-12-31') (type: date) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16 Select Vectorization: className: VectorSelectOperator native: true projectedOutputColumnNums: [4, 24, 33, 40, 44, 49, 53, 55, 57, 59, 61, 63, 65, 69, 72, 75, 78] +<<<<<<< HEAD + selectExpressions: IfExprStringScalarStringGroupColumn(col 17:boolean, val Singlecol 23:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 17:boolean, IfExprStringScalarStringGroupColumn(col 18:boolean, val Twocol 22:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 18:boolean, IfExprStringScalarStringGroupColumn(col 19:boolean, val Somecol 21:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 19:boolean, IfExprStringScalarStringScalar(col 20:boolean, val Many, val Huge number)(children: LongColLessLongScalar(col 4:int, val 100) -> 20:boolean) -> 21:string) -> 22:string) -> 23:string) -> 24:string, IfExprStringScalarStringGroupColumn(col 25:boolean, val Singlecol 32:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 25:boolean, IfExprStringScalarStringGroupColumn(col 26:boolean, val Twocol 31:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 26:boolean, IfExprStringScalarStringGroupColumn(col 27:boolean, val Somecol 30:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 27:boolean, IfExprColumnNull(col 28:boolean, col 29:string, null)(children: LongColLessLongScalar(col 4:int, val 100) -> 28:boolean, ConstantVectorExpression(val Many) -> 29:string) -> 30:string) -> 31:string) -> 32:string) -> 33:string, IfExprStringScalarStringGroupColumn(col 34:boolean, val Singlecol 39:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 34:boolean, IfExprStringScalarStringGroupColumn(col 35:boolean, val Twocol 38:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 35:boolean, IfExprColumnNull(col 36:boolean, col 37:string, null)(children: LongColLessLongScalar(col 4:int, val 10) -> 36:boolean, ConstantVectorExpression(val Some) -> 37:string) -> 38:string) -> 39:string) -> 40:string, IfExprLongColumnLongColumn(col 41:boolean, col 42:date, col 43:date)(children: StringGroupColEqualCharScalar(col 14:char(10), val SHIP) -> 41:boolean, VectorUDFDateAddColScalar(col 10:date, val 10) -> 42:date, VectorUDFDateAddColScalar(col 10:date, val 5) -> 43:date) -> 44:date, IfExprDoubleColumnDoubleColumn(col 45:boolean, col 47:doublecol 48:double)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 45:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 46:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 46:double) -> 47:double, ConstantVectorExpression(val 0.0) -> 48:double) -> 49:double, IfExprDoubleColumnDoubleScalar(col 50:boolean, col 52:double, val 0.0)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 50:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 51:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 51:double) -> 52:double) -> 53:double, IfExprNullColumn(col 54:boolean, null, col 79)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 54:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 79:decimal(10,2)) -> 55:decimal(10,2), IfExprColumnNull(col 56:boolean, col 80:decimal(10,2), null)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 56:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 80:decimal(10,2)) -> 57:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 58:boolean) -> 59:decimal(12,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 60:boolean) -> 61:decimal(12,2), IfExprDecimal64ScalarDecimal64Column(col 62:boolean, decimal64Val 0, decimalVal 0, col 7:decimal(10,2)/DECIMAL_64)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 62:boolean) -> 63:decimal(10,2)/DECIMAL_64, IfExprDecimal64ColumnDecimal64Scalar(col 64:boolean, col 7:decimal(10,2)/DECIMAL_64, decimal64Val 0, decimalVal 0)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 64:boolean) -> 65:decimal(10,2)/DECIMAL_64, IfExprTimestampColumnColumn(col 66:boolean, col 67:timestampcol 68:timestamp)(children: LongColGreaterLongScalar(col 1:int, val 30) -> 66:boolean, CastDateToTimestamp(col 12:date) -> 67:timestamp, CastDateToTimestamp(col 11:date) -> 68:timestamp) -> 69:timestamp, IfExprColumnNull(col 70:boolean, col 71:int, null)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 70:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 71:int) -> 72:int, IfExprNullColumn(col 73:boolean, null, col 74)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 73:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 74:int) -> 75:int, IfExprLongScalarLongScalar(col 77:boolean, val 14245, val 14609)(children: LongColGreaterLongScalar(col 76:int, val 100)(children: LongColModuloLongScalar(col 2:int, val 500) -> 76:int) -> 77:boolean) -> 78:date + Statistics: Num rows: 101 Data size: 57327 Basic stats: COMPLETE Column stats: NONE +======= selectExpressions: IfExprStringScalarStringGroupColumn(col 17:boolean, val Singlecol 23:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 17:boolean, IfExprStringScalarStringGroupColumn(col 18:boolean, val Twocol 22:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 18:boolean, IfExprStringScalarStringGroupColumn(col 19:boolean, val Somecol 21:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 19:boolean, IfExprStringScalarStringScalar(col 20:boolean, val Many, val Huge number)(children: LongColLessLongScalar(col 4:int, val 100) -> 20:boolean) -> 21:string) -> 22:string) -> 23:string) -> 24:string, IfExprStringScalarStringGroupColumn(col 25:boolean, val Singlecol 32:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 25:boolean, IfExprStringScalarStringGroupColumn(col 26:boolean, val Twocol 31:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 26:boolean, IfExprStringScalarStringGroupColumn(col 27:boolean, val Somecol 30:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 27:boolean, IfExprColumnNull(col 28:boolean, col 29:string, null)(children: LongColLessLongScalar(col 4:int, val 100) -> 28:boolean, ConstantVectorExpression(val Many) -> 29:string) -> 30:string) -> 31:string) -> 32:string) -> 33:string, IfExprStringScalarStringGroupColumn(col 34:boolean, val Singlecol 39:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 34:boolean, IfExprStringScalarStringGroupColumn(col 35:boolean, val Twocol 38:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 35:boolean, IfExprStringScalarStringGroupColumn(col 36:boolean, val Somecol 37:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 36:boolean, IfExprNullNull(null, null) -> 37:string) -> 38:string) -> 39:string) -> 40:string, IfExprLongColumnLongColumn(col 41:boolean, col 42:date, col 43:date)(children: StringGroupColEqualCharScalar(col 14:char(10), val SHIP) -> 41:boolean, VectorUDFDateAddColScalar(col 10:date, val 10) -> 42:date, VectorUDFDateAddColScalar(col 10:date, val 5) -> 43:date) -> 44:date, IfExprDoubleColumnDoubleColumn(col 45:boolean, col 47:doublecol 48:double)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 45:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 46:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 46:double) -> 47:double, ConstantVectorExpression(val 0.0) -> 48:double) -> 49:double, IfExprDoubleColumnDoubleScalar(col 50:boolean, col 52:double, val 0.0)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 50:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 51:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 51:double) -> 52:double) -> 53:double, IfExprNullColumn(col 54:boolean, null, col 79)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 54:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 79:decimal(10,2)) -> 55:decimal(10,2), IfExprColumnNull(col 56:boolean, col 80:decimal(10,2), null)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 56:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 80:decimal(10,2)) -> 57:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 58:boolean) -> 59:decimal(12,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 60:boolean) -> 61:decimal(12,2), IfExprDecimal64ScalarDecimal64Column(col 62:boolean, decimal64Val 0, decimalVal 0, col 7:decimal(10,2)/DECIMAL_64)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 62:boolean) -> 63:decimal(10,2)/DECIMAL_64, IfExprDecimal64ColumnDecimal64Scalar(col 64:boolean, col 7:decimal(10,2)/DECIMAL_64, decimal64Val 0, decimalVal 0)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 64:boolean) -> 65:decimal(10,2)/DECIMAL_64, IfExprTimestampColumnColumn(col 66:boolean, col 67:timestampcol 68:timestamp)(children: LongColGreaterLongScalar(col 1:int, val 30) -> 66:boolean, CastDateToTimestamp(col 12:date) -> 67:timestamp, CastDateToTimestamp(col 11:date) -> 68:timestamp) -> 69:timestamp, IfExprColumnNull(col 70:boolean, col 71:int, null)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 70:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 71:int) -> 72:int, IfExprNullColumn(col 73:boolean, null, col 74)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 73:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 74:int) -> 75:int, IfExprLongScalarLongScalar(col 77:boolean, val 14245, val 14609)(children: LongColGreaterLongScalar(col 76:int, val 100)(children: LongColModuloLongScalar(col 2:int, val 500) -> 76:int) -> 77:boolean) -> 78:date Statistics: Num rows: 101 Data size: 141804 Basic stats: COMPLETE Column stats: COMPLETE +>>>>>>> asf/master File Output Operator compressed: false File Sink Vectorization: @@ -883,14 +894,20 @@ STAGE PLANS: native: true vectorizationSchemaColumns: [0:l_orderkey:int, 1:l_partkey:int, 2:l_suppkey:int, 3:l_linenumber:int, 4:l_quantity:int, 5:l_extendedprice:double, 6:l_discount:double, 7:l_tax:decimal(10,2)/DECIMAL_64, 8:l_returnflag:char(1), 9:l_linestatus:char(1), 10:l_shipdate:date, 11:l_commitdate:date, 12:l_receiptdate:date, 13:l_shipinstruct:varchar(20), 14:l_shipmode:char(10), 15:l_comment:string, 16:ROW__ID:struct] Select Operator - expressions: l_quantity (type: int), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN (null) ELSE (null) END (type: string), if((l_shipmode = 'SHIP '), date_add(l_shipdate, 10), date_add(l_shipdate, 5)) (type: date), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END (type: double), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END (type: double), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(10,2)), if((l_partkey > 30), CAST( l_receiptdate AS TIMESTAMP), CAST( l_commitdate AS TIMESTAMP)) (type: timestamp), if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null) (type: int), if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)) (type: int), if(((l_suppkey % 500) > 100), DATE'2009-01-01', DATE'2009-12-31') (type: date) + expressions: l_quantity (type: int), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') ELSE (null) END (type: string), if((l_shipmode = 'SHIP '), date_add(l_shipdate, 10), date_add(l_shipdate, 5)) (type: date), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END (type: double), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END (type: double), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(10,2)), if((l_partkey > 30), CAST( l_receiptdate AS TIMESTAMP), CAST( l_commitdate AS TIMESTAMP)) (type: timestamp), if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null) (type: int), if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)) (type: int), if(((l_suppkey % 500) > 100), DATE'2009-01-01', DATE'2009-12-31') (type: date) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16 Select Vectorization: className: VectorSelectOperator native: true +<<<<<<< HEAD + projectedOutputColumnNums: [4, 27, 39, 48, 52, 57, 62, 64, 66, 71, 76, 78, 80, 84, 87, 90, 93] + selectExpressions: IfExprColumnCondExpr(col 17:boolean, col 18:stringcol 26:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 17:boolean, ConstantVectorExpression(val Single) -> 18:string, IfExprColumnCondExpr(col 19:boolean, col 20:stringcol 25:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 19:boolean, ConstantVectorExpression(val Two) -> 20:string, IfExprColumnCondExpr(col 21:boolean, col 22:stringcol 24:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 21:boolean, ConstantVectorExpression(val Some) -> 22:string, IfExprStringScalarStringScalar(col 23:boolean, val Many, val Huge number)(children: LongColLessLongScalar(col 4:int, val 100) -> 23:boolean) -> 24:string) -> 25:string) -> 26:string) -> 27:string, IfExprColumnCondExpr(col 28:boolean, col 29:stringcol 38:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 28:boolean, ConstantVectorExpression(val Single) -> 29:string, IfExprColumnCondExpr(col 30:boolean, col 31:stringcol 37:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 30:boolean, ConstantVectorExpression(val Two) -> 31:string, IfExprColumnCondExpr(col 32:boolean, col 33:stringcol 36:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 32:boolean, ConstantVectorExpression(val Some) -> 33:string, IfExprColumnNull(col 34:boolean, col 35:string, null)(children: LongColLessLongScalar(col 4:int, val 100) -> 34:boolean, ConstantVectorExpression(val Many) -> 35:string) -> 36:string) -> 37:string) -> 38:string) -> 39:string, IfExprColumnCondExpr(col 40:boolean, col 41:stringcol 47:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 40:boolean, ConstantVectorExpression(val Single) -> 41:string, IfExprColumnCondExpr(col 42:boolean, col 43:stringcol 46:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 42:boolean, ConstantVectorExpression(val Two) -> 43:string, IfExprColumnNull(col 44:boolean, col 45:string, null)(children: LongColLessLongScalar(col 4:int, val 10) -> 44:boolean, ConstantVectorExpression(val Some) -> 45:string) -> 46:string) -> 47:string) -> 48:string, IfExprCondExprCondExpr(col 49:boolean, col 50:datecol 51:date)(children: StringGroupColEqualCharScalar(col 14:char(10), val SHIP) -> 49:boolean, VectorUDFDateAddColScalar(col 10:date, val 10) -> 50:date, VectorUDFDateAddColScalar(col 10:date, val 5) -> 51:date) -> 52:date, IfExprCondExprCondExpr(col 53:boolean, col 55:doublecol 56:double)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 53:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 54:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 54:double) -> 55:double, ConstantVectorExpression(val 0.0) -> 56:double) -> 57:double, IfExprCondExprColumn(col 58:boolean, col 60:double, col 61:double)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 58:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 59:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 59:double) -> 60:double, ConstantVectorExpression(val 0.0) -> 61:double) -> 62:double, IfExprNullColumn(col 63:boolean, null, col 94)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 63:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 94:decimal(10,2)) -> 64:decimal(10,2), IfExprColumnNull(col 65:boolean, col 95:decimal(10,2), null)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 65:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 95:decimal(10,2)) -> 66:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 70:boolean) -> 71:decimal(12,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 75:boolean) -> 76:decimal(12,2), IfExprDecimal64ScalarDecimal64Column(col 77:boolean, decimal64Val 0, decimalVal 0, col 7:decimal(10,2)/DECIMAL_64)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 77:boolean) -> 78:decimal(10,2)/DECIMAL_64, IfExprDecimal64ColumnDecimal64Scalar(col 79:boolean, col 7:decimal(10,2)/DECIMAL_64, decimal64Val 0, decimalVal 0)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 79:boolean) -> 80:decimal(10,2)/DECIMAL_64, IfExprCondExprCondExpr(col 81:boolean, col 82:timestampcol 83:timestamp)(children: LongColGreaterLongScalar(col 1:int, val 30) -> 81:boolean, CastDateToTimestamp(col 12:date) -> 82:timestamp, CastDateToTimestamp(col 11:date) -> 83:timestamp) -> 84:timestamp, IfExprCondExprNull(col 85:boolean, col 86:int, null)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 85:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 86:int) -> 87:int, IfExprNullCondExpr(col 88:boolean, null, col 89:int)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 88:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 89:int) -> 90:int, IfExprLongScalarLongScalar(col 92:boolean, val 14245, val 14609)(children: LongColGreaterLongScalar(col 91:int, val 100)(children: LongColModuloLongScalar(col 2:int, val 500) -> 91:int) -> 92:boolean) -> 93:date + Statistics: Num rows: 101 Data size: 57327 Basic stats: COMPLETE Column stats: NONE +======= projectedOutputColumnNums: [4, 27, 39, 49, 53, 58, 63, 65, 67, 72, 77, 79, 81, 85, 88, 91, 94] selectExpressions: IfExprColumnCondExpr(col 17:boolean, col 18:stringcol 26:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 17:boolean, ConstantVectorExpression(val Single) -> 18:string, IfExprColumnCondExpr(col 19:boolean, col 20:stringcol 25:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 19:boolean, ConstantVectorExpression(val Two) -> 20:string, IfExprColumnCondExpr(col 21:boolean, col 22:stringcol 24:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 21:boolean, ConstantVectorExpression(val Some) -> 22:string, IfExprStringScalarStringScalar(col 23:boolean, val Many, val Huge number)(children: LongColLessLongScalar(col 4:int, val 100) -> 23:boolean) -> 24:string) -> 25:string) -> 26:string) -> 27:string, IfExprColumnCondExpr(col 28:boolean, col 29:stringcol 38:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 28:boolean, ConstantVectorExpression(val Single) -> 29:string, IfExprColumnCondExpr(col 30:boolean, col 31:stringcol 37:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 30:boolean, ConstantVectorExpression(val Two) -> 31:string, IfExprColumnCondExpr(col 32:boolean, col 33:stringcol 36:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 32:boolean, ConstantVectorExpression(val Some) -> 33:string, IfExprColumnNull(col 34:boolean, col 35:string, null)(children: LongColLessLongScalar(col 4:int, val 100) -> 34:boolean, ConstantVectorExpression(val Many) -> 35:string) -> 36:string) -> 37:string) -> 38:string) -> 39:string, IfExprColumnCondExpr(col 40:boolean, col 41:stringcol 48:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 40:boolean, ConstantVectorExpression(val Single) -> 41:string, IfExprColumnCondExpr(col 42:boolean, col 43:stringcol 47:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 42:boolean, ConstantVectorExpression(val Two) -> 43:string, IfExprColumnCondExpr(col 44:boolean, col 45:stringcol 46:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 44:boolean, ConstantVectorExpression(val Some) -> 45:string, IfExprNullNull(null, null) -> 46:string) -> 47:string) -> 48:string) -> 49:string, IfExprCondExprCondExpr(col 50:boolean, col 51:datecol 52:date)(children: StringGroupColEqualCharScalar(col 14:char(10), val SHIP) -> 50:boolean, VectorUDFDateAddColScalar(col 10:date, val 10) -> 51:date, VectorUDFDateAddColScalar(col 10:date, val 5) -> 52:date) -> 53:date, IfExprCondExprCondExpr(col 54:boolean, col 56:doublecol 57:double)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 54:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 55:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 55:double) -> 56:double, ConstantVectorExpression(val 0.0) -> 57:double) -> 58:double, IfExprCondExprColumn(col 59:boolean, col 61:double, col 62:double)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 59:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 60:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 60:double) -> 61:double, ConstantVectorExpression(val 0.0) -> 62:double) -> 63:double, IfExprNullColumn(col 64:boolean, null, col 95)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 64:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 95:decimal(10,2)) -> 65:decimal(10,2), IfExprColumnNull(col 66:boolean, col 96:decimal(10,2), null)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 66:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 96:decimal(10,2)) -> 67:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 71:boolean) -> 72:decimal(12,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 76:boolean) -> 77:decimal(12,2), IfExprDecimal64ScalarDecimal64Column(col 78:boolean, decimal64Val 0, decimalVal 0, col 7:decimal(10,2)/DECIMAL_64)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 78:boolean) -> 79:decimal(10,2)/DECIMAL_64, IfExprDecimal64ColumnDecimal64Scalar(col 80:boolean, col 7:decimal(10,2)/DECIMAL_64, decimal64Val 0, decimalVal 0)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 80:boolean) -> 81:decimal(10,2)/DECIMAL_64, IfExprCondExprCondExpr(col 82:boolean, col 83:timestampcol 84:timestamp)(children: LongColGreaterLongScalar(col 1:int, val 30) -> 82:boolean, CastDateToTimestamp(col 12:date) -> 83:timestamp, CastDateToTimestamp(col 11:date) -> 84:timestamp) -> 85:timestamp, IfExprCondExprNull(col 86:boolean, col 87:int, null)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 86:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 87:int) -> 88:int, IfExprNullCondExpr(col 89:boolean, null, col 90:int)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 89:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 90:int) -> 91:int, IfExprLongScalarLongScalar(col 93:boolean, val 14245, val 14609)(children: LongColGreaterLongScalar(col 92:int, val 100)(children: LongColModuloLongScalar(col 2:int, val 500) -> 92:int) -> 93:boolean) -> 94:date Statistics: Num rows: 101 Data size: 141804 Basic stats: COMPLETE Column stats: COMPLETE +>>>>>>> asf/master File Output Operator compressed: false File Sink Vectorization: @@ -917,7 +934,7 @@ STAGE PLANS: includeColumns: [1, 2, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14] dataColumns: l_orderkey:int, l_partkey:int, l_suppkey:int, l_linenumber:int, l_quantity:int, l_extendedprice:double, l_discount:double, l_tax:decimal(10,2)/DECIMAL_64, l_returnflag:char(1), l_linestatus:char(1), l_shipdate:date, l_commitdate:date, l_receiptdate:date, l_shipinstruct:varchar(20), l_shipmode:char(10), l_comment:string partitionColumnCount: 0 - scratchColumnTypeNames: [bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, string, bigint, string, bigint, string, bigint, string, string, string, string, string, bigint, bigint, bigint, bigint, bigint, double, double, double, double, bigint, double, double, double, double, bigint, decimal(10,2), bigint, decimal(10,2), bigint, bigint, decimal(12,2), bigint, decimal(12,2), bigint, decimal(12,2), bigint, bigint, decimal(12,2), bigint, decimal(10,2)/DECIMAL_64, bigint, decimal(10,2)/DECIMAL_64, bigint, timestamp, timestamp, timestamp, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, decimal(10,2), decimal(10,2)] + scratchColumnTypeNames: [bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, string, bigint, string, bigint, string, bigint, string, string, string, string, bigint, bigint, bigint, bigint, bigint, double, double, double, double, bigint, double, double, double, double, bigint, decimal(10,2), bigint, decimal(10,2), bigint, bigint, decimal(12,2), bigint, decimal(12,2), bigint, decimal(12,2), bigint, bigint, decimal(12,2), bigint, decimal(10,2)/DECIMAL_64, bigint, decimal(10,2)/DECIMAL_64, bigint, timestamp, timestamp, timestamp, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, decimal(10,2), decimal(10,2)] Stage: Stage-0 Fetch Operator diff --git ql/src/test/results/clientpositive/llap/vector_case_when_2.q.out ql/src/test/results/clientpositive/llap/vector_case_when_2.q.out index 218a5cff17..d7a7c2f9f9 100644 --- ql/src/test/results/clientpositive/llap/vector_case_when_2.q.out +++ ql/src/test/results/clientpositive/llap/vector_case_when_2.q.out @@ -144,13 +144,13 @@ STAGE PLANS: native: true vectorizationSchemaColumns: [0:cdate:date, 1:ctimestamp1:timestamp, 2:stimestamp1:string, 3:ctimestamp2:timestamp, 4:ROW__ID:struct] Select Operator - expressions: ctimestamp1 (type: timestamp), ctimestamp2 (type: timestamp), CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN (null) ELSE (null) END (type: string), if((ctimestamp1 < TIMESTAMP'1974-10-04 17:21:03.989'), year(ctimestamp1), year(ctimestamp2)) (type: int), CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END (type: string), if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)) (type: int), if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null) (type: int), if(((UDFToDouble(ctimestamp1) % 500.0D) > 100.0D), date_add(cdate, 1), date_add(cdate, 365)) (type: date), stimestamp1 (type: string) + expressions: ctimestamp1 (type: timestamp), ctimestamp2 (type: timestamp), CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') ELSE (null) END (type: string), if((ctimestamp1 < TIMESTAMP'1974-10-04 17:21:03.989'), year(ctimestamp1), year(ctimestamp2)) (type: int), CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END (type: string), if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)) (type: int), if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null) (type: int), if(((UDFToDouble(ctimestamp1) % 500.0D) > 100.0D), date_add(cdate, 1), date_add(cdate, 365)) (type: date), stimestamp1 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10 Select Vectorization: className: VectorSelectOperator native: true - projectedOutputColumnNums: [1, 3, 9, 14, 19, 23, 25, 28, 33, 39, 2] - selectExpressions: VectorUDFAdaptor(CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 1800-12-31 00:00:00) -> 5:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 1900-01-01 00:00:00) -> 6:boolean, TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 7:boolean, TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 8:boolean) -> 9:string, VectorUDFAdaptor(CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 10:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 11:boolean, TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 12:boolean, TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 13:boolean) -> 14:string, VectorUDFAdaptor(CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN (null) ELSE (null) END)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 15:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 16:boolean, TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 17:boolean, TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 18:boolean) -> 19:string, IfExprLongColumnLongColumn(col 20:boolean, col 21:int, col 22:int)(children: TimestampColLessTimestampScalar(col 1:timestamp, val 1974-10-04 17:21:03.989) -> 20:boolean, VectorUDFYearTimestamp(col 1:timestamp, field YEAR) -> 21:int, VectorUDFYearTimestamp(col 3:timestamp, field YEAR) -> 22:int) -> 23:int, VectorUDFAdaptor(CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END)(children: SelectStringColLikeStringScalar(col 2:string) -> 24:boolean) -> 25:string, VectorUDFAdaptor(if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)))(children: TimestampColEqualTimestampScalar(col 1:timestamp, val 2021-09-24 03:18:32.413655165) -> 26:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 27:int) -> 28:int, VectorUDFAdaptor(if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null))(children: ColAndCol(col 29:boolean, col 30:boolean)(children: TimestampColGreaterEqualTimestampScalar(col 3:timestamp, val 5344-10-04 18:40:08.165) -> 29:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 6631-11-13 16:31:29.702202248) -> 30:boolean) -> 31:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 32:int) -> 33:int, IfExprLongColumnLongColumn(col 36:boolean, col 37:date, col 38:date)(children: DoubleColGreaterDoubleScalar(col 35:double, val 100.0)(children: DoubleColModuloDoubleScalar(col 34:double, val 500.0)(children: CastTimestampToDouble(col 1:timestamp) -> 34:double) -> 35:double) -> 36:boolean, VectorUDFDateAddColScalar(col 0:date, val 1) -> 37:date, VectorUDFDateAddColScalar(col 0:date, val 365) -> 38:date) -> 39:date + projectedOutputColumnNums: [1, 3, 9, 14, 18, 22, 24, 27, 32, 38, 2] + selectExpressions: VectorUDFAdaptor(CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 1800-12-31 00:00:00) -> 5:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 1900-01-01 00:00:00) -> 6:boolean, TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 7:boolean, TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 8:boolean) -> 9:string, VectorUDFAdaptor(CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 10:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 11:boolean, TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 12:boolean, TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 13:boolean) -> 14:string, VectorUDFAdaptor(CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') ELSE (null) END)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 15:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 16:boolean, TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 17:boolean) -> 18:string, IfExprLongColumnLongColumn(col 19:boolean, col 20:int, col 21:int)(children: TimestampColLessTimestampScalar(col 1:timestamp, val 1974-10-04 17:21:03.989) -> 19:boolean, VectorUDFYearTimestamp(col 1:timestamp, field YEAR) -> 20:int, VectorUDFYearTimestamp(col 3:timestamp, field YEAR) -> 21:int) -> 22:int, VectorUDFAdaptor(CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END)(children: SelectStringColLikeStringScalar(col 2:string) -> 23:boolean) -> 24:string, VectorUDFAdaptor(if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)))(children: TimestampColEqualTimestampScalar(col 1:timestamp, val 2021-09-24 03:18:32.413655165) -> 25:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 26:int) -> 27:int, VectorUDFAdaptor(if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null))(children: ColAndCol(col 28:boolean, col 29:boolean)(children: TimestampColGreaterEqualTimestampScalar(col 3:timestamp, val 5344-10-04 18:40:08.165) -> 28:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 6631-11-13 16:31:29.702202248) -> 29:boolean) -> 30:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 31:int) -> 32:int, IfExprLongColumnLongColumn(col 35:boolean, col 36:date, col 37:date)(children: DoubleColGreaterDoubleScalar(col 34:double, val 100.0)(children: DoubleColModuloDoubleScalar(col 33:double, val 500.0)(children: CastTimestampToDouble(col 1:timestamp) -> 33:double) -> 34:double) -> 35:boolean, VectorUDFDateAddColScalar(col 0:date, val 1) -> 36:date, VectorUDFDateAddColScalar(col 0:date, val 365) -> 37:date) -> 38:date Statistics: Num rows: 51 Data size: 50745 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: timestamp), _col10 (type: string), _col1 (type: timestamp) @@ -160,7 +160,7 @@ STAGE PLANS: keyColumns: 1:timestamp, 2:string, 3:timestamp native: true nativeConditionsMet: hive.vectorized.execution.reducesink.new.enabled IS true, hive.execution.engine tez IN [tez, spark] IS true, No PTF TopN IS true, No DISTINCT columns IS true, BinarySortableSerDe for keys IS true, LazyBinarySerDe for values IS true - valueColumns: 9:string, 14:string, 19:string, 23:int, 25:string, 28:int, 33:int, 39:date + valueColumns: 9:string, 14:string, 18:string, 22:int, 24:string, 27:int, 32:int, 38:date Statistics: Num rows: 51 Data size: 50745 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: int), _col8 (type: int), _col9 (type: date) Execution mode: vectorized, llap @@ -179,7 +179,7 @@ STAGE PLANS: includeColumns: [0, 1, 2, 3] dataColumns: cdate:date, ctimestamp1:timestamp, stimestamp1:string, ctimestamp2:timestamp partitionColumnCount: 0 - scratchColumnTypeNames: [bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, double, double, bigint, bigint, bigint, bigint] + scratchColumnTypeNames: [bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, double, double, bigint, bigint, bigint, bigint] Reducer 2 Execution mode: vectorized, llap Reduce Vectorization: @@ -433,13 +433,13 @@ STAGE PLANS: native: true vectorizationSchemaColumns: [0:cdate:date, 1:ctimestamp1:timestamp, 2:stimestamp1:string, 3:ctimestamp2:timestamp, 4:ROW__ID:struct] Select Operator - expressions: ctimestamp1 (type: timestamp), ctimestamp2 (type: timestamp), CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN (null) ELSE (null) END (type: string), if((ctimestamp1 < TIMESTAMP'1974-10-04 17:21:03.989'), year(ctimestamp1), year(ctimestamp2)) (type: int), CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END (type: string), if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)) (type: int), if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null) (type: int), if(((UDFToDouble(ctimestamp1) % 500.0D) > 100.0D), date_add(cdate, 1), date_add(cdate, 365)) (type: date), stimestamp1 (type: string) + expressions: ctimestamp1 (type: timestamp), ctimestamp2 (type: timestamp), CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') ELSE (null) END (type: string), if((ctimestamp1 < TIMESTAMP'1974-10-04 17:21:03.989'), year(ctimestamp1), year(ctimestamp2)) (type: int), CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END (type: string), if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)) (type: int), if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null) (type: int), if(((UDFToDouble(ctimestamp1) % 500.0D) > 100.0D), date_add(cdate, 1), date_add(cdate, 365)) (type: date), stimestamp1 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10 Select Vectorization: className: VectorSelectOperator native: true projectedOutputColumnNums: [1, 3, 12, 21, 28, 32, 34, 37, 42, 48, 2] - selectExpressions: IfExprStringScalarStringGroupColumn(col 5:boolean, val 1800s or Earliercol 11:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 1800-12-31 00:00:00) -> 5:boolean, IfExprStringScalarStringGroupColumn(col 6:boolean, val 1900scol 10:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 1900-01-01 00:00:00) -> 6:boolean, IfExprStringScalarStringGroupColumn(col 7:boolean, val Late 2000scol 9:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 7:boolean, IfExprStringScalarStringScalar(col 8:boolean, val Early 2010s, val Unknown)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 8:boolean) -> 9:string) -> 10:string) -> 11:string) -> 12:string, IfExprStringScalarStringGroupColumn(col 13:boolean, val Oldcol 20:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 13:boolean, IfExprStringScalarStringGroupColumn(col 14:boolean, val Early 2000scol 19:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 14:boolean, IfExprStringScalarStringGroupColumn(col 15:boolean, val Late 2000scol 18:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 15:boolean, IfExprColumnNull(col 16:boolean, col 17:string, null)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 16:boolean, ConstantVectorExpression(val Early 2010s) -> 17:string) -> 18:string) -> 19:string) -> 20:string) -> 21:string, IfExprStringScalarStringGroupColumn(col 22:boolean, val Oldcol 27:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 22:boolean, IfExprStringScalarStringGroupColumn(col 23:boolean, val Early 2000scol 26:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 23:boolean, IfExprStringScalarStringGroupColumn(col 24:boolean, val Late 2000scol 25:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 24:boolean, IfExprNullNull(null, null) -> 25:string) -> 26:string) -> 27:string) -> 28:string, IfExprLongColumnLongColumn(col 29:boolean, col 30:int, col 31:int)(children: TimestampColLessTimestampScalar(col 1:timestamp, val 1974-10-04 17:21:03.989) -> 29:boolean, VectorUDFYearTimestamp(col 1:timestamp, field YEAR) -> 30:int, VectorUDFYearTimestamp(col 3:timestamp, field YEAR) -> 31:int) -> 32:int, IfExprStringGroupColumnStringScalar(col 33:boolean, col 2:string, val 2018-03-08 23:04:59)(children: SelectStringColLikeStringScalar(col 2:string) -> 33:boolean) -> 34:string, IfExprNullColumn(col 35:boolean, null, col 36)(children: TimestampColEqualTimestampScalar(col 1:timestamp, val 2021-09-24 03:18:32.413655165) -> 35:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 36:int) -> 37:int, IfExprColumnNull(col 40:boolean, col 41:int, null)(children: ColAndCol(col 38:boolean, col 39:boolean)(children: TimestampColGreaterEqualTimestampScalar(col 3:timestamp, val 5344-10-04 18:40:08.165) -> 38:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 6631-11-13 16:31:29.702202248) -> 39:boolean) -> 40:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 41:int) -> 42:int, IfExprLongColumnLongColumn(col 45:boolean, col 46:date, col 47:date)(children: DoubleColGreaterDoubleScalar(col 44:double, val 100.0)(children: DoubleColModuloDoubleScalar(col 43:double, val 500.0)(children: CastTimestampToDouble(col 1:timestamp) -> 43:double) -> 44:double) -> 45:boolean, VectorUDFDateAddColScalar(col 0:date, val 1) -> 46:date, VectorUDFDateAddColScalar(col 0:date, val 365) -> 47:date) -> 48:date + selectExpressions: IfExprStringScalarStringGroupColumn(col 5:boolean, val 1800s or Earliercol 11:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 1800-12-31 00:00:00) -> 5:boolean, IfExprStringScalarStringGroupColumn(col 6:boolean, val 1900scol 10:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 1900-01-01 00:00:00) -> 6:boolean, IfExprStringScalarStringGroupColumn(col 7:boolean, val Late 2000scol 9:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 7:boolean, IfExprStringScalarStringScalar(col 8:boolean, val Early 2010s, val Unknown)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 8:boolean) -> 9:string) -> 10:string) -> 11:string) -> 12:string, IfExprStringScalarStringGroupColumn(col 13:boolean, val Oldcol 20:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 13:boolean, IfExprStringScalarStringGroupColumn(col 14:boolean, val Early 2000scol 19:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 14:boolean, IfExprStringScalarStringGroupColumn(col 15:boolean, val Late 2000scol 18:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 15:boolean, IfExprColumnNull(col 16:boolean, col 17:string, null)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 16:boolean, ConstantVectorExpression(val Early 2010s) -> 17:string) -> 18:string) -> 19:string) -> 20:string) -> 21:string, IfExprStringScalarStringGroupColumn(col 22:boolean, val Oldcol 27:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 22:boolean, IfExprStringScalarStringGroupColumn(col 23:boolean, val Early 2000scol 26:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 23:boolean, IfExprColumnNull(col 24:boolean, col 25:string, null)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 24:boolean, ConstantVectorExpression(val Late 2000s) -> 25:string) -> 26:string) -> 27:string) -> 28:string, IfExprLongColumnLongColumn(col 29:boolean, col 30:int, col 31:int)(children: TimestampColLessTimestampScalar(col 1:timestamp, val 1974-10-04 17:21:03.989) -> 29:boolean, VectorUDFYearTimestamp(col 1:timestamp, field YEAR) -> 30:int, VectorUDFYearTimestamp(col 3:timestamp, field YEAR) -> 31:int) -> 32:int, IfExprStringGroupColumnStringScalar(col 33:boolean, col 2:string, val 2018-03-08 23:04:59)(children: SelectStringColLikeStringScalar(col 2:string) -> 33:boolean) -> 34:string, IfExprNullColumn(col 35:boolean, null, col 36)(children: TimestampColEqualTimestampScalar(col 1:timestamp, val 2021-09-24 03:18:32.413655165) -> 35:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 36:int) -> 37:int, IfExprColumnNull(col 40:boolean, col 41:int, null)(children: ColAndCol(col 38:boolean, col 39:boolean)(children: TimestampColGreaterEqualTimestampScalar(col 3:timestamp, val 5344-10-04 18:40:08.165) -> 38:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 6631-11-13 16:31:29.702202248) -> 39:boolean) -> 40:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 41:int) -> 42:int, IfExprLongColumnLongColumn(col 45:boolean, col 46:date, col 47:date)(children: DoubleColGreaterDoubleScalar(col 44:double, val 100.0)(children: DoubleColModuloDoubleScalar(col 43:double, val 500.0)(children: CastTimestampToDouble(col 1:timestamp) -> 43:double) -> 44:double) -> 45:boolean, VectorUDFDateAddColScalar(col 0:date, val 1) -> 46:date, VectorUDFDateAddColScalar(col 0:date, val 365) -> 47:date) -> 48:date Statistics: Num rows: 51 Data size: 50745 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: timestamp), _col10 (type: string), _col1 (type: timestamp) @@ -722,13 +722,13 @@ STAGE PLANS: native: true vectorizationSchemaColumns: [0:cdate:date, 1:ctimestamp1:timestamp, 2:stimestamp1:string, 3:ctimestamp2:timestamp, 4:ROW__ID:struct] Select Operator - expressions: ctimestamp1 (type: timestamp), ctimestamp2 (type: timestamp), CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN (null) ELSE (null) END (type: string), if((ctimestamp1 < TIMESTAMP'1974-10-04 17:21:03.989'), year(ctimestamp1), year(ctimestamp2)) (type: int), CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END (type: string), if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)) (type: int), if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null) (type: int), if(((UDFToDouble(ctimestamp1) % 500.0D) > 100.0D), date_add(cdate, 1), date_add(cdate, 365)) (type: date), stimestamp1 (type: string) + expressions: ctimestamp1 (type: timestamp), ctimestamp2 (type: timestamp), CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') ELSE (null) END (type: string), if((ctimestamp1 < TIMESTAMP'1974-10-04 17:21:03.989'), year(ctimestamp1), year(ctimestamp2)) (type: int), CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END (type: string), if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)) (type: int), if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null) (type: int), if(((UDFToDouble(ctimestamp1) % 500.0D) > 100.0D), date_add(cdate, 1), date_add(cdate, 365)) (type: date), stimestamp1 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10 Select Vectorization: className: VectorSelectOperator native: true - projectedOutputColumnNums: [1, 3, 15, 27, 37, 41, 43, 46, 51, 57, 2] - selectExpressions: IfExprColumnCondExpr(col 5:boolean, col 6:stringcol 14:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 1800-12-31 00:00:00) -> 5:boolean, ConstantVectorExpression(val 1800s or Earlier) -> 6:string, IfExprColumnCondExpr(col 7:boolean, col 8:stringcol 13:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 1900-01-01 00:00:00) -> 7:boolean, ConstantVectorExpression(val 1900s) -> 8:string, IfExprColumnCondExpr(col 9:boolean, col 10:stringcol 12:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 9:boolean, ConstantVectorExpression(val Late 2000s) -> 10:string, IfExprStringScalarStringScalar(col 11:boolean, val Early 2010s, val Unknown)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 11:boolean) -> 12:string) -> 13:string) -> 14:string) -> 15:string, IfExprColumnCondExpr(col 16:boolean, col 17:stringcol 26:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 16:boolean, ConstantVectorExpression(val Old) -> 17:string, IfExprColumnCondExpr(col 18:boolean, col 19:stringcol 25:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 18:boolean, ConstantVectorExpression(val Early 2000s) -> 19:string, IfExprColumnCondExpr(col 20:boolean, col 21:stringcol 24:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 20:boolean, ConstantVectorExpression(val Late 2000s) -> 21:string, IfExprColumnNull(col 22:boolean, col 23:string, null)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 22:boolean, ConstantVectorExpression(val Early 2010s) -> 23:string) -> 24:string) -> 25:string) -> 26:string) -> 27:string, IfExprColumnCondExpr(col 28:boolean, col 29:stringcol 36:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 28:boolean, ConstantVectorExpression(val Old) -> 29:string, IfExprColumnCondExpr(col 30:boolean, col 31:stringcol 35:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 30:boolean, ConstantVectorExpression(val Early 2000s) -> 31:string, IfExprColumnCondExpr(col 32:boolean, col 33:stringcol 34:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 32:boolean, ConstantVectorExpression(val Late 2000s) -> 33:string, IfExprNullNull(null, null) -> 34:string) -> 35:string) -> 36:string) -> 37:string, IfExprCondExprCondExpr(col 38:boolean, col 39:intcol 40:int)(children: TimestampColLessTimestampScalar(col 1:timestamp, val 1974-10-04 17:21:03.989) -> 38:boolean, VectorUDFYearTimestamp(col 1:timestamp, field YEAR) -> 39:int, VectorUDFYearTimestamp(col 3:timestamp, field YEAR) -> 40:int) -> 41:int, IfExprStringGroupColumnStringScalar(col 42:boolean, col 2:string, val 2018-03-08 23:04:59)(children: SelectStringColLikeStringScalar(col 2:string) -> 42:boolean) -> 43:string, IfExprNullCondExpr(col 44:boolean, null, col 45:int)(children: TimestampColEqualTimestampScalar(col 1:timestamp, val 2021-09-24 03:18:32.413655165) -> 44:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 45:int) -> 46:int, IfExprCondExprNull(col 49:boolean, col 50:int, null)(children: ColAndCol(col 47:boolean, col 48:boolean)(children: TimestampColGreaterEqualTimestampScalar(col 3:timestamp, val 5344-10-04 18:40:08.165) -> 47:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 6631-11-13 16:31:29.702202248) -> 48:boolean) -> 49:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 50:int) -> 51:int, IfExprCondExprCondExpr(col 54:boolean, col 55:datecol 56:date)(children: DoubleColGreaterDoubleScalar(col 53:double, val 100.0)(children: DoubleColModuloDoubleScalar(col 52:double, val 500.0)(children: CastTimestampToDouble(col 1:timestamp) -> 52:double) -> 53:double) -> 54:boolean, VectorUDFDateAddColScalar(col 0:date, val 1) -> 55:date, VectorUDFDateAddColScalar(col 0:date, val 365) -> 56:date) -> 57:date + projectedOutputColumnNums: [1, 3, 15, 27, 36, 40, 42, 45, 50, 56, 2] + selectExpressions: IfExprColumnCondExpr(col 5:boolean, col 6:stringcol 14:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 1800-12-31 00:00:00) -> 5:boolean, ConstantVectorExpression(val 1800s or Earlier) -> 6:string, IfExprColumnCondExpr(col 7:boolean, col 8:stringcol 13:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 1900-01-01 00:00:00) -> 7:boolean, ConstantVectorExpression(val 1900s) -> 8:string, IfExprColumnCondExpr(col 9:boolean, col 10:stringcol 12:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 9:boolean, ConstantVectorExpression(val Late 2000s) -> 10:string, IfExprStringScalarStringScalar(col 11:boolean, val Early 2010s, val Unknown)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 11:boolean) -> 12:string) -> 13:string) -> 14:string) -> 15:string, IfExprColumnCondExpr(col 16:boolean, col 17:stringcol 26:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 16:boolean, ConstantVectorExpression(val Old) -> 17:string, IfExprColumnCondExpr(col 18:boolean, col 19:stringcol 25:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 18:boolean, ConstantVectorExpression(val Early 2000s) -> 19:string, IfExprColumnCondExpr(col 20:boolean, col 21:stringcol 24:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 20:boolean, ConstantVectorExpression(val Late 2000s) -> 21:string, IfExprColumnNull(col 22:boolean, col 23:string, null)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 22:boolean, ConstantVectorExpression(val Early 2010s) -> 23:string) -> 24:string) -> 25:string) -> 26:string) -> 27:string, IfExprColumnCondExpr(col 28:boolean, col 29:stringcol 35:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 28:boolean, ConstantVectorExpression(val Old) -> 29:string, IfExprColumnCondExpr(col 30:boolean, col 31:stringcol 34:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 30:boolean, ConstantVectorExpression(val Early 2000s) -> 31:string, IfExprColumnNull(col 32:boolean, col 33:string, null)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 32:boolean, ConstantVectorExpression(val Late 2000s) -> 33:string) -> 34:string) -> 35:string) -> 36:string, IfExprCondExprCondExpr(col 37:boolean, col 38:intcol 39:int)(children: TimestampColLessTimestampScalar(col 1:timestamp, val 1974-10-04 17:21:03.989) -> 37:boolean, VectorUDFYearTimestamp(col 1:timestamp, field YEAR) -> 38:int, VectorUDFYearTimestamp(col 3:timestamp, field YEAR) -> 39:int) -> 40:int, IfExprStringGroupColumnStringScalar(col 41:boolean, col 2:string, val 2018-03-08 23:04:59)(children: SelectStringColLikeStringScalar(col 2:string) -> 41:boolean) -> 42:string, IfExprNullCondExpr(col 43:boolean, null, col 44:int)(children: TimestampColEqualTimestampScalar(col 1:timestamp, val 2021-09-24 03:18:32.413655165) -> 43:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 44:int) -> 45:int, IfExprCondExprNull(col 48:boolean, col 49:int, null)(children: ColAndCol(col 46:boolean, col 47:boolean)(children: TimestampColGreaterEqualTimestampScalar(col 3:timestamp, val 5344-10-04 18:40:08.165) -> 46:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 6631-11-13 16:31:29.702202248) -> 47:boolean) -> 48:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 49:int) -> 50:int, IfExprCondExprCondExpr(col 53:boolean, col 54:datecol 55:date)(children: DoubleColGreaterDoubleScalar(col 52:double, val 100.0)(children: DoubleColModuloDoubleScalar(col 51:double, val 500.0)(children: CastTimestampToDouble(col 1:timestamp) -> 51:double) -> 52:double) -> 53:boolean, VectorUDFDateAddColScalar(col 0:date, val 1) -> 54:date, VectorUDFDateAddColScalar(col 0:date, val 365) -> 55:date) -> 56:date Statistics: Num rows: 51 Data size: 50745 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: timestamp), _col10 (type: string), _col1 (type: timestamp) @@ -738,7 +738,7 @@ STAGE PLANS: keyColumns: 1:timestamp, 2:string, 3:timestamp native: true nativeConditionsMet: hive.vectorized.execution.reducesink.new.enabled IS true, hive.execution.engine tez IN [tez, spark] IS true, No PTF TopN IS true, No DISTINCT columns IS true, BinarySortableSerDe for keys IS true, LazyBinarySerDe for values IS true - valueColumns: 15:string, 27:string, 37:string, 41:int, 43:string, 46:int, 51:int, 57:date + valueColumns: 15:string, 27:string, 36:string, 40:int, 42:string, 45:int, 50:int, 56:date Statistics: Num rows: 51 Data size: 50745 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: int), _col8 (type: int), _col9 (type: date) Execution mode: vectorized, llap @@ -757,7 +757,7 @@ STAGE PLANS: includeColumns: [0, 1, 2, 3] dataColumns: cdate:date, ctimestamp1:timestamp, stimestamp1:string, ctimestamp2:timestamp partitionColumnCount: 0 - scratchColumnTypeNames: [bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, string, bigint, string, bigint, string, bigint, string, string, string, string, string, bigint, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, double, double, bigint, bigint, bigint, bigint] + scratchColumnTypeNames: [bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, string, bigint, string, bigint, string, bigint, string, string, string, string, bigint, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, double, double, bigint, bigint, bigint, bigint] Reducer 2 Execution mode: vectorized, llap Reduce Vectorization: diff --git ql/src/test/results/clientpositive/llap/vector_coalesce_3.q.out ql/src/test/results/clientpositive/llap/vector_coalesce_3.q.out index 493cfca23a..0a341490e1 100644 --- ql/src/test/results/clientpositive/llap/vector_coalesce_3.q.out +++ ql/src/test/results/clientpositive/llap/vector_coalesce_3.q.out @@ -162,13 +162,13 @@ STAGE PLANS: native: true vectorizationSchemaColumns: [0:member:bigint, 1:attr:bigint, 2:ROW__ID:struct] Select Operator - expressions: member (type: bigint), CASE WHEN (CASE WHEN (attr is not null) THEN ((attr > 1L)) ELSE (true) END) THEN (attr) ELSE (null) END (type: bigint) + expressions: member (type: bigint), CASE WHEN (((attr > 1L) or attr is null)) THEN (attr) ELSE (null) END (type: bigint) outputColumnNames: _col0, _col1 Select Vectorization: className: VectorSelectOperator native: true - projectedOutputColumnNums: [0, 7] - selectExpressions: IfExprColumnNull(col 6:boolean, col 1:bigint, null)(children: IfExprCondExprColumn(col 3:boolean, col 4:boolean, col 5:boolean)(children: IsNotNull(col 1:bigint) -> 3:boolean, LongColGreaterLongScalar(col 1:bigint, val 1) -> 4:boolean, ConstantVectorExpression(val 1) -> 5:boolean) -> 6:boolean, col 1:bigint) -> 7:bigint + projectedOutputColumnNums: [0, 6] + selectExpressions: IfExprColumnNull(col 5:boolean, col 1:bigint, null)(children: ColOrCol(col 3:boolean, col 4:boolean)(children: LongColGreaterLongScalar(col 1:bigint, val 1) -> 3:boolean, IsNull(col 1:bigint) -> 4:boolean) -> 5:boolean, col 1:bigint) -> 6:bigint Statistics: Num rows: 3 Data size: 48 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: bigint) @@ -179,7 +179,7 @@ STAGE PLANS: keyColumns: 0:bigint native: true nativeConditionsMet: hive.vectorized.execution.reducesink.new.enabled IS true, hive.execution.engine tez IN [tez, spark] IS true, No PTF TopN IS true, No DISTINCT columns IS true, BinarySortableSerDe for keys IS true, LazyBinarySerDe for values IS true - valueColumns: 7:bigint + valueColumns: 6:bigint Statistics: Num rows: 3 Data size: 48 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col1 (type: bigint) Execution mode: vectorized, llap @@ -198,7 +198,7 @@ STAGE PLANS: includeColumns: [0, 1] dataColumns: member:bigint, attr:bigint partitionColumnCount: 0 - scratchColumnTypeNames: [bigint, bigint, bigint, bigint, bigint] + scratchColumnTypeNames: [bigint, bigint, bigint, bigint] Stage: Stage-0 Fetch Operator diff --git ql/src/test/results/clientpositive/llap/vector_decimal_math_funcs.q.out ql/src/test/results/clientpositive/llap/vector_decimal_math_funcs.q.out index b26fb62e17..f1906f52e7 100644 --- ql/src/test/results/clientpositive/llap/vector_decimal_math_funcs.q.out +++ ql/src/test/results/clientpositive/llap/vector_decimal_math_funcs.q.out @@ -119,8 +119,13 @@ STAGE PLANS: Map Operator Tree: TableScan alias: decimal_test_n0 +<<<<<<< HEAD + filterExpr: (((cbigint % 500L) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) + Statistics: Num rows: 12289 Data size: 1401120 Basic stats: COMPLETE Column stats: NONE +======= filterExpr: (((cbigint % 500) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) Statistics: Num rows: 12289 Data size: 1100992 Basic stats: COMPLETE Column stats: COMPLETE +>>>>>>> asf/master TableScan Vectorization: native: true vectorizationSchemaColumns: [0:cbigint:bigint, 1:cdouble:double, 2:cdecimal1:decimal(20,10), 3:cdecimal2:decimal(23,14), 4:ROW__ID:struct] @@ -129,8 +134,13 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: FilterExprAndExpr(children: FilterLongColEqualLongScalar(col 5:bigint, val 0)(children: LongColModuloLongScalar(col 0:bigint, val 500) -> 5:bigint), FilterDoubleColGreaterEqualDoubleScalar(col 7:double, val -1.0)(children: FuncSinDoubleToDouble(col 6:double)(children: CastDecimalToDouble(col 2:decimal(20,10)) -> 6:double) -> 7:double)) +<<<<<<< HEAD + predicate: (((cbigint % 500L) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) + Statistics: Num rows: 2048 Data size: 233500 Basic stats: COMPLETE Column stats: NONE +======= predicate: (((cbigint % 500) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) Statistics: Num rows: 2048 Data size: 183600 Basic stats: COMPLETE Column stats: COMPLETE +>>>>>>> asf/master Select Operator expressions: cdecimal1 (type: decimal(20,10)), round(cdecimal1, 2) (type: decimal(13,2)), round(cdecimal1) (type: decimal(11,0)), floor(cdecimal1) (type: decimal(11,0)), ceil(cdecimal1) (type: decimal(11,0)), round(exp(cdecimal1), 58) (type: double), ln(cdecimal1) (type: double), log10(cdecimal1) (type: double), log2(cdecimal1) (type: double), log2((cdecimal1 - 15601)) (type: double), log(2, cdecimal1) (type: double), power(log2(cdecimal1), 2) (type: double), power(log2(cdecimal1), 2) (type: double), sqrt(cdecimal1) (type: double), abs(cdecimal1) (type: decimal(20,10)), sin(cdecimal1) (type: double), asin(cdecimal1) (type: double), cos(cdecimal1) (type: double), acos(cdecimal1) (type: double), atan(cdecimal1) (type: double), degrees(cdecimal1) (type: double), radians(cdecimal1) (type: double), cdecimal1 (type: decimal(20,10)), (- cdecimal1) (type: decimal(20,10)), sign(cdecimal1) (type: int), cos(((- sin(log(cdecimal1))) + 3.14159D)) (type: double) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20, _col21, _col22, _col23, _col24, _col25 @@ -370,8 +380,13 @@ STAGE PLANS: Map Operator Tree: TableScan alias: decimal_test_small +<<<<<<< HEAD + filterExpr: (((cbigint % 500L) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) + Statistics: Num rows: 12288 Data size: 1401000 Basic stats: COMPLETE Column stats: NONE +======= filterExpr: (((cbigint % 500) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) Statistics: Num rows: 12288 Data size: 1100992 Basic stats: COMPLETE Column stats: COMPLETE +>>>>>>> asf/master TableScan Vectorization: native: true vectorizationSchemaColumns: [0:cbigint:bigint, 1:cdouble:double, 2:cdecimal1:decimal(12,4)/DECIMAL_64, 3:cdecimal2:decimal(14,8)/DECIMAL_64, 4:ROW__ID:struct] @@ -380,8 +395,13 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: FilterExprAndExpr(children: FilterLongColEqualLongScalar(col 5:bigint, val 0)(children: LongColModuloLongScalar(col 0:bigint, val 500) -> 5:bigint), FilterDoubleColGreaterEqualDoubleScalar(col 8:double, val -1.0)(children: FuncSinDoubleToDouble(col 7:double)(children: CastDecimalToDouble(col 6:decimal(12,4))(children: ConvertDecimal64ToDecimal(col 2:decimal(12,4)/DECIMAL_64) -> 6:decimal(12,4)) -> 7:double) -> 8:double)) +<<<<<<< HEAD + predicate: (((cbigint % 500L) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) + Statistics: Num rows: 2048 Data size: 233500 Basic stats: COMPLETE Column stats: NONE +======= predicate: (((cbigint % 500) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) Statistics: Num rows: 2048 Data size: 183600 Basic stats: COMPLETE Column stats: COMPLETE +>>>>>>> asf/master Select Operator expressions: cdecimal1 (type: decimal(12,4)), round(cdecimal1, 2) (type: decimal(11,2)), round(cdecimal1) (type: decimal(9,0)), floor(cdecimal1) (type: decimal(9,0)), ceil(cdecimal1) (type: decimal(9,0)), round(exp(cdecimal1), 58) (type: double), ln(cdecimal1) (type: double), log10(cdecimal1) (type: double), log2(cdecimal1) (type: double), log2((cdecimal1 - 15601)) (type: double), log(2, cdecimal1) (type: double), power(log2(cdecimal1), 2) (type: double), power(log2(cdecimal1), 2) (type: double), sqrt(cdecimal1) (type: double), abs(cdecimal1) (type: decimal(12,4)), sin(cdecimal1) (type: double), asin(cdecimal1) (type: double), cos(cdecimal1) (type: double), acos(cdecimal1) (type: double), atan(cdecimal1) (type: double), degrees(cdecimal1) (type: double), radians(cdecimal1) (type: double), cdecimal1 (type: decimal(12,4)), (- cdecimal1) (type: decimal(12,4)), sign(cdecimal1) (type: int), cos(((- sin(log(cdecimal1))) + 3.14159D)) (type: double) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16, _col17, _col18, _col19, _col20, _col21, _col22, _col23, _col24, _col25 diff --git ql/src/test/results/clientpositive/llap/vector_groupby_mapjoin.q.out ql/src/test/results/clientpositive/llap/vector_groupby_mapjoin.q.out index c20bc71257..ddaf6d7115 100644 --- ql/src/test/results/clientpositive/llap/vector_groupby_mapjoin.q.out +++ ql/src/test/results/clientpositive/llap/vector_groupby_mapjoin.q.out @@ -93,8 +93,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterLongColEqualLongScalar(col 4:bigint, val 0), FilterExprAndExpr(children: SelectColumnIsNull(col 3:boolean), SelectColumnIsNotNull(col 0:string), FilterLongColGreaterEqualLongColumn(col 5:bigint, col 4:bigint))) - predicate: ((_col2 = 0L) or (_col5 is null and _col0 is not null and (_col3 >= _col2))) (type: boolean) + predicateExpression: FilterExprAndExpr(children: FilterExprOrExpr(children: SelectColumnIsNull(col 3:boolean), FilterLongColEqualLongScalar(col 4:bigint, val 0)), FilterExprOrExpr(children: SelectColumnIsNotNull(col 0:string), FilterLongColEqualLongScalar(col 4:bigint, val 0), SelectColumnIsNotNull(col 3:boolean)), FilterExprOrExpr(children: FilterLongColGreaterEqualLongColumn(col 5:bigint, col 4:bigint), FilterLongColEqualLongScalar(col 4:bigint, val 0), SelectColumnIsNotNull(col 3:boolean), SelectColumnIsNull(col 0:string))) + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col0 is null) and (_col0 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) Statistics: Num rows: 895 Data size: 175214 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: string), _col1 (type: string) diff --git ql/src/test/results/clientpositive/llap/vectorization_0.q.out ql/src/test/results/clientpositive/llap/vectorization_0.q.out index ec0712b8bb..9fe775d649 100644 --- ql/src/test/results/clientpositive/llap/vectorization_0.q.out +++ ql/src/test/results/clientpositive/llap/vectorization_0.q.out @@ -30772,6 +30772,9 @@ POSTHOOK: query: explain extended select * from alltypesorc where POSTHOOK: type: QUERY POSTHOOK: Input: default@alltypesorc #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `ctinyint`, `csmallint`, `cint`, `cbigint`, `cfloat`, `cdouble`, `cstring1`, `cstring2`, `ctimestamp1`, `ctimestamp2`, `cboolean1`, `cboolean2` +FROM `default`.`alltypesorc` +WHERE ROW(`cint`, `cfloat`) IN (ROW(49, 3.5), ROW(47, 2.09), ROW(45, 3.02)) STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -31017,6 +31020,11 @@ POSTHOOK: query: explain extended select count(*),cstring1 from alltypesorc wher POSTHOOK: type: QUERY POSTHOOK: Input: default@alltypesorc #### A masked pattern was here #### +OPTIMIZED SQL: SELECT COUNT(*) AS `_o__c0`, `cstring1` +FROM `default`.`alltypesorc` +WHERE `cstring1` IN ('biology', 'history', 'topology') +GROUP BY `cstring1` +ORDER BY `cstring1` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 diff --git ql/src/test/results/clientpositive/llap/vectorization_5.q.out ql/src/test/results/clientpositive/llap/vectorization_5.q.out index 8fe415657c..573ae4fa22 100644 --- ql/src/test/results/clientpositive/llap/vectorization_5.q.out +++ ql/src/test/results/clientpositive/llap/vectorization_5.q.out @@ -62,7 +62,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((cboolean2 is not null and (cstring1 like '%b%')) or ((UDFToDouble(ctinyint) = cdouble) and ctimestamp2 is not null and (cstring2 like 'a'))) (type: boolean) + filterExpr: (((cstring1 like '%b%') and cboolean2 is not null) or ((UDFToDouble(ctinyint) = cdouble) and (cstring2 like 'a') and ctimestamp2 is not null)) (type: boolean) Statistics: Num rows: 12288 Data size: 2454862 Basic stats: COMPLETE Column stats: COMPLETE TableScan Vectorization: native: true @@ -71,8 +71,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: SelectColumnIsNotNull(col 11:boolean), FilterStringColLikeStringScalar(col 6:string, pattern %b%)), FilterExprAndExpr(children: FilterDoubleColEqualDoubleColumn(col 13:double, col 5:double)(children: CastLongToDouble(col 0:tinyint) -> 13:double), SelectColumnIsNotNull(col 9:timestamp), FilterStringColLikeStringScalar(col 7:string, pattern a))) - predicate: (((UDFToDouble(ctinyint) = cdouble) and ctimestamp2 is not null and (cstring2 like 'a')) or (cboolean2 is not null and (cstring1 like '%b%'))) (type: boolean) + predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: FilterStringColLikeStringScalar(col 6:string, pattern %b%), SelectColumnIsNotNull(col 11:boolean)), FilterExprAndExpr(children: FilterDoubleColEqualDoubleColumn(col 13:double, col 5:double)(children: CastLongToDouble(col 0:tinyint) -> 13:double), FilterStringColLikeStringScalar(col 7:string, pattern a), SelectColumnIsNotNull(col 9:timestamp))) + predicate: (((UDFToDouble(ctinyint) = cdouble) and (cstring2 like 'a') and ctimestamp2 is not null) or ((cstring1 like '%b%') and cboolean2 is not null)) (type: boolean) Statistics: Num rows: 7658 Data size: 1529972 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: ctinyint (type: tinyint), csmallint (type: smallint), cint (type: int) diff --git ql/src/test/results/clientpositive/llap/vectorization_8.q.out ql/src/test/results/clientpositive/llap/vectorization_8.q.out index 3959239dbe..7d0594ae8f 100644 --- ql/src/test/results/clientpositive/llap/vectorization_8.q.out +++ ql/src/test/results/clientpositive/llap/vectorization_8.q.out @@ -72,7 +72,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((cstring2 is not null and (UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D)) or (cfloat < -6432.0) or (cboolean1 is not null and (cdouble = 988888.0D))) (type: boolean) + filterExpr: (((UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D) and cstring2 is not null) or (cfloat < -6432.0) or ((cdouble = 988888.0D) and cboolean1 is not null)) (type: boolean) Statistics: Num rows: 12288 Data size: 2983078 Basic stats: COMPLETE Column stats: COMPLETE TableScan Vectorization: native: true @@ -81,8 +81,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: SelectColumnIsNotNull(col 7:string), FilterDoubleColLessEqualDoubleScalar(col 13:double, val 10.0)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 16.0)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: SelectColumnIsNotNull(col 10:boolean), FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0))) - predicate: ((cboolean1 is not null and (cdouble = 988888.0D)) or (cfloat < -6432.0) or (cstring2 is not null and (UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D))) (type: boolean) + predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: FilterDoubleColLessEqualDoubleScalar(col 13:double, val 10.0)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 16.0)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double), SelectColumnIsNotNull(col 7:string)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0), SelectColumnIsNotNull(col 10:boolean))) + predicate: (((UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D) and cstring2 is not null) or ((cdouble = 988888.0D) and cboolean1 is not null) or (cfloat < -6432.0)) (type: boolean) Statistics: Num rows: 3059 Data size: 742850 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: ctimestamp1 (type: timestamp), cdouble (type: double), cboolean1 (type: boolean), cstring1 (type: string), cfloat (type: float), (- cdouble) (type: double), (-5638.15D - cdouble) (type: double), (cdouble * -257.0D) (type: double), (UDFToFloat(cint) + cfloat) (type: float), ((- cdouble) + UDFToDouble(cbigint)) (type: double), (- cdouble) (type: double), (-1.389 - cfloat) (type: float), (- cfloat) (type: float), ((-5638.15D - cdouble) + UDFToDouble((UDFToFloat(cint) + cfloat))) (type: double) @@ -313,7 +313,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((cstring2 is not null and (UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D)) or (cfloat < -6432.0) or (cboolean1 is not null and (cdouble = 988888.0D))) (type: boolean) + filterExpr: (((UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D) and cstring2 is not null) or (cfloat < -6432.0) or ((cdouble = 988888.0D) and cboolean1 is not null)) (type: boolean) Statistics: Num rows: 12288 Data size: 2983078 Basic stats: COMPLETE Column stats: COMPLETE TableScan Vectorization: native: true @@ -321,8 +321,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: SelectColumnIsNotNull(col 7:string), FilterDoubleColLessEqualDoubleScalar(col 13:double, val 12.503)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 11.998)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: SelectColumnIsNotNull(col 10:boolean), FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0))) - predicate: ((cboolean1 is not null and (cdouble = 988888.0D)) or (cfloat < -6432.0) or (cstring2 is not null and (UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D))) (type: boolean) + predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: FilterDoubleColLessEqualDoubleScalar(col 13:double, val 12.503)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 11.998)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double), SelectColumnIsNotNull(col 7:string)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0), SelectColumnIsNotNull(col 10:boolean))) + predicate: (((UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D) and cstring2 is not null) or ((cdouble = 988888.0D) and cboolean1 is not null) or (cfloat < -6432.0)) (type: boolean) Statistics: Num rows: 3059 Data size: 742850 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: ctimestamp1 (type: timestamp), cdouble (type: double), cboolean1 (type: boolean), cstring1 (type: string), cfloat (type: float), (- cdouble) (type: double), (-5638.15D - cdouble) (type: double), (cdouble * -257.0D) (type: double), (UDFToFloat(cint) + cfloat) (type: float), ((- cdouble) + UDFToDouble(cbigint)) (type: double), (- cdouble) (type: double), (-1.389 - cfloat) (type: float), (- cfloat) (type: float), ((-5638.15D - cdouble) + UDFToDouble((UDFToFloat(cint) + cfloat))) (type: double) diff --git ql/src/test/results/clientpositive/llap/vectorization_short_regress.q.out ql/src/test/results/clientpositive/llap/vectorization_short_regress.q.out index 19fd205106..38ca44b946 100644 --- ql/src/test/results/clientpositive/llap/vectorization_short_regress.q.out +++ ql/src/test/results/clientpositive/llap/vectorization_short_regress.q.out @@ -622,7 +622,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((ctimestamp1 = ctimestamp2) or (cfloat = 762.0) or (cstring1 = 'ss') or ((UDFToLong(csmallint) <= cbigint) and (cboolean2 = 1)) or (cboolean1 is not null and ctimestamp2 is not null and (cstring2 > 'a'))) (type: boolean) + filterExpr: ((ctimestamp1 = ctimestamp2) or (cfloat = 762.0) or (cstring1 = 'ss') or ((UDFToLong(csmallint) <= cbigint) and (cboolean2 = 1)) or ((cstring2 > 'a') and cboolean1 is not null and ctimestamp2 is not null)) (type: boolean) Statistics: Num rows: 12288 Data size: 3093170 Basic stats: COMPLETE Column stats: COMPLETE TableScan Vectorization: native: true @@ -630,8 +630,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterTimestampColEqualTimestampColumn(col 8:timestamp, col 9:timestamp), FilterDoubleColEqualDoubleScalar(col 4:float, val 762.0), FilterStringGroupColEqualStringScalar(col 6:string, val ss), FilterExprAndExpr(children: FilterLongColLessEqualLongColumn(col 1:bigint, col 3:bigint)(children: col 1:smallint), FilterLongColEqualLongScalar(col 11:boolean, val 1)), FilterExprAndExpr(children: SelectColumnIsNotNull(col 10:boolean), SelectColumnIsNotNull(col 9:timestamp), FilterStringGroupColGreaterStringScalar(col 7:string, val a))) - predicate: (((UDFToLong(csmallint) <= cbigint) and (cboolean2 = 1)) or (cboolean1 is not null and ctimestamp2 is not null and (cstring2 > 'a')) or (cfloat = 762.0) or (cstring1 = 'ss') or (ctimestamp1 = ctimestamp2)) (type: boolean) + predicateExpression: FilterExprOrExpr(children: FilterTimestampColEqualTimestampColumn(col 8:timestamp, col 9:timestamp), FilterDoubleColEqualDoubleScalar(col 4:float, val 762.0), FilterStringGroupColEqualStringScalar(col 6:string, val ss), FilterExprAndExpr(children: FilterLongColLessEqualLongColumn(col 1:bigint, col 3:bigint)(children: col 1:smallint), FilterLongColEqualLongScalar(col 11:boolean, val 1)), FilterExprAndExpr(children: FilterStringGroupColGreaterStringScalar(col 7:string, val a), SelectColumnIsNotNull(col 10:boolean), SelectColumnIsNotNull(col 9:timestamp))) + predicate: (((UDFToLong(csmallint) <= cbigint) and (cboolean2 = 1)) or ((cstring2 > 'a') and cboolean1 is not null and ctimestamp2 is not null) or (cfloat = 762.0) or (cstring1 = 'ss') or (ctimestamp1 = ctimestamp2)) (type: boolean) Statistics: Num rows: 11346 Data size: 2856120 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: cbigint (type: bigint), ctinyint (type: tinyint), csmallint (type: smallint), cint (type: int), cdouble (type: double), UDFToDouble(cbigint) (type: double), (UDFToDouble(cbigint) * UDFToDouble(cbigint)) (type: double), UDFToDouble(csmallint) (type: double), (UDFToDouble(csmallint) * UDFToDouble(csmallint)) (type: double), (cdouble * cdouble) (type: double) @@ -2219,7 +2219,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((UDFToInteger(csmallint) >= -257) and ((UDFToInteger(csmallint) = -6432) or ((UDFToDouble(cint) >= cdouble) and (UDFToInteger(ctinyint) <= cint)))) (type: boolean) + filterExpr: ((UDFToInteger(csmallint) >= -257) and (UDFToDouble(cint) >= cdouble) and (UDFToInteger(ctinyint) <= cint)) (type: boolean) Statistics: Num rows: 12288 Data size: 256884 Basic stats: COMPLETE Column stats: COMPLETE TableScan Vectorization: native: true @@ -2227,9 +2227,9 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprAndExpr(children: FilterLongColGreaterEqualLongScalar(col 1:int, val -257)(children: col 1:smallint), FilterExprOrExpr(children: FilterLongColEqualLongScalar(col 1:int, val -6432)(children: col 1:smallint), FilterExprAndExpr(children: FilterDoubleColGreaterEqualDoubleColumn(col 13:double, col 5:double)(children: CastLongToDouble(col 2:int) -> 13:double), FilterLongColLessEqualLongColumn(col 0:int, col 2:int)(children: col 0:tinyint)))) - predicate: (((UDFToInteger(csmallint) = -6432) or ((UDFToDouble(cint) >= cdouble) and (UDFToInteger(ctinyint) <= cint))) and (UDFToInteger(csmallint) >= -257)) (type: boolean) - Statistics: Num rows: 2503 Data size: 52344 Basic stats: COMPLETE Column stats: COMPLETE + predicateExpression: FilterExprAndExpr(children: FilterLongColGreaterEqualLongScalar(col 1:int, val -257)(children: col 1:smallint), FilterDoubleColGreaterEqualDoubleColumn(col 13:double, col 5:double)(children: CastLongToDouble(col 2:int) -> 13:double), FilterLongColLessEqualLongColumn(col 0:int, col 2:int)(children: col 0:tinyint)) + predicate: ((UDFToDouble(cint) >= cdouble) and (UDFToInteger(csmallint) >= -257) and (UDFToInteger(ctinyint) <= cint)) (type: boolean) + Statistics: Num rows: 455 Data size: 9548 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: csmallint (type: smallint), cbigint (type: bigint), ctinyint (type: tinyint), UDFToDouble(csmallint) (type: double), (UDFToDouble(csmallint) * UDFToDouble(csmallint)) (type: double), UDFToDouble(ctinyint) (type: double), (UDFToDouble(ctinyint) * UDFToDouble(ctinyint)) (type: double) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6 @@ -2238,7 +2238,7 @@ STAGE PLANS: native: true projectedOutputColumnNums: [1, 3, 0, 14, 17, 18, 21] selectExpressions: CastLongToDouble(col 1:smallint) -> 14:double, DoubleColMultiplyDoubleColumn(col 15:double, col 16:double)(children: CastLongToDouble(col 1:smallint) -> 15:double, CastLongToDouble(col 1:smallint) -> 16:double) -> 17:double, CastLongToDouble(col 0:tinyint) -> 18:double, DoubleColMultiplyDoubleColumn(col 19:double, col 20:double)(children: CastLongToDouble(col 0:tinyint) -> 19:double, CastLongToDouble(col 0:tinyint) -> 20:double) -> 21:double - Statistics: Num rows: 2503 Data size: 52344 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 455 Data size: 9548 Basic stats: COMPLETE Column stats: COMPLETE Group By Operator aggregations: sum(_col4), sum(_col3), count(_col0), sum(_col1), sum(_col6), sum(_col5), count(_col2), count() Group By Vectorization: @@ -2252,7 +2252,7 @@ STAGE PLANS: keys: _col0 (type: smallint) mode: hash outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 1251 Data size: 83804 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 227 Data size: 15212 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: smallint) sort order: + @@ -2261,7 +2261,7 @@ STAGE PLANS: className: VectorReduceSinkLongOperator native: true nativeConditionsMet: hive.vectorized.execution.reducesink.new.enabled IS true, hive.execution.engine tez IN [tez, spark] IS true, No PTF TopN IS true, No DISTINCT columns IS true, BinarySortableSerDe for keys IS true, LazyBinarySerDe for values IS true - Statistics: Num rows: 1251 Data size: 83804 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 227 Data size: 15212 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col1 (type: double), _col2 (type: double), _col3 (type: bigint), _col4 (type: bigint), _col5 (type: double), _col6 (type: double), _col7 (type: bigint), _col8 (type: bigint) Execution mode: vectorized, llap LLAP IO: all inputs @@ -2296,7 +2296,7 @@ STAGE PLANS: keys: KEY._col0 (type: smallint) mode: mergepartial outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 1251 Data size: 83804 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 227 Data size: 15212 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: _col0 (type: smallint), (UDFToInteger(_col0) % -75) (type: int), power(((_col1 - ((_col2 * _col2) / _col3)) / CASE WHEN ((_col3 = 1L)) THEN (null) ELSE ((_col3 - 1)) END), 0.5) (type: double), (-1.389 / CAST( _col0 AS decimal(5,0))) (type: decimal(10,9)), _col4 (type: bigint), (UDFToDouble((UDFToInteger(_col0) % -75)) / UDFToDouble(_col4)) (type: double), (- (UDFToInteger(_col0) % -75)) (type: int), ((_col5 - ((_col6 * _col6) / _col7)) / _col7) (type: double), (- (- (UDFToInteger(_col0) % -75))) (type: int), _col8 (type: bigint), (_col8 - -89010L) (type: bigint) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10 @@ -2305,7 +2305,7 @@ STAGE PLANS: native: true projectedOutputColumnNums: [0, 9, 17, 19, 4, 23, 25, 29, 32, 8, 33] selectExpressions: LongColModuloLongScalar(col 0:int, val -75)(children: col 0:smallint) -> 9:int, FuncPowerDoubleToDouble(col 16:double)(children: DoubleColDivideLongColumn(col 12:double, col 15:bigint)(children: DoubleColSubtractDoubleColumn(col 1:double, col 11:double)(children: DoubleColDivideLongColumn(col 10:double, col 3:bigint)(children: DoubleColMultiplyDoubleColumn(col 2:double, col 2:double) -> 10:double) -> 11:double) -> 12:double, IfExprNullCondExpr(col 13:boolean, null, col 14:bigint)(children: LongColEqualLongScalar(col 3:bigint, val 1) -> 13:boolean, LongColSubtractLongScalar(col 3:bigint, val 1) -> 14:bigint) -> 15:bigint) -> 16:double) -> 17:double, DecimalScalarDivideDecimalColumn(val -1.389, col 18:decimal(5,0))(children: CastLongToDecimal(col 0:smallint) -> 18:decimal(5,0)) -> 19:decimal(10,9), DoubleColDivideDoubleColumn(col 21:double, col 22:double)(children: CastLongToDouble(col 20:int)(children: LongColModuloLongScalar(col 0:int, val -75)(children: col 0:smallint) -> 20:int) -> 21:double, CastLongToDouble(col 4:bigint) -> 22:double) -> 23:double, LongColUnaryMinus(col 24:int)(children: LongColModuloLongScalar(col 0:int, val -75)(children: col 0:smallint) -> 24:int) -> 25:int, DoubleColDivideLongColumn(col 28:double, col 7:bigint)(children: DoubleColSubtractDoubleColumn(col 5:double, col 27:double)(children: DoubleColDivideLongColumn(col 26:double, col 7:bigint)(children: DoubleColMultiplyDoubleColumn(col 6:double, col 6:double) -> 26:double) -> 27:double) -> 28:double) -> 29:double, LongColUnaryMinus(col 31:int)(children: LongColUnaryMinus(col 30:int)(children: LongColModuloLongScalar(col 0:int, val -75)(children: col 0:smallint) -> 30:int) -> 31:int) -> 32:int, LongColSubtractLongScalar(col 8:bigint, val -89010) -> 33:bigint - Statistics: Num rows: 1251 Data size: 218912 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 227 Data size: 39728 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator key expressions: _col0 (type: smallint), _col1 (type: int), _col2 (type: double), _col3 (type: decimal(10,9)), _col4 (type: bigint), _col5 (type: double), _col6 (type: int), _col7 (type: double), _col8 (type: int), _col9 (type: bigint), _col10 (type: bigint) sort order: +++++++++++ @@ -2313,7 +2313,7 @@ STAGE PLANS: className: VectorReduceSinkObjectHashOperator native: true nativeConditionsMet: hive.vectorized.execution.reducesink.new.enabled IS true, hive.execution.engine tez IN [tez, spark] IS true, No PTF TopN IS true, No DISTINCT columns IS true, BinarySortableSerDe for keys IS true, LazyBinarySerDe for values IS true - Statistics: Num rows: 1251 Data size: 218912 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 227 Data size: 39728 Basic stats: COMPLETE Column stats: COMPLETE TopN Hash Memory Usage: 0.1 Reducer 3 Execution mode: vectorized, llap @@ -2331,7 +2331,7 @@ STAGE PLANS: className: VectorSelectOperator native: true projectedOutputColumnNums: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] - Statistics: Num rows: 1251 Data size: 218912 Basic stats: COMPLETE Column stats: COMPLETE + Statistics: Num rows: 227 Data size: 39728 Basic stats: COMPLETE Column stats: COMPLETE Limit Number of rows: 20 Limit Vectorization: diff --git ql/src/test/results/clientpositive/llap/vectorized_casts.q.out ql/src/test/results/clientpositive/llap/vectorized_casts.q.out index d1a9620186..0d21c2ac8a 100644 --- ql/src/test/results/clientpositive/llap/vectorized_casts.q.out +++ ql/src/test/results/clientpositive/llap/vectorized_casts.q.out @@ -169,7 +169,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((cbigint % 250) = 0) (type: boolean) + filterExpr: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 12288 Data size: 1684250 Basic stats: COMPLETE Column stats: COMPLETE TableScan Vectorization: native: true @@ -179,7 +179,7 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: FilterLongColEqualLongScalar(col 13:bigint, val 0)(children: LongColModuloLongScalar(col 3:bigint, val 250) -> 13:bigint) - predicate: ((cbigint % 250) = 0) (type: boolean) + predicate: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 6144 Data size: 842180 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: UDFToBoolean(ctinyint) (type: boolean), UDFToBoolean(csmallint) (type: boolean), UDFToBoolean(cint) (type: boolean), UDFToBoolean(cbigint) (type: boolean), UDFToBoolean(cfloat) (type: boolean), UDFToBoolean(cdouble) (type: boolean), cboolean1 (type: boolean), UDFToBoolean((cbigint * 0L)) (type: boolean), UDFToBoolean(ctimestamp1) (type: boolean), UDFToBoolean(cstring1) (type: boolean), UDFToInteger(ctinyint) (type: int), UDFToInteger(csmallint) (type: int), cint (type: int), UDFToInteger(cbigint) (type: int), UDFToInteger(cfloat) (type: int), UDFToInteger(cdouble) (type: int), UDFToInteger(cboolean1) (type: int), UDFToInteger(ctimestamp1) (type: int), UDFToInteger(cstring1) (type: int), UDFToInteger(substr(cstring1, 1, 1)) (type: int), UDFToByte(cfloat) (type: tinyint), UDFToShort(cfloat) (type: smallint), UDFToLong(cfloat) (type: bigint), UDFToDouble(ctinyint) (type: double), UDFToDouble(csmallint) (type: double), UDFToDouble(cint) (type: double), UDFToDouble(cbigint) (type: double), UDFToDouble(cfloat) (type: double), cdouble (type: double), UDFToDouble(cboolean1) (type: double), UDFToDouble(ctimestamp1) (type: double), UDFToDouble(cstring1) (type: double), UDFToDouble(substr(cstring1, 1, 1)) (type: double), UDFToFloat(cint) (type: float), UDFToFloat(cdouble) (type: float), CAST( ctinyint AS TIMESTAMP) (type: timestamp), CAST( csmallint AS TIMESTAMP) (type: timestamp), CAST( cint AS TIMESTAMP) (type: timestamp), CAST( cbigint AS TIMESTAMP) (type: timestamp), CAST( cfloat AS TIMESTAMP) (type: timestamp), CAST( cdouble AS TIMESTAMP) (type: timestamp), CAST( cboolean1 AS TIMESTAMP) (type: timestamp), CAST( (cbigint * 0L) AS TIMESTAMP) (type: timestamp), CAST( CAST( ctimestamp1 AS DATE) AS TIMESTAMP) (type: timestamp), ctimestamp1 (type: timestamp), CAST( cstring1 AS TIMESTAMP) (type: timestamp), CAST( substr(cstring1, 1, 1) AS TIMESTAMP) (type: timestamp), CAST( ctinyint AS STRING) (type: string), CAST( csmallint AS STRING) (type: string), CAST( cint AS STRING) (type: string), CAST( cbigint AS STRING) (type: string), CAST( cfloat AS STRING) (type: string), CAST( cdouble AS STRING) (type: string), CAST( cboolean1 AS STRING) (type: string), CAST( (cbigint * 0L) AS STRING) (type: string), CAST( ctimestamp1 AS STRING) (type: string), cstring1 (type: string), CAST( CAST( cstring1 AS CHAR(10)) AS STRING) (type: string), CAST( CAST( cstring1 AS varchar(10)) AS STRING) (type: string), UDFToFloat(UDFToInteger(cfloat)) (type: float), UDFToDouble((cint * 2)) (type: double), CAST( sin(cfloat) AS STRING) (type: string), (UDFToDouble(UDFToFloat(cint)) + UDFToDouble(cboolean1)) (type: double) diff --git ql/src/test/results/clientpositive/llap/vectorized_math_funcs.q.out ql/src/test/results/clientpositive/llap/vectorized_math_funcs.q.out index 63b42fde3a..26472f7f1d 100644 --- ql/src/test/results/clientpositive/llap/vectorized_math_funcs.q.out +++ ql/src/test/results/clientpositive/llap/vectorized_math_funcs.q.out @@ -123,7 +123,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: (((cbigint % 500) = 0) and (sin(cfloat) >= -1.0D)) (type: boolean) + filterExpr: (((cbigint % 500L) = 0) and (sin(cfloat) >= -1.0D)) (type: boolean) Statistics: Num rows: 12288 Data size: 293580 Basic stats: COMPLETE Column stats: COMPLETE TableScan Vectorization: native: true @@ -132,7 +132,7 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: FilterExprAndExpr(children: FilterLongColEqualLongScalar(col 13:bigint, val 0)(children: LongColModuloLongScalar(col 3:bigint, val 500) -> 13:bigint), FilterDoubleColGreaterEqualDoubleScalar(col 14:double, val -1.0)(children: FuncSinDoubleToDouble(col 4:float) -> 14:double)) - predicate: (((cbigint % 500) = 0) and (sin(cfloat) >= -1.0D)) (type: boolean) + predicate: (((cbigint % 500L) = 0) and (sin(cfloat) >= -1.0D)) (type: boolean) Statistics: Num rows: 2048 Data size: 48960 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: cdouble (type: double), round(cdouble, 2) (type: double), floor(cdouble) (type: bigint), ceil(cdouble) (type: bigint), rand() (type: double), rand(98007) (type: double), exp(ln(cdouble)) (type: double), ln(cdouble) (type: double), ln(cfloat) (type: double), log10(cdouble) (type: double), log2(cdouble) (type: double), log2((cdouble - 15601.0D)) (type: double), log2(cfloat) (type: double), log2(cbigint) (type: double), log2(cint) (type: double), log2(csmallint) (type: double), log2(ctinyint) (type: double), log(2, cdouble) (type: double), power(log2(cdouble), 2) (type: double), power(log2(cdouble), 2) (type: double), sqrt(cdouble) (type: double), sqrt(cbigint) (type: double), bin(cbigint) (type: string), hex(cdouble) (type: string), conv(cbigint, 10, 16) (type: string), abs(cdouble) (type: double), abs(ctinyint) (type: int), (cint pmod 3) (type: int), sin(cdouble) (type: double), asin(cdouble) (type: double), cos(cdouble) (type: double), acos(cdouble) (type: double), atan(cdouble) (type: double), degrees(cdouble) (type: double), radians(cdouble) (type: double), cdouble (type: double), cbigint (type: bigint), (- cdouble) (type: double), sign(cdouble) (type: double), sign(cbigint) (type: double), cos(((- sin(log(cdouble))) + 3.14159D)) (type: double) diff --git ql/src/test/results/clientpositive/llap/vectorized_string_funcs.q.out ql/src/test/results/clientpositive/llap/vectorized_string_funcs.q.out index 7a5073577e..1d3fa093a3 100644 --- ql/src/test/results/clientpositive/llap/vectorized_string_funcs.q.out +++ ql/src/test/results/clientpositive/llap/vectorized_string_funcs.q.out @@ -63,10 +63,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: (((cbigint % 237) = 0) and (length(substr(cstring1, 1, 2)) <= 2) and (cstring1 like '%')) (type: boolean) + filterExpr: (((cbigint % 237L) = 0) and (length(substr(cstring1, 1, 2)) <= 2) and (cstring1 like '%')) (type: boolean) Statistics: Num rows: 12288 Data size: 1816546 Basic stats: COMPLETE Column stats: COMPLETE Filter Operator - predicate: (((cbigint % 237) = 0) and (cstring1 like '%') and (length(substr(cstring1, 1, 2)) <= 2)) (type: boolean) + predicate: (((cbigint % 237L) = 0) and (cstring1 like '%') and (length(substr(cstring1, 1, 2)) <= 2)) (type: boolean) Statistics: Num rows: 1024 Data size: 151470 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: substr(cstring1, 1, 2) (type: string), substr(cstring1, 2) (type: string), lower(cstring1) (type: string), upper(cstring1) (type: string), upper(cstring1) (type: string), length(cstring1) (type: int), trim(cstring1) (type: string), ltrim(cstring1) (type: string), rtrim(cstring1) (type: string), concat(cstring1, cstring2) (type: string), concat('>', cstring1) (type: string), concat(cstring1, '<') (type: string), concat(substr(cstring1, 1, 2), substr(cstring2, 1, 2)) (type: string) diff --git ql/src/test/results/clientpositive/llap/vectorized_timestamp_ints_casts.q.out ql/src/test/results/clientpositive/llap/vectorized_timestamp_ints_casts.q.out index c52e3b9e94..43edbcff24 100644 --- ql/src/test/results/clientpositive/llap/vectorized_timestamp_ints_casts.q.out +++ ql/src/test/results/clientpositive/llap/vectorized_timestamp_ints_casts.q.out @@ -55,7 +55,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((cbigint % 250) = 0) (type: boolean) + filterExpr: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 12288 Data size: 1684250 Basic stats: COMPLETE Column stats: COMPLETE TableScan Vectorization: native: true @@ -64,7 +64,7 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: FilterLongColEqualLongScalar(col 13:bigint, val 0)(children: LongColModuloLongScalar(col 3:bigint, val 250) -> 13:bigint) - predicate: ((cbigint % 250) = 0) (type: boolean) + predicate: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 6144 Data size: 842180 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: CAST( ctinyint AS TIMESTAMP) (type: timestamp), CAST( csmallint AS TIMESTAMP) (type: timestamp), CAST( cint AS TIMESTAMP) (type: timestamp), CAST( cbigint AS TIMESTAMP) (type: timestamp), CAST( cfloat AS TIMESTAMP) (type: timestamp), CAST( cdouble AS TIMESTAMP) (type: timestamp), CAST( cboolean1 AS TIMESTAMP) (type: timestamp), CAST( (cbigint * 0L) AS TIMESTAMP) (type: timestamp), ctimestamp1 (type: timestamp), CAST( cstring1 AS TIMESTAMP) (type: timestamp), CAST( substr(cstring1, 1, 1) AS TIMESTAMP) (type: timestamp) @@ -224,7 +224,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((cbigint % 250) = 0) (type: boolean) + filterExpr: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 12288 Data size: 1684250 Basic stats: COMPLETE Column stats: COMPLETE TableScan Vectorization: native: true @@ -233,7 +233,7 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: FilterLongColEqualLongScalar(col 13:bigint, val 0)(children: LongColModuloLongScalar(col 3:bigint, val 250) -> 13:bigint) - predicate: ((cbigint % 250) = 0) (type: boolean) + predicate: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 6144 Data size: 842180 Basic stats: COMPLETE Column stats: COMPLETE Select Operator expressions: CAST( ctinyint AS TIMESTAMP) (type: timestamp), CAST( csmallint AS TIMESTAMP) (type: timestamp), CAST( cint AS TIMESTAMP) (type: timestamp), CAST( cbigint AS TIMESTAMP) (type: timestamp), CAST( cfloat AS TIMESTAMP) (type: timestamp), CAST( cdouble AS TIMESTAMP) (type: timestamp), CAST( cboolean1 AS TIMESTAMP) (type: timestamp), CAST( (cbigint * 0L) AS TIMESTAMP) (type: timestamp), ctimestamp1 (type: timestamp), CAST( cstring1 AS TIMESTAMP) (type: timestamp), CAST( substr(cstring1, 1, 1) AS TIMESTAMP) (type: timestamp) diff --git ql/src/test/results/clientpositive/macro.q.out ql/src/test/results/clientpositive/macro.q.out index c126a14d67..e4c35107f0 100644 --- ql/src/test/results/clientpositive/macro.q.out +++ ql/src/test/results/clientpositive/macro.q.out @@ -49,7 +49,7 @@ POSTHOOK: query: EXPLAIN EXTENDED SELECT SIGMOID(2) FROM src LIMIT 1 POSTHOOK: type: QUERY POSTHOOK: Input: default@src #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST(0.8807970779778823 AS DOUBLE) AS `$f0` +OPTIMIZED SQL: SELECT CAST(0.8807970779778823 AS DOUBLE) AS `_o__c0` FROM `default`.`src` LIMIT 1 STAGE DEPENDENCIES: @@ -130,7 +130,7 @@ POSTHOOK: query: EXPLAIN EXTENDED SELECT FIXED_NUMBER() + 1 FROM src LIMIT 1 POSTHOOK: type: QUERY POSTHOOK: Input: default@src #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST(2 AS INTEGER) AS `$f0` +OPTIMIZED SQL: SELECT CAST(2 AS INTEGER) AS `_o__c0` FROM `default`.`src` LIMIT 1 STAGE DEPENDENCIES: @@ -238,7 +238,7 @@ POSTHOOK: query: EXPLAIN EXTENDED SELECT SIMPLE_ADD(1, 9) FROM src LIMIT 1 POSTHOOK: type: QUERY POSTHOOK: Input: default@src #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST(10 AS INTEGER) AS `$f0` +OPTIMIZED SQL: SELECT CAST(10 AS INTEGER) AS `_o__c0` FROM `default`.`src` LIMIT 1 STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/mergejoin.q.out ql/src/test/results/clientpositive/mergejoin.q.out index 2108434f27..5c0498cb58 100644 --- ql/src/test/results/clientpositive/mergejoin.q.out +++ ql/src/test/results/clientpositive/mergejoin.q.out @@ -3358,7 +3358,7 @@ POSTHOOK: Input: default@tab_part_n10@ds=2008-04-08 #### A masked pattern was here #### NULL NULL NULL 98 val_98 2008-04-08 NULL NULL NULL 98 val_98 2008-04-08 -Warning: Shuffle Join JOIN[12][tables = [$hdt$_0, $hdt$_1, $hdt$_2]] in Stage 'Stage-1:MAPRED' is a cross product +Warning: Shuffle Join JOIN[11][tables = [$hdt$_0, $hdt$_1]] in Stage 'Stage-1:MAPRED' is a cross product PREHOOK: query: select * from (select * from tab_n9 where tab_n9.key = 0)a full outer join @@ -3927,8 +3927,7 @@ NULL NULL NULL NULL NULL NULL 97 val_97 2008-04-08 NULL NULL NULL NULL NULL NULL 97 val_97 2008-04-08 NULL NULL NULL NULL NULL NULL 98 val_98 2008-04-08 NULL NULL NULL NULL NULL NULL 98 val_98 2008-04-08 -Warning: Shuffle Join JOIN[14][tables = [$hdt$_0, $hdt$_1]] in Stage 'Stage-1:MAPRED' is a cross product -Warning: Shuffle Join JOIN[10][tables = [$hdt$_1, $hdt$_2]] in Stage 'Stage-2:MAPRED' is a cross product +Warning: Shuffle Join JOIN[10][tables = [$hdt$_0, $hdt$_1]] in Stage 'Stage-1:MAPRED' is a cross product PREHOOK: query: select * from (select * from tab_n9 where tab_n9.key = 0)a join diff --git ql/src/test/results/clientpositive/optimize_filter_literal.q.out ql/src/test/results/clientpositive/optimize_filter_literal.q.out index 3e8ca3a7f9..4ef0f51375 100644 --- ql/src/test/results/clientpositive/optimize_filter_literal.q.out +++ ql/src/test/results/clientpositive/optimize_filter_literal.q.out @@ -136,7 +136,7 @@ POSTHOOK: Input: default@tab_n14@ds=2008-04-08 POSTHOOK: Output: default@tab_n14 POSTHOOK: Output: default@tab_n14@ds=2008-04-08 #### A masked pattern was here #### -Warning: Shuffle Join JOIN[12][tables = [$hdt$_0, $hdt$_1, $hdt$_2]] in Stage 'Stage-1:MAPRED' is a cross product +Warning: Shuffle Join JOIN[11][tables = [$hdt$_0, $hdt$_1]] in Stage 'Stage-1:MAPRED' is a cross product PREHOOK: query: select * from (select * from tab_n14 where tab_n14.key = 0)a full outer join diff --git ql/src/test/results/clientpositive/order3.q.out ql/src/test/results/clientpositive/order3.q.out index b090d6fb18..f0beebe436 100644 --- ql/src/test/results/clientpositive/order3.q.out +++ ql/src/test/results/clientpositive/order3.q.out @@ -288,23 +288,27 @@ STAGE PLANS: Execution mode: vectorized Reduce Operator Tree: Select Operator - expressions: KEY.reducesinkkey0 (type: int), VALUE._col0 (type: bigint), 'AAA' (type: string) - outputColumnNames: _col0, _col1, _col2 + expressions: KEY.reducesinkkey0 (type: int), VALUE._col0 (type: bigint) + outputColumnNames: _col0, _col1 Statistics: Num rows: 7 Data size: 70 Basic stats: COMPLETE Column stats: NONE Limit Number of rows: 3 Statistics: Num rows: 3 Data size: 30 Basic stats: COMPLETE Column stats: NONE - File Output Operator - compressed: false + Select Operator + expressions: _col0 (type: int), _col1 (type: bigint), 'AAA' (type: string) + outputColumnNames: _col0, _col1, _col2 Statistics: Num rows: 3 Data size: 30 Basic stats: COMPLETE Column stats: NONE - table: - input format: org.apache.hadoop.mapred.SequenceFileInputFormat - output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat - serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + File Output Operator + compressed: false + Statistics: Num rows: 3 Data size: 30 Basic stats: COMPLETE Column stats: NONE + table: + input format: org.apache.hadoop.mapred.SequenceFileInputFormat + output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat + serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe Stage: Stage-0 Fetch Operator - limit: 3 + limit: -1 Processor Tree: ListSink diff --git ql/src/test/results/clientpositive/parquet_vectorization_0.q.out ql/src/test/results/clientpositive/parquet_vectorization_0.q.out index 3698e9d95c..ec9ae03a0f 100644 --- ql/src/test/results/clientpositive/parquet_vectorization_0.q.out +++ ql/src/test/results/clientpositive/parquet_vectorization_0.q.out @@ -30572,6 +30572,9 @@ POSTHOOK: query: explain extended select * from alltypesparquet where POSTHOOK: type: QUERY POSTHOOK: Input: default@alltypesparquet #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `ctinyint`, `csmallint`, `cint`, `cbigint`, `cfloat`, `cdouble`, `cstring1`, `cstring2`, `ctimestamp1`, `ctimestamp2`, `cboolean1`, `cboolean2` +FROM `default`.`alltypesparquet` +WHERE ROW(`cint`, `cfloat`) IN (ROW(49, 3.5), ROW(47, 2.09), ROW(45, 3.02)) STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -30808,6 +30811,11 @@ POSTHOOK: query: explain extended select count(*),cstring1 from alltypesparquet POSTHOOK: type: QUERY POSTHOOK: Input: default@alltypesparquet #### A masked pattern was here #### +OPTIMIZED SQL: SELECT COUNT(*) AS `_o__c0`, `cstring1` +FROM `default`.`alltypesparquet` +WHERE `cstring1` IN ('biology', 'history', 'topology') +GROUP BY `cstring1` +ORDER BY `cstring1` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-2 depends on stages: Stage-1 diff --git ql/src/test/results/clientpositive/parquet_vectorization_5.q.out ql/src/test/results/clientpositive/parquet_vectorization_5.q.out index baee2c80a9..594b5f5c63 100644 --- ql/src/test/results/clientpositive/parquet_vectorization_5.q.out +++ ql/src/test/results/clientpositive/parquet_vectorization_5.q.out @@ -56,7 +56,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesparquet - filterExpr: ((cboolean2 is not null and (cstring1 like '%b%')) or ((UDFToDouble(ctinyint) = cdouble) and ctimestamp2 is not null and (cstring2 like 'a'))) (type: boolean) + filterExpr: (((cstring1 like '%b%') and cboolean2 is not null) or ((UDFToDouble(ctinyint) = cdouble) and (cstring2 like 'a') and ctimestamp2 is not null)) (type: boolean) Statistics: Num rows: 12288 Data size: 147456 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -64,8 +64,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: SelectColumnIsNotNull(col 11:boolean), FilterStringColLikeStringScalar(col 6:string, pattern %b%)), FilterExprAndExpr(children: FilterDoubleColEqualDoubleColumn(col 13:double, col 5:double)(children: CastLongToDouble(col 0:tinyint) -> 13:double), SelectColumnIsNotNull(col 9:timestamp), FilterStringColLikeStringScalar(col 7:string, pattern a))) - predicate: (((UDFToDouble(ctinyint) = cdouble) and ctimestamp2 is not null and (cstring2 like 'a')) or (cboolean2 is not null and (cstring1 like '%b%'))) (type: boolean) + predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: FilterStringColLikeStringScalar(col 6:string, pattern %b%), SelectColumnIsNotNull(col 11:boolean)), FilterExprAndExpr(children: FilterDoubleColEqualDoubleColumn(col 13:double, col 5:double)(children: CastLongToDouble(col 0:tinyint) -> 13:double), FilterStringColLikeStringScalar(col 7:string, pattern a), SelectColumnIsNotNull(col 9:timestamp))) + predicate: (((UDFToDouble(ctinyint) = cdouble) and (cstring2 like 'a') and ctimestamp2 is not null) or ((cstring1 like '%b%') and cboolean2 is not null)) (type: boolean) Statistics: Num rows: 9216 Data size: 110592 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: ctinyint (type: tinyint), csmallint (type: smallint), cint (type: int) diff --git ql/src/test/results/clientpositive/parquet_vectorization_8.q.out ql/src/test/results/clientpositive/parquet_vectorization_8.q.out index b0c3397e39..37871d96e5 100644 --- ql/src/test/results/clientpositive/parquet_vectorization_8.q.out +++ ql/src/test/results/clientpositive/parquet_vectorization_8.q.out @@ -66,7 +66,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesparquet - filterExpr: ((cstring2 is not null and (UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D)) or (cfloat < -6432.0) or (cboolean1 is not null and (cdouble = 988888.0D))) (type: boolean) + filterExpr: (((UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D) and cstring2 is not null) or (cfloat < -6432.0) or ((cdouble = 988888.0D) and cboolean1 is not null)) (type: boolean) Statistics: Num rows: 12288 Data size: 147456 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -74,8 +74,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: SelectColumnIsNotNull(col 7:string), FilterDoubleColLessEqualDoubleScalar(col 13:double, val 10.0)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 16.0)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: SelectColumnIsNotNull(col 10:boolean), FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0))) - predicate: ((cboolean1 is not null and (cdouble = 988888.0D)) or (cfloat < -6432.0) or (cstring2 is not null and (UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D))) (type: boolean) + predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: FilterDoubleColLessEqualDoubleScalar(col 13:double, val 10.0)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 16.0)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double), SelectColumnIsNotNull(col 7:string)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0), SelectColumnIsNotNull(col 10:boolean))) + predicate: (((UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D) and cstring2 is not null) or ((cdouble = 988888.0D) and cboolean1 is not null) or (cfloat < -6432.0)) (type: boolean) Statistics: Num rows: 12288 Data size: 147456 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: ctimestamp1 (type: timestamp), cdouble (type: double), cboolean1 (type: boolean), cstring1 (type: string), cfloat (type: float), (- cdouble) (type: double), (-5638.15D - cdouble) (type: double), (cdouble * -257.0D) (type: double), (UDFToFloat(cint) + cfloat) (type: float), ((- cdouble) + UDFToDouble(cbigint)) (type: double), (- cdouble) (type: double), (-1.389 - cfloat) (type: float), (- cfloat) (type: float), ((-5638.15D - cdouble) + UDFToDouble((UDFToFloat(cint) + cfloat))) (type: double) @@ -272,7 +272,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesparquet - filterExpr: ((cstring2 is not null and (UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D)) or (cfloat < -6432.0) or (cboolean1 is not null and (cdouble = 988888.0D))) (type: boolean) + filterExpr: (((UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D) and cstring2 is not null) or (cfloat < -6432.0) or ((cdouble = 988888.0D) and cboolean1 is not null)) (type: boolean) Statistics: Num rows: 12288 Data size: 147456 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -280,8 +280,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: SelectColumnIsNotNull(col 7:string), FilterDoubleColLessEqualDoubleScalar(col 13:double, val 12.503)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 11.998)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: SelectColumnIsNotNull(col 10:boolean), FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0))) - predicate: ((cboolean1 is not null and (cdouble = 988888.0D)) or (cfloat < -6432.0) or (cstring2 is not null and (UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D))) (type: boolean) + predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: FilterDoubleColLessEqualDoubleScalar(col 13:double, val 12.503)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 11.998)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double), SelectColumnIsNotNull(col 7:string)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0), SelectColumnIsNotNull(col 10:boolean))) + predicate: (((UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D) and cstring2 is not null) or ((cdouble = 988888.0D) and cboolean1 is not null) or (cfloat < -6432.0)) (type: boolean) Statistics: Num rows: 12288 Data size: 147456 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: ctimestamp1 (type: timestamp), cdouble (type: double), cboolean1 (type: boolean), cstring1 (type: string), cfloat (type: float), (- cdouble) (type: double), (-5638.15D - cdouble) (type: double), (cdouble * -257.0D) (type: double), (UDFToFloat(cint) + cfloat) (type: float), ((- cdouble) + UDFToDouble(cbigint)) (type: double), (- cdouble) (type: double), (-1.389 - cfloat) (type: float), (- cfloat) (type: float), ((-5638.15D - cdouble) + UDFToDouble((UDFToFloat(cint) + cfloat))) (type: double) diff --git ql/src/test/results/clientpositive/pcr.q.out ql/src/test/results/clientpositive/pcr.q.out index d71ef675d5..6307cdd19a 100644 --- ql/src/test/results/clientpositive/pcr.q.out +++ ql/src/test/results/clientpositive/pcr.q.out @@ -1522,6 +1522,11 @@ POSTHOOK: Input: default@pcr_t1 POSTHOOK: Input: default@pcr_t1@ds=2000-04-08 POSTHOOK: Input: default@pcr_t1@ds=2000-04-09 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT CAST(14 AS INTEGER) AS `key`, `value` +FROM (SELECT `value` +FROM `default`.`pcr_t1` +WHERE `ds` IN ('2000-04-08', '2000-04-09') AND `key` = 14 +ORDER BY `value`) AS `t1` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1712,6 +1717,10 @@ POSTHOOK: Input: default@pcr_t1 POSTHOOK: Input: default@pcr_t1@ds=2000-04-08 POSTHOOK: Input: default@pcr_t1@ds=2000-04-09 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value` +FROM `default`.`pcr_t1` +WHERE `ds` IN ('2000-04-08', '2000-04-09') +ORDER BY `key`, `value` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1942,7 +1951,7 @@ POSTHOOK: Input: default@pcr_t1@ds=2000-04-10 #### A masked pattern was here #### OPTIMIZED SQL: SELECT `key`, `value` FROM `default`.`pcr_t1` -WHERE `ds` >= '2000-04-08' OR `ds` IS NOT NULL +WHERE `ds` >= '2000-04-08' OR `ds` < '2000-04-10' ORDER BY `key`, `value` STAGE DEPENDENCIES: Stage-1 is a root stage @@ -1954,7 +1963,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: pcr_t1 - filterExpr: ((ds >= '2000-04-08') or ds is not null) (type: boolean) + filterExpr: ((ds >= '2000-04-08') or (ds < '2000-04-10')) (type: boolean) Statistics: Num rows: 60 Data size: 480 Basic stats: COMPLETE Column stats: NONE GatherStats: false Select Operator @@ -2241,6 +2250,10 @@ POSTHOOK: Input: default@pcr_t1 POSTHOOK: Input: default@pcr_t1@ds=2000-04-08 POSTHOOK: Input: default@pcr_t1@ds=2000-04-09 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, `ds` +FROM `default`.`pcr_t1` +WHERE ROW(`key`, `ds`) IN (ROW(1, '2000-04-08'), ROW(2, '2000-04-09')) +ORDER BY `key`, `value`, `ds` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -2430,7 +2443,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@pcr_t1 POSTHOOK: Input: default@pcr_t1@ds=2000-04-08 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS STRING) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-08' AS STRING) AS `ds1` +OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds1` FROM (SELECT * FROM (SELECT `key`, `value` FROM `default`.`pcr_t1` @@ -2710,7 +2723,7 @@ POSTHOOK: Input: default@pcr_t1 POSTHOOK: Input: default@pcr_t1@ds=2000-04-08 POSTHOOK: Input: default@pcr_t1@ds=2000-04-09 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS STRING) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-09' AS STRING) AS `ds1` +OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-09' AS VARCHAR(65536)) AS `ds1` FROM (SELECT * FROM (SELECT `key`, `value` FROM `default`.`pcr_t1` @@ -5052,6 +5065,11 @@ POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=11 POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds`, `hr` +FROM (SELECT `key`, `value`, `hr` +FROM `default`.`srcpart` +WHERE `hr` IN ('11', '12') AND `ds` = '2008-04-08' AND `key` = 11 +ORDER BY `key`, `hr`) AS `t1` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -5247,7 +5265,7 @@ POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=11 POSTHOOK: Input: default@srcpart@ds=2008-04-09/hr=11 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `key`, `value`, `ds`, CAST('11' AS STRING) AS `hr` +OPTIMIZED SQL: SELECT `key`, `value`, `ds`, CAST('11' AS VARCHAR(65536)) AS `hr` FROM (SELECT `key`, `value`, `ds` FROM `default`.`srcpart` WHERE `hr` = '11' AND `key` = 11 diff --git ql/src/test/results/clientpositive/pcs.q.out ql/src/test/results/clientpositive/pcs.q.out index 225624eb97..45bfc6f4ca 100644 --- ql/src/test/results/clientpositive/pcs.q.out +++ ql/src/test/results/clientpositive/pcs.q.out @@ -98,6 +98,10 @@ POSTHOOK: Input: default@pcs_t1 POSTHOOK: Input: default@pcs_t1@ds=2000-04-08 POSTHOOK: Input: default@pcs_t1@ds=2000-04-09 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, `ds` +FROM `default`.`pcs_t1` +WHERE ROW(`key`, `ds`) IN (ROW(1, '2000-04-08'), ROW(2, '2000-04-09')) +ORDER BY `key`, `value`, `ds` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -289,6 +293,9 @@ POSTHOOK: Input: default@pcs_t1 POSTHOOK: Input: default@pcs_t1@ds=2000-04-08 POSTHOOK: Input: default@pcs_t1@ds=2000-04-09 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `ds` +FROM `default`.`pcs_t1` +WHERE ROW(`key`, `ds`) IN (ROW(1, '2000-04-08'), ROW(2, '2000-04-09')) STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -467,6 +474,9 @@ POSTHOOK: Input: default@pcs_t1 POSTHOOK: Input: default@pcs_t1@ds=2000-04-08 POSTHOOK: Input: default@pcs_t1@ds=2000-04-09 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `ds` +FROM `default`.`pcs_t1` +WHERE ROW(`ds`, `key` + 2) IN (ROW('2000-04-08', 3), ROW('2000-04-09', 4)) STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -866,6 +876,9 @@ POSTHOOK: Input: default@pcs_t1 POSTHOOK: Input: default@pcs_t1@ds=2000-04-08 POSTHOOK: Input: default@pcs_t1@ds=2000-04-09 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `ds` +FROM `default`.`pcs_t1` +WHERE ROW(`ds`, `key` + `key`) IN (ROW('2000-04-08', 1), ROW('2000-04-09', 2)) STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1272,9 +1285,9 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@pcs_t1 POSTHOOK: Input: default@pcs_t1@ds=2000-04-08 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('2000-04-08' AS STRING) AS `$f0` +OPTIMIZED SQL: SELECT `ds` FROM `default`.`pcs_t1` -WHERE `ds` = '2000-04-08' +WHERE `ds` = '2000-04-08' IS TRUE STAGE DEPENDENCIES: Stage-0 is a root stage @@ -1332,11 +1345,11 @@ STAGE PLANS: Processor Tree: TableScan alias: pcs_t1 - filterExpr: (ds = '2000-04-08') (type: boolean) + filterExpr: true is true (type: boolean) Statistics: Num rows: 20 Data size: 160 Basic stats: COMPLETE Column stats: NONE GatherStats: false Select Operator - expressions: '2000-04-08' (type: string) + expressions: ds (type: string) outputColumnNames: _col0 Statistics: Num rows: 20 Data size: 160 Basic stats: COMPLETE Column stats: NONE ListSink @@ -1383,6 +1396,9 @@ POSTHOOK: Input: default@pcs_t1 POSTHOOK: Input: default@pcs_t1@ds=2000-04-08 POSTHOOK: Input: default@pcs_t1@ds=2000-04-09 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `ds` +FROM `default`.`pcs_t1` +WHERE ROW(`ds`, `key`, RAND(100)) IN (ROW('2000-04-08', 1, 0.2), ROW('2000-04-09', 2, 0.3)) STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1549,6 +1565,9 @@ POSTHOOK: Input: default@pcs_t1@ds=2000-04-08 POSTHOOK: Input: default@pcs_t1@ds=2000-04-09 POSTHOOK: Input: default@pcs_t1@ds=2000-04-10 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `ds` +FROM `default`.`pcs_t1` +WHERE (`ds` = '2000-04-08' OR `key` IS NOT NULL) AND `key` = 2 OR `ds` = '2000-04-08' = FALSE AND `key` = 3 STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1559,23 +1578,23 @@ STAGE PLANS: Map Operator Tree: TableScan alias: pcs_t1 - filterExpr: (struct(key,((ds = '2000-04-08') or (key = 2)))) IN (const struct(2,true), const struct(3,false)) (type: boolean) + filterExpr: ((((ds = '2000-04-08') or key is not null) and (key = 2)) or (((ds = '2000-04-08') = false) and (key = 3))) (type: boolean) Statistics: Num rows: 60 Data size: 480 Basic stats: COMPLETE Column stats: NONE GatherStats: false Filter Operator isSamplingPred: false - predicate: (struct(key,((ds = '2000-04-08') or (key = 2)))) IN (const struct(2,true), const struct(3,false)) (type: boolean) - Statistics: Num rows: 30 Data size: 240 Basic stats: COMPLETE Column stats: NONE + predicate: ((((ds = '2000-04-08') = false) and (key = 3)) or (((ds = '2000-04-08') or key is not null) and (key = 2))) (type: boolean) + Statistics: Num rows: 45 Data size: 360 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: ds (type: string) outputColumnNames: _col0 - Statistics: Num rows: 30 Data size: 240 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 45 Data size: 360 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false GlobalTableId: 0 #### A masked pattern was here #### NumFilesPerFileSink: 1 - Statistics: Num rows: 30 Data size: 240 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 45 Data size: 360 Basic stats: COMPLETE Column stats: NONE #### A masked pattern was here #### table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat @@ -1592,6 +1611,7 @@ STAGE PLANS: TotalFiles: 1 GatherStats: false MultiFileSpray: false + Execution mode: vectorized Path -> Alias: #### A masked pattern was here #### Path -> Partition: @@ -1781,6 +1801,9 @@ POSTHOOK: Input: default@pcs_t1@ds=2000-04-08 POSTHOOK: Input: default@pcs_t1@ds=2000-04-09 POSTHOOK: Input: default@pcs_t1@ds=2000-04-10 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `ds` +FROM `default`.`pcs_t1` +WHERE `key` = 3 OR ROW(`key`, `ds` = '2000-04-08' OR `key` = 2) IN (ROW(2, TRUE), ROW(3, FALSE)) AND `key` + 5 > 0 STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 diff --git ql/src/test/results/clientpositive/perf/spark/query11.q.out ql/src/test/results/clientpositive/perf/spark/query11.q.out index 28ce6d0814..7224b13d51 100644 --- ql/src/test/results/clientpositive/perf/spark/query11.q.out +++ ql/src/test/results/clientpositive/perf/spark/query11.q.out @@ -673,16 +673,16 @@ STAGE PLANS: outputColumnNames: _col1, _col3, _col5, _col6, _col8, _col9 Statistics: Num rows: 1149975359 Data size: 101451160012 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN (_col3 is not null) THEN (CASE WHEN (_col6) THEN (((_col1 / _col5) > (_col9 / _col3))) ELSE ((null > (_col9 / _col3))) END) ELSE (CASE WHEN (_col6) THEN (((_col1 / _col5) > null)) ELSE (null) END) END (type: boolean) - Statistics: Num rows: 574987679 Data size: 50725579961 Basic stats: COMPLETE Column stats: NONE + predicate: ((_col6 and ((_col1 / _col5) > (_col9 / _col3))) and _col3 is not null) (type: boolean) + Statistics: Num rows: 191662561 Data size: 16908526771 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col8 (type: string) outputColumnNames: _col0 - Statistics: Num rows: 574987679 Data size: 50725579961 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 191662561 Data size: 16908526771 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string) sort order: + - Statistics: Num rows: 574987679 Data size: 50725579961 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 191662561 Data size: 16908526771 Basic stats: COMPLETE Column stats: NONE TopN Hash Memory Usage: 0.1 Reducer 6 Execution mode: vectorized @@ -690,7 +690,7 @@ STAGE PLANS: Select Operator expressions: KEY.reducesinkkey0 (type: string) outputColumnNames: _col0 - Statistics: Num rows: 574987679 Data size: 50725579961 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 191662561 Data size: 16908526771 Basic stats: COMPLETE Column stats: NONE Limit Number of rows: 100 Statistics: Num rows: 100 Data size: 8800 Basic stats: COMPLETE Column stats: NONE diff --git ql/src/test/results/clientpositive/perf/spark/query21.q.out ql/src/test/results/clientpositive/perf/spark/query21.q.out index 6c2efe75c9..4eac120d57 100644 --- ql/src/test/results/clientpositive/perf/spark/query21.q.out +++ ql/src/test/results/clientpositive/perf/spark/query21.q.out @@ -231,7 +231,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3 Statistics: Num rows: 25012152 Data size: 395187961 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col2 > 0L)) THEN ((UDFToDouble(_col3) / UDFToDouble(_col2)) BETWEEN 0.666667D AND 1.5D) ELSE (null) END (type: boolean) + predicate: CASE WHEN ((_col2 > 0L)) THEN ((UDFToDouble(_col3) / UDFToDouble(_col2)) BETWEEN 0.666667D AND 1.5D) ELSE (false) END (type: boolean) Statistics: Num rows: 12506076 Data size: 197593980 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string), _col1 (type: string) diff --git ql/src/test/results/clientpositive/perf/spark/query31.q.out ql/src/test/results/clientpositive/perf/spark/query31.q.out index 27cfadc942..8d9f52eb0e 100644 --- ql/src/test/results/clientpositive/perf/spark/query31.q.out +++ ql/src/test/results/clientpositive/perf/spark/query31.q.out @@ -837,15 +837,15 @@ STAGE PLANS: outputColumnNames: _col1, _col2, _col4, _col6, _col7, _col8, _col9, _col11, _col13 Statistics: Num rows: 2529945843 Data size: 223192556861 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (CASE WHEN ((_col11 > 0)) THEN (CASE WHEN (_col2) THEN (((_col6 / _col1) > (_col9 / _col11))) ELSE ((null > (_col9 / _col11))) END) ELSE (CASE WHEN (_col2) THEN (((_col6 / _col1) > null)) ELSE (null) END) END and CASE WHEN ((_col9 > 0)) THEN (CASE WHEN (_col7) THEN (((_col4 / _col6) > (_col13 / _col9))) ELSE ((null > (_col13 / _col9))) END) ELSE (CASE WHEN (_col7) THEN (((_col4 / _col6) > null)) ELSE (null) END) END) (type: boolean) - Statistics: Num rows: 632486460 Data size: 55798139149 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col11 > 0) is true and (_col2 is true and ((_col6 / _col1) > (_col9 / _col11)))) and ((_col9 > 0) is true and (_col7 is true and ((_col4 / _col6) > (_col13 / _col9))))) (type: boolean) + Statistics: Num rows: 17569068 Data size: 1549948280 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col8 (type: string), 2000 (type: int), (_col6 / _col1) (type: decimal(37,20)), (_col9 / _col11) (type: decimal(37,20)), (_col4 / _col6) (type: decimal(37,20)), (_col13 / _col9) (type: decimal(37,20)) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 - Statistics: Num rows: 632486460 Data size: 55798139149 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 17569068 Data size: 1549948280 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 632486460 Data size: 55798139149 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 17569068 Data size: 1549948280 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat diff --git ql/src/test/results/clientpositive/perf/spark/query34.q.out ql/src/test/results/clientpositive/perf/spark/query34.q.out index 1dd58b399f..a0ba9e10c5 100644 --- ql/src/test/results/clientpositive/perf/spark/query34.q.out +++ ql/src/test/results/clientpositive/perf/spark/query34.q.out @@ -228,7 +228,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2 Statistics: Num rows: 383325119 Data size: 33817053293 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: _col2 BETWEEN 15 AND 20 (type: boolean) + predicate: _col2 BETWEEN 15L AND 20L (type: boolean) Statistics: Num rows: 3 Data size: 264 Basic stats: COMPLETE Column stats: NONE Spark HashTable Sink Operator keys: diff --git ql/src/test/results/clientpositive/perf/spark/query36.q.out ql/src/test/results/clientpositive/perf/spark/query36.q.out index c6088be8db..facbf5a4e3 100644 --- ql/src/test/results/clientpositive/perf/spark/query36.q.out +++ ql/src/test/results/clientpositive/perf/spark/query36.q.out @@ -234,9 +234,9 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4 Statistics: Num rows: 1149975358 Data size: 101451159969 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator - key expressions: (grouping(_col4, 1) + grouping(_col4, 0)) (type: bigint), CASE WHEN ((grouping(_col4, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END (type: string), (_col2 / _col3) (type: decimal(37,20)) + key expressions: (grouping(_col4, 1) + grouping(_col4, 0)) (type: bigint), CASE WHEN ((grouping(_col4, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END (type: string), (_col2 / _col3) (type: decimal(37,20)) sort order: +++ - Map-reduce partition columns: (grouping(_col4, 1) + grouping(_col4, 0)) (type: bigint), CASE WHEN ((grouping(_col4, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END (type: string) + Map-reduce partition columns: (grouping(_col4, 1) + grouping(_col4, 0)) (type: bigint), CASE WHEN ((grouping(_col4, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END (type: string) Statistics: Num rows: 1149975358 Data size: 101451159969 Basic stats: COMPLETE Column stats: NONE value expressions: _col0 (type: string), _col1 (type: string), _col2 (type: decimal(17,2)), _col3 (type: decimal(17,2)), _col4 (type: bigint) Reducer 5 @@ -256,7 +256,7 @@ STAGE PLANS: input alias: ptf_1 name: windowingtablefunction order by: (_col2 / _col3) ASC NULLS FIRST - partition by: (grouping(_col4, 1) + grouping(_col4, 0)), CASE WHEN ((grouping(_col4, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END + partition by: (grouping(_col4, 1) + grouping(_col4, 0)), CASE WHEN ((grouping(_col4, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END raw input shape: window functions: window function definition diff --git ql/src/test/results/clientpositive/perf/spark/query4.q.out ql/src/test/results/clientpositive/perf/spark/query4.q.out index 93e83ef10e..f223cdb2a4 100644 --- ql/src/test/results/clientpositive/perf/spark/query4.q.out +++ ql/src/test/results/clientpositive/perf/spark/query4.q.out @@ -986,16 +986,16 @@ STAGE PLANS: outputColumnNames: _col1, _col3, _col5, _col6, _col8, _col9, _col11, _col13, _col14 Statistics: Num rows: 1916625598 Data size: 169085266687 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (CASE WHEN (_col3 is not null) THEN (CASE WHEN (_col9) THEN (((_col11 / _col8) > (_col14 / _col3))) ELSE ((null > (_col14 / _col3))) END) ELSE (CASE WHEN (_col9) THEN (((_col11 / _col8) > null)) ELSE (null) END) END and CASE WHEN (_col6) THEN (CASE WHEN (_col9) THEN (((_col11 / _col8) > (_col1 / _col5))) ELSE ((null > (_col1 / _col5))) END) ELSE (CASE WHEN (_col9) THEN (((_col11 / _col8) > null)) ELSE (null) END) END) (type: boolean) - Statistics: Num rows: 479156399 Data size: 42271316627 Basic stats: COMPLETE Column stats: NONE + predicate: ((_col3 is not null and (_col9 and ((_col11 / _col8) > (_col14 / _col3)))) and (_col6 and (_col9 and ((_col11 / _col8) > (_col1 / _col5))))) (type: boolean) + Statistics: Num rows: 26619802 Data size: 2348406660 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col13 (type: string) outputColumnNames: _col0 - Statistics: Num rows: 479156399 Data size: 42271316627 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 26619802 Data size: 2348406660 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string) sort order: + - Statistics: Num rows: 479156399 Data size: 42271316627 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 26619802 Data size: 2348406660 Basic stats: COMPLETE Column stats: NONE TopN Hash Memory Usage: 0.1 Reducer 6 Execution mode: vectorized @@ -1003,7 +1003,7 @@ STAGE PLANS: Select Operator expressions: KEY.reducesinkkey0 (type: string) outputColumnNames: _col0 - Statistics: Num rows: 479156399 Data size: 42271316627 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 26619802 Data size: 2348406660 Basic stats: COMPLETE Column stats: NONE Limit Number of rows: 100 Statistics: Num rows: 100 Data size: 8800 Basic stats: COMPLETE Column stats: NONE diff --git ql/src/test/results/clientpositive/perf/spark/query42.q.out ql/src/test/results/clientpositive/perf/spark/query42.q.out index f4b4914867..961ea27352 100644 --- ql/src/test/results/clientpositive/perf/spark/query42.q.out +++ ql/src/test/results/clientpositive/perf/spark/query42.q.out @@ -181,23 +181,27 @@ STAGE PLANS: Execution mode: vectorized Reduce Operator Tree: Select Operator - expressions: 1998 (type: int), KEY.reducesinkkey1 (type: int), KEY.reducesinkkey2 (type: string), KEY.reducesinkkey0 (type: decimal(17,2)) - outputColumnNames: _col0, _col1, _col2, _col3 + expressions: KEY.reducesinkkey1 (type: int), KEY.reducesinkkey2 (type: string), KEY.reducesinkkey0 (type: decimal(17,2)) + outputColumnNames: _col0, _col1, _col2 Statistics: Num rows: 348477374 Data size: 30742775095 Basic stats: COMPLETE Column stats: NONE Limit Number of rows: 100 Statistics: Num rows: 100 Data size: 8800 Basic stats: COMPLETE Column stats: NONE - File Output Operator - compressed: false + Select Operator + expressions: 1998 (type: int), _col0 (type: int), _col1 (type: string), _col2 (type: decimal(17,2)) + outputColumnNames: _col0, _col1, _col2, _col3 Statistics: Num rows: 100 Data size: 8800 Basic stats: COMPLETE Column stats: NONE - table: - input format: org.apache.hadoop.mapred.SequenceFileInputFormat - output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat - serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + File Output Operator + compressed: false + Statistics: Num rows: 100 Data size: 8800 Basic stats: COMPLETE Column stats: NONE + table: + input format: org.apache.hadoop.mapred.SequenceFileInputFormat + output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat + serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe Stage: Stage-0 Fetch Operator - limit: 100 + limit: -1 Processor Tree: ListSink diff --git ql/src/test/results/clientpositive/perf/spark/query45.q.out ql/src/test/results/clientpositive/perf/spark/query45.q.out index c8242745ee..af93ba88ed 100644 --- ql/src/test/results/clientpositive/perf/spark/query45.q.out +++ ql/src/test/results/clientpositive/perf/spark/query45.q.out @@ -71,18 +71,16 @@ STAGE PLANS: predicate: (i_item_sk) IN (2, 3, 5, 7, 11, 13, 17, 19, 23, 29) (type: boolean) Statistics: Num rows: 462000 Data size: 663560457 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: i_item_id (type: string) - outputColumnNames: i_item_id Statistics: Num rows: 462000 Data size: 663560457 Basic stats: COMPLETE Column stats: NONE Group By Operator - aggregations: count(), count(i_item_id) + aggregations: count() mode: hash - outputColumnNames: _col0, _col1 - Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: NONE + outputColumnNames: _col0 + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator sort order: - Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: NONE - value expressions: _col0 (type: bigint), _col1 (type: bigint) + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE + value expressions: _col0 (type: bigint) Execution mode: vectorized Reducer 16 Execution mode: vectorized @@ -90,10 +88,10 @@ STAGE PLANS: Map Reduce Local Work Reduce Operator Tree: Group By Operator - aggregations: count(VALUE._col0), count(VALUE._col1) + aggregations: count(VALUE._col0) mode: mergepartial - outputColumnNames: _col0, _col1 - Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: NONE + outputColumnNames: _col0 + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE Spark HashTable Sink Operator keys: 0 @@ -106,7 +104,7 @@ STAGE PLANS: Reducer 13 <- Map 12 (PARTITION-LEVEL SORT, 154), Map 14 (PARTITION-LEVEL SORT, 154) Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 855), Map 6 (PARTITION-LEVEL SORT, 855) Reducer 3 <- Reducer 2 (PARTITION-LEVEL SORT, 777), Reducer 9 (PARTITION-LEVEL SORT, 777) - Reducer 4 <- Reducer 3 (GROUP, 230) + Reducer 4 <- Reducer 3 (GROUP, 218) Reducer 5 <- Reducer 4 (SORT, 1) Reducer 8 <- Map 7 (PARTITION-LEVEL SORT, 8), Reducer 11 (PARTITION-LEVEL SORT, 8) Reducer 9 <- Reducer 13 (PARTITION-LEVEL SORT, 174), Reducer 8 (PARTITION-LEVEL SORT, 174) @@ -295,7 +293,7 @@ STAGE PLANS: keys: 0 _col0 (type: int) 1 _col6 (type: int) - outputColumnNames: _col3, _col4, _col6, _col8, _col12 + outputColumnNames: _col3, _col4, _col8, _col12 Statistics: Num rows: 191667562 Data size: 26061245514 Basic stats: COMPLETE Column stats: NONE Map Join Operator condition map: @@ -303,32 +301,32 @@ STAGE PLANS: keys: 0 1 - outputColumnNames: _col3, _col4, _col6, _col8, _col12, _col16, _col17 + outputColumnNames: _col3, _col4, _col8, _col12, _col16 input vertices: 1 Reducer 16 - Statistics: Num rows: 191667562 Data size: 29319594068 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 191667562 Data size: 27786253572 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: _col12 (type: decimal(7,2)), _col3 (type: string), _col4 (type: string), _col6 (type: string), _col16 (type: bigint), _col17 (type: bigint), _col8 (type: boolean) - outputColumnNames: _col3, _col7, _col8, _col13, _col14, _col15, _col17 - Statistics: Num rows: 191667562 Data size: 29319594068 Basic stats: COMPLETE Column stats: NONE + expressions: _col12 (type: decimal(7,2)), _col3 (type: string), _col4 (type: string), _col16 (type: bigint), _col8 (type: boolean) + outputColumnNames: _col3, _col7, _col8, _col14, _col16 + Statistics: Num rows: 191667562 Data size: 27786253572 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((substr(_col8, 1, 5)) IN ('85669', '86197', '88274', '83405', '86475', '85392', '85460', '80348', '81792') or CASE WHEN ((_col14 = 0L)) THEN (false) WHEN (_col17 is not null) THEN (true) WHEN (_col13 is null) THEN (null) WHEN ((_col15 < _col14)) THEN (null) ELSE (false) END) (type: boolean) - Statistics: Num rows: 191667562 Data size: 29319594068 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col14 <> 0L) and _col16 is not null) or (substr(_col8, 1, 5)) IN ('85669', '86197', '88274', '83405', '86475', '85392', '85460', '80348', '81792')) (type: boolean) + Statistics: Num rows: 191667562 Data size: 27786253572 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col3 (type: decimal(7,2)), _col7 (type: string), _col8 (type: string) outputColumnNames: _col3, _col7, _col8 - Statistics: Num rows: 191667562 Data size: 29319594068 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 191667562 Data size: 27786253572 Basic stats: COMPLETE Column stats: NONE Group By Operator aggregations: sum(_col3) keys: _col8 (type: string), _col7 (type: string) mode: hash outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 191667562 Data size: 29319594068 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 191667562 Data size: 27786253572 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string), _col1 (type: string) sort order: ++ Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 191667562 Data size: 29319594068 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 191667562 Data size: 27786253572 Basic stats: COMPLETE Column stats: NONE TopN Hash Memory Usage: 0.1 value expressions: _col2 (type: decimal(17,2)) Reducer 4 @@ -339,11 +337,11 @@ STAGE PLANS: keys: KEY._col0 (type: string), KEY._col1 (type: string) mode: mergepartial outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 95833781 Data size: 14659797034 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 95833781 Data size: 13893126786 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string), _col1 (type: string) sort order: ++ - Statistics: Num rows: 95833781 Data size: 14659797034 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 95833781 Data size: 13893126786 Basic stats: COMPLETE Column stats: NONE TopN Hash Memory Usage: 0.1 value expressions: _col2 (type: decimal(17,2)) Reducer 5 @@ -352,13 +350,13 @@ STAGE PLANS: Select Operator expressions: KEY.reducesinkkey0 (type: string), KEY.reducesinkkey1 (type: string), VALUE._col0 (type: decimal(17,2)) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 95833781 Data size: 14659797034 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 95833781 Data size: 13893126786 Basic stats: COMPLETE Column stats: NONE Limit Number of rows: 100 - Statistics: Num rows: 100 Data size: 15200 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 100 Data size: 14400 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 100 Data size: 15200 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 100 Data size: 14400 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -371,14 +369,14 @@ STAGE PLANS: keys: 0 _col1 (type: string) 1 _col0 (type: string) - outputColumnNames: _col0, _col1, _col3 + outputColumnNames: _col0, _col3 Statistics: Num rows: 508200 Data size: 729916518 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: int) sort order: + Map-reduce partition columns: _col0 (type: int) Statistics: Num rows: 508200 Data size: 729916518 Basic stats: COMPLETE Column stats: NONE - value expressions: _col1 (type: string), _col3 (type: boolean) + value expressions: _col3 (type: boolean) Reducer 9 Reduce Operator Tree: Join Operator @@ -387,14 +385,14 @@ STAGE PLANS: keys: 0 _col0 (type: int) 1 _col1 (type: int) - outputColumnNames: _col1, _col3, _col6, _col7 + outputColumnNames: _col3, _col6, _col7 Statistics: Num rows: 174243235 Data size: 23692040863 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col6 (type: int) sort order: + Map-reduce partition columns: _col6 (type: int) Statistics: Num rows: 174243235 Data size: 23692040863 Basic stats: COMPLETE Column stats: NONE - value expressions: _col1 (type: string), _col3 (type: boolean), _col7 (type: decimal(7,2)) + value expressions: _col3 (type: boolean), _col7 (type: decimal(7,2)) Stage: Stage-0 Fetch Operator diff --git ql/src/test/results/clientpositive/perf/spark/query53.q.out ql/src/test/results/clientpositive/perf/spark/query53.q.out index ea5dde1e51..18e224f38f 100644 --- ql/src/test/results/clientpositive/perf/spark/query53.q.out +++ ql/src/test/results/clientpositive/perf/spark/query53.q.out @@ -249,7 +249,7 @@ STAGE PLANS: outputColumnNames: avg_window_0, _col0, _col2 Statistics: Num rows: 383325119 Data size: 33817053293 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((avg_window_0 > 0)) THEN (((abs((_col2 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (null) END (type: boolean) + predicate: CASE WHEN ((avg_window_0 > 0)) THEN (((abs((_col2 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (false) END (type: boolean) Statistics: Num rows: 191662559 Data size: 16908526602 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col2 (type: decimal(17,2)), avg_window_0 (type: decimal(21,6)) diff --git ql/src/test/results/clientpositive/perf/spark/query6.q.out ql/src/test/results/clientpositive/perf/spark/query6.q.out index 2702aefd92..18e1067fcc 100644 --- ql/src/test/results/clientpositive/perf/spark/query6.q.out +++ ql/src/test/results/clientpositive/perf/spark/query6.q.out @@ -326,7 +326,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2 Statistics: Num rows: 231000 Data size: 331780228 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: _col0 (type: string), (1.2 * CAST( (_col1 / _col2) AS decimal(16,6))) (type: decimal(19,7)) + expressions: _col0 (type: string), (1.2 * (_col1 / _col2)) (type: decimal(38,21)) outputColumnNames: _col0, _col1 Statistics: Num rows: 231000 Data size: 331780228 Basic stats: COMPLETE Column stats: NONE Map Join Operator @@ -344,7 +344,7 @@ STAGE PLANS: sort order: + Map-reduce partition columns: _col0 (type: string) Statistics: Num rows: 231000 Data size: 333859228 Basic stats: COMPLETE Column stats: NONE - value expressions: _col1 (type: decimal(19,7)) + value expressions: _col1 (type: decimal(38,21)) Reducer 16 Reduce Operator Tree: Join Operator diff --git ql/src/test/results/clientpositive/perf/spark/query63.q.out ql/src/test/results/clientpositive/perf/spark/query63.q.out index 2d905d382b..a75610ff28 100644 --- ql/src/test/results/clientpositive/perf/spark/query63.q.out +++ ql/src/test/results/clientpositive/perf/spark/query63.q.out @@ -251,7 +251,7 @@ STAGE PLANS: outputColumnNames: avg_window_0, _col0, _col2 Statistics: Num rows: 383325119 Data size: 33817053293 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((avg_window_0 > 0)) THEN (((abs((_col2 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (null) END (type: boolean) + predicate: CASE WHEN ((avg_window_0 > 0)) THEN (((abs((_col2 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (false) END (type: boolean) Statistics: Num rows: 191662559 Data size: 16908526602 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col2 (type: decimal(17,2)), avg_window_0 (type: decimal(21,6)) diff --git ql/src/test/results/clientpositive/perf/spark/query70.q.out ql/src/test/results/clientpositive/perf/spark/query70.q.out index d73e54243d..b34ecfc247 100644 --- ql/src/test/results/clientpositive/perf/spark/query70.q.out +++ ql/src/test/results/clientpositive/perf/spark/query70.q.out @@ -386,9 +386,9 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3 Statistics: Num rows: 1149975358 Data size: 101451159969 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator - key expressions: (grouping(_col3, 1) + grouping(_col3, 0)) (type: bigint), CASE WHEN ((grouping(_col3, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END (type: string), _col2 (type: decimal(17,2)) + key expressions: (grouping(_col3, 1) + grouping(_col3, 0)) (type: bigint), CASE WHEN ((grouping(_col3, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END (type: string), _col2 (type: decimal(17,2)) sort order: ++- - Map-reduce partition columns: (grouping(_col3, 1) + grouping(_col3, 0)) (type: bigint), CASE WHEN ((grouping(_col3, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END (type: string) + Map-reduce partition columns: (grouping(_col3, 1) + grouping(_col3, 0)) (type: bigint), CASE WHEN ((grouping(_col3, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END (type: string) Statistics: Num rows: 1149975358 Data size: 101451159969 Basic stats: COMPLETE Column stats: NONE value expressions: _col0 (type: string), _col1 (type: string), _col3 (type: bigint) Reducer 5 @@ -408,7 +408,7 @@ STAGE PLANS: input alias: ptf_1 name: windowingtablefunction order by: _col2 DESC NULLS LAST - partition by: (grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END + partition by: (grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END raw input shape: window functions: window function definition diff --git ql/src/test/results/clientpositive/perf/spark/query73.q.out ql/src/test/results/clientpositive/perf/spark/query73.q.out index 26791ff929..def587c814 100644 --- ql/src/test/results/clientpositive/perf/spark/query73.q.out +++ ql/src/test/results/clientpositive/perf/spark/query73.q.out @@ -222,7 +222,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2 Statistics: Num rows: 383325119 Data size: 33817053293 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: _col2 BETWEEN 1 AND 5 (type: boolean) + predicate: _col2 BETWEEN 1L AND 5L (type: boolean) Statistics: Num rows: 2 Data size: 176 Basic stats: COMPLETE Column stats: NONE Spark HashTable Sink Operator keys: diff --git ql/src/test/results/clientpositive/perf/spark/query74.q.out ql/src/test/results/clientpositive/perf/spark/query74.q.out index cc9b74eb0c..eae3514f64 100644 --- ql/src/test/results/clientpositive/perf/spark/query74.q.out +++ ql/src/test/results/clientpositive/perf/spark/query74.q.out @@ -641,16 +641,16 @@ STAGE PLANS: outputColumnNames: _col1, _col3, _col5, _col6, _col7, _col8, _col9, _col10 Statistics: Num rows: 1149975359 Data size: 101451160012 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN (_col3 is not null) THEN (CASE WHEN (_col6) THEN (((_col1 / _col5) > (_col10 / _col3))) ELSE ((null > (_col10 / _col3))) END) ELSE (CASE WHEN (_col6) THEN (((_col1 / _col5) > null)) ELSE (null) END) END (type: boolean) - Statistics: Num rows: 574987679 Data size: 50725579961 Basic stats: COMPLETE Column stats: NONE + predicate: ((_col6 and ((_col1 / _col5) > (_col10 / _col3))) and _col3 is not null) (type: boolean) + Statistics: Num rows: 191662561 Data size: 16908526771 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col7 (type: string), _col8 (type: string), _col9 (type: string) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 574987679 Data size: 50725579961 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 191662561 Data size: 16908526771 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col1 (type: string), _col0 (type: string), _col2 (type: string) sort order: +++ - Statistics: Num rows: 574987679 Data size: 50725579961 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 191662561 Data size: 16908526771 Basic stats: COMPLETE Column stats: NONE TopN Hash Memory Usage: 0.1 Reducer 6 Execution mode: vectorized @@ -658,7 +658,7 @@ STAGE PLANS: Select Operator expressions: KEY.reducesinkkey1 (type: string), KEY.reducesinkkey0 (type: string), KEY.reducesinkkey2 (type: string) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 574987679 Data size: 50725579961 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 191662561 Data size: 16908526771 Basic stats: COMPLETE Column stats: NONE Limit Number of rows: 100 Statistics: Num rows: 100 Data size: 8800 Basic stats: COMPLETE Column stats: NONE diff --git ql/src/test/results/clientpositive/perf/spark/query78.q.out ql/src/test/results/clientpositive/perf/spark/query78.q.out index c121a341fd..ce0a9dfe29 100644 --- ql/src/test/results/clientpositive/perf/spark/query78.q.out +++ ql/src/test/results/clientpositive/perf/spark/query78.q.out @@ -139,13 +139,13 @@ STAGE PLANS: Reducer 11 <- Map 10 (PARTITION-LEVEL SORT, 85), Reducer 14 (PARTITION-LEVEL SORT, 85) Reducer 12 <- Reducer 11 (GROUP, 93) Reducer 14 <- Map 13 (PARTITION-LEVEL SORT, 164), Map 15 (PARTITION-LEVEL SORT, 164) - Reducer 17 <- Map 10 (PARTITION-LEVEL SORT, 85), Reducer 20 (PARTITION-LEVEL SORT, 85) + Reducer 17 <- Map 16 (PARTITION-LEVEL SORT, 85), Reducer 20 (PARTITION-LEVEL SORT, 85) Reducer 18 <- Reducer 17 (GROUP, 93) Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 219), Reducer 8 (PARTITION-LEVEL SORT, 219) Reducer 20 <- Map 19 (PARTITION-LEVEL SORT, 177), Map 21 (PARTITION-LEVEL SORT, 177) Reducer 3 <- Reducer 2 (GROUP, 241) - Reducer 4 <- Reducer 12 (PARTITION-LEVEL SORT, 167), Reducer 3 (PARTITION-LEVEL SORT, 167) - Reducer 5 <- Reducer 18 (PARTITION-LEVEL SORT, 113), Reducer 4 (PARTITION-LEVEL SORT, 113) + Reducer 4 <- Reducer 12 (PARTITION-LEVEL SORT, 136), Reducer 3 (PARTITION-LEVEL SORT, 136) + Reducer 5 <- Reducer 18 (PARTITION-LEVEL SORT, 148), Reducer 4 (PARTITION-LEVEL SORT, 148) Reducer 6 <- Reducer 5 (SORT, 1) Reducer 8 <- Map 7 (PARTITION-LEVEL SORT, 432), Map 9 (PARTITION-LEVEL SORT, 432) #### A masked pattern was here #### @@ -192,10 +192,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: web_sales - filterExpr: ws_sold_date_sk is not null (type: boolean) + filterExpr: (ws_sold_date_sk is not null and ws_item_sk is not null and ws_bill_customer_sk is not null) (type: boolean) Statistics: Num rows: 144002668 Data size: 19580198212 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ws_sold_date_sk is not null (type: boolean) + predicate: (ws_bill_customer_sk is not null and ws_item_sk is not null and ws_sold_date_sk is not null) (type: boolean) Statistics: Num rows: 144002668 Data size: 19580198212 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: ws_sold_date_sk (type: int), ws_item_sk (type: int), ws_bill_customer_sk (type: int), ws_order_number (type: int), ws_quantity (type: int), ws_wholesale_cost (type: decimal(7,2)), ws_sales_price (type: decimal(7,2)) @@ -212,25 +212,48 @@ STAGE PLANS: Map Operator Tree: TableScan alias: web_returns + filterExpr: wr_item_sk is not null (type: boolean) Statistics: Num rows: 14398467 Data size: 1325194184 Basic stats: COMPLETE Column stats: NONE - Select Operator - expressions: wr_item_sk (type: int), wr_order_number (type: int) - outputColumnNames: _col0, _col1 + Filter Operator + predicate: wr_item_sk is not null (type: boolean) Statistics: Num rows: 14398467 Data size: 1325194184 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: int), _col1 (type: int) - sort order: ++ - Map-reduce partition columns: _col0 (type: int), _col1 (type: int) + Select Operator + expressions: wr_item_sk (type: int), wr_order_number (type: int) + outputColumnNames: _col0, _col1 Statistics: Num rows: 14398467 Data size: 1325194184 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: int), _col1 (type: int) + sort order: ++ + Map-reduce partition columns: _col0 (type: int), _col1 (type: int) + Statistics: Num rows: 14398467 Data size: 1325194184 Basic stats: COMPLETE Column stats: NONE + Execution mode: vectorized + Map 16 + Map Operator Tree: + TableScan + alias: date_dim + filterExpr: ((d_year = 2000) and d_date_sk is not null) (type: boolean) + Statistics: Num rows: 73049 Data size: 81741831 Basic stats: COMPLETE Column stats: NONE + Filter Operator + predicate: ((d_year = 2000) and d_date_sk is not null) (type: boolean) + Statistics: Num rows: 36524 Data size: 40870356 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: d_date_sk (type: int) + outputColumnNames: _col0 + Statistics: Num rows: 36524 Data size: 40870356 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: int) + sort order: + + Map-reduce partition columns: _col0 (type: int) + Statistics: Num rows: 36524 Data size: 40870356 Basic stats: COMPLETE Column stats: NONE Execution mode: vectorized Map 19 Map Operator Tree: TableScan alias: catalog_sales - filterExpr: ((cs_item_sk = cs_item_sk) and cs_sold_date_sk is not null) (type: boolean) + filterExpr: ((cs_item_sk = cs_item_sk) and cs_sold_date_sk is not null and cs_bill_customer_sk is not null) (type: boolean) Statistics: Num rows: 287989836 Data size: 38999608952 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((cs_item_sk = cs_item_sk) and cs_sold_date_sk is not null) (type: boolean) + predicate: ((cs_item_sk = cs_item_sk) and cs_bill_customer_sk is not null and cs_sold_date_sk is not null) (type: boolean) Statistics: Num rows: 143994918 Data size: 19499804476 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: cs_sold_date_sk (type: int), cs_bill_customer_sk (type: int), cs_item_sk (type: int), cs_order_number (type: int), cs_quantity (type: int), cs_wholesale_cost (type: decimal(7,2)), cs_sales_price (type: decimal(7,2)) @@ -262,10 +285,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: store_sales - filterExpr: ss_sold_date_sk is not null (type: boolean) + filterExpr: (ss_sold_date_sk is not null and ss_item_sk is not null and ss_customer_sk is not null) (type: boolean) Statistics: Num rows: 575995635 Data size: 50814502088 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ss_sold_date_sk is not null (type: boolean) + predicate: (ss_customer_sk is not null and ss_item_sk is not null and ss_sold_date_sk is not null) (type: boolean) Statistics: Num rows: 575995635 Data size: 50814502088 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: ss_sold_date_sk (type: int), ss_item_sk (type: int), ss_customer_sk (type: int), ss_ticket_number (type: int), ss_quantity (type: int), ss_wholesale_cost (type: decimal(7,2)), ss_sales_price (type: decimal(7,2)) @@ -282,16 +305,20 @@ STAGE PLANS: Map Operator Tree: TableScan alias: store_returns + filterExpr: sr_item_sk is not null (type: boolean) Statistics: Num rows: 57591150 Data size: 4462194832 Basic stats: COMPLETE Column stats: NONE - Select Operator - expressions: sr_item_sk (type: int), sr_ticket_number (type: int) - outputColumnNames: _col0, _col1 + Filter Operator + predicate: sr_item_sk is not null (type: boolean) Statistics: Num rows: 57591150 Data size: 4462194832 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: int), _col1 (type: int) - sort order: ++ - Map-reduce partition columns: _col0 (type: int), _col1 (type: int) + Select Operator + expressions: sr_item_sk (type: int), sr_ticket_number (type: int) + outputColumnNames: _col0, _col1 Statistics: Num rows: 57591150 Data size: 4462194832 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: int), _col1 (type: int) + sort order: ++ + Map-reduce partition columns: _col0 (type: int), _col1 (type: int) + Statistics: Num rows: 57591150 Data size: 4462194832 Basic stats: COMPLETE Column stats: NONE Execution mode: vectorized Reducer 11 Reduce Operator Tree: @@ -324,16 +351,19 @@ STAGE PLANS: mode: mergepartial outputColumnNames: _col0, _col1, _col2, _col3, _col4 Statistics: Num rows: 43560808 Data size: 5923010147 Basic stats: COMPLETE Column stats: NONE - Select Operator - expressions: _col1 (type: int), _col0 (type: int), _col2 (type: bigint), _col3 (type: decimal(17,2)), _col4 (type: decimal(17,2)) - outputColumnNames: _col0, _col1, _col2, _col3, _col4 - Statistics: Num rows: 43560808 Data size: 5923010147 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col1 (type: int), _col0 (type: int) - sort order: ++ - Map-reduce partition columns: _col1 (type: int), _col0 (type: int) - Statistics: Num rows: 43560808 Data size: 5923010147 Basic stats: COMPLETE Column stats: NONE - value expressions: _col2 (type: bigint), _col3 (type: decimal(17,2)), _col4 (type: decimal(17,2)) + Filter Operator + predicate: (_col2 > 0L) (type: boolean) + Statistics: Num rows: 14520269 Data size: 1974336670 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: _col1 (type: int), _col0 (type: int), _col2 (type: bigint), _col3 (type: decimal(17,2)), _col4 (type: decimal(17,2)) + outputColumnNames: _col0, _col1, _col2, _col3, _col4 + Statistics: Num rows: 14520269 Data size: 1974336670 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col1 (type: int), _col0 (type: int) + sort order: ++ + Map-reduce partition columns: _col1 (type: int), _col0 (type: int) + Statistics: Num rows: 14520269 Data size: 1974336670 Basic stats: COMPLETE Column stats: NONE + value expressions: _col2 (type: bigint), _col3 (type: decimal(17,2)), _col4 (type: decimal(17,2)) Reducer 14 Reduce Operator Tree: Join Operator @@ -390,14 +420,21 @@ STAGE PLANS: Statistics: Num rows: 43558464 Data size: 5898691072 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col2 (type: bigint), _col3 (type: decimal(17,2)), _col4 (type: decimal(17,2)) - outputColumnNames: _col0, _col1, _col2, _col3 + outputColumnNames: _col1, _col2, _col3, _col4 Statistics: Num rows: 43558464 Data size: 5898691072 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: int) - sort order: + - Map-reduce partition columns: _col0 (type: int) - Statistics: Num rows: 43558464 Data size: 5898691072 Basic stats: COMPLETE Column stats: NONE - value expressions: _col1 (type: bigint), _col2 (type: decimal(17,2)), _col3 (type: decimal(17,2)) + Filter Operator + predicate: (_col2 > 0L) (type: boolean) + Statistics: Num rows: 14519488 Data size: 1966230357 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: _col1 (type: int), _col2 (type: bigint), CASE WHEN (_col2 is not null) THEN (_col2) ELSE (0) END (type: bigint), CASE WHEN (_col3 is not null) THEN (_col3) ELSE (0) END (type: decimal(17,2)), CASE WHEN (_col4 is not null) THEN (_col4) ELSE (0) END (type: decimal(17,2)) + outputColumnNames: _col0, _col1, _col2, _col3, _col4 + Statistics: Num rows: 14519488 Data size: 1966230357 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: int) + sort order: + + Map-reduce partition columns: _col0 (type: int) + Statistics: Num rows: 14519488 Data size: 1966230357 Basic stats: COMPLETE Column stats: NONE + value expressions: _col1 (type: bigint), _col2 (type: bigint), _col3 (type: decimal(17,2)), _col4 (type: decimal(17,2)) Reducer 2 Reduce Operator Tree: Join Operator @@ -466,60 +503,58 @@ STAGE PLANS: Reduce Operator Tree: Join Operator condition map: - Left Outer Join 0 to 1 + Inner Join 0 to 1 keys: 0 _col1 (type: int), _col0 (type: int) 1 _col1 (type: int), _col0 (type: int) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col7, _col8, _col9 Statistics: Num rows: 191662559 Data size: 16908526668 Basic stats: COMPLETE Column stats: NONE - Filter Operator - predicate: CASE WHEN (_col7 is not null) THEN ((_col7 > 0L)) ELSE (false) END (type: boolean) - Statistics: Num rows: 95831279 Data size: 8454263289 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col1 (type: int) - sort order: + - Map-reduce partition columns: _col1 (type: int) - Statistics: Num rows: 95831279 Data size: 8454263289 Basic stats: COMPLETE Column stats: NONE - value expressions: _col0 (type: int), _col2 (type: bigint), _col3 (type: decimal(17,2)), _col4 (type: decimal(17,2)), _col7 (type: bigint), _col8 (type: decimal(17,2)), _col9 (type: decimal(17,2)) + Reduce Output Operator + key expressions: _col1 (type: int) + sort order: + + Map-reduce partition columns: _col1 (type: int) + Statistics: Num rows: 191662559 Data size: 16908526668 Basic stats: COMPLETE Column stats: NONE + value expressions: _col0 (type: int), _col2 (type: bigint), _col3 (type: decimal(17,2)), _col4 (type: decimal(17,2)), _col7 (type: bigint), _col8 (type: decimal(17,2)), _col9 (type: decimal(17,2)) Reducer 5 Reduce Operator Tree: Join Operator condition map: - Left Outer Join 0 to 1 + Inner Join 0 to 1 keys: 0 _col1 (type: int) 1 _col0 (type: int) - outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col7, _col8, _col9, _col11, _col12, _col13 - Statistics: Num rows: 105414409 Data size: 9299689819 Basic stats: COMPLETE Column stats: NONE - Filter Operator - predicate: CASE WHEN (_col11 is not null) THEN ((_col11 > 0L)) ELSE (false) END (type: boolean) - Statistics: Num rows: 52707204 Data size: 4649844865 Basic stats: COMPLETE Column stats: NONE - Select Operator - expressions: _col0 (type: int), _col1 (type: int), (CASE WHEN (_col7 is not null) THEN (_col7) ELSE (0) END + CASE WHEN (_col11 is not null) THEN (_col11) ELSE (0) END) (type: bigint), (CASE WHEN (_col8 is not null) THEN (_col8) ELSE (0) END + CASE WHEN (_col12 is not null) THEN (_col12) ELSE (0) END) (type: decimal(18,2)), (CASE WHEN (_col9 is not null) THEN (_col9) ELSE (0) END + CASE WHEN (_col13 is not null) THEN (_col13) ELSE (0) END) (type: decimal(18,2)), _col2 (type: bigint), _col3 (type: decimal(17,2)), _col4 (type: decimal(17,2)), round((UDFToDouble(_col2) / UDFToDouble(CASE WHEN ((_col7 is not null and _col11 is not null)) THEN ((_col7 + _col11)) ELSE (1) END)), 2) (type: double) - outputColumnNames: _col0, _col1, _col6, _col7, _col8, _col9, _col10, _col11, _col12 - Statistics: Num rows: 52707204 Data size: 4649844865 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: int), _col1 (type: int), _col9 (type: bigint), _col10 (type: decimal(17,2)), _col11 (type: decimal(17,2)), _col6 (type: bigint), _col7 (type: decimal(18,2)), _col8 (type: decimal(18,2)), _col12 (type: double) - sort order: ++---++++ - Statistics: Num rows: 52707204 Data size: 4649844865 Basic stats: COMPLETE Column stats: NONE - TopN Hash Memory Usage: 0.1 + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col7, _col8, _col9, _col11, _col12, _col13, _col14 + Statistics: Num rows: 210828819 Data size: 18599379737 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: _col0 (type: int), _col1 (type: int), (CASE WHEN (_col7 is not null) THEN (_col7) ELSE (0) END + _col12) (type: bigint), (CASE WHEN (_col8 is not null) THEN (_col8) ELSE (0) END + _col13) (type: decimal(18,2)), (CASE WHEN (_col9 is not null) THEN (_col9) ELSE (0) END + _col14) (type: decimal(18,2)), _col2 (type: bigint), _col3 (type: decimal(17,2)), _col4 (type: decimal(17,2)), round((UDFToDouble(_col2) / UDFToDouble(CASE WHEN ((_col7 + _col11) is not null) THEN ((_col7 + _col11)) ELSE (1) END)), 2) (type: double) + outputColumnNames: _col0, _col1, _col6, _col7, _col8, _col9, _col10, _col11, _col12 + Statistics: Num rows: 210828819 Data size: 18599379737 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: int), _col1 (type: int), _col9 (type: bigint), _col10 (type: decimal(17,2)), _col11 (type: decimal(17,2)), _col6 (type: bigint), _col7 (type: decimal(18,2)), _col8 (type: decimal(18,2)), _col12 (type: double) + sort order: ++---++++ + Statistics: Num rows: 210828819 Data size: 18599379737 Basic stats: COMPLETE Column stats: NONE + TopN Hash Memory Usage: 0.1 Reducer 6 Execution mode: vectorized Reduce Operator Tree: Select Operator - expressions: 2000 (type: int), KEY.reducesinkkey0 (type: int), KEY.reducesinkkey1 (type: int), KEY.reducesinkkey8 (type: double), KEY.reducesinkkey2 (type: bigint), KEY.reducesinkkey3 (type: decimal(17,2)), KEY.reducesinkkey4 (type: decimal(17,2)), KEY.reducesinkkey5 (type: bigint), KEY.reducesinkkey6 (type: decimal(18,2)), KEY.reducesinkkey7 (type: decimal(18,2)) - outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9 - Statistics: Num rows: 52707204 Data size: 4649844865 Basic stats: COMPLETE Column stats: NONE + expressions: KEY.reducesinkkey0 (type: int), KEY.reducesinkkey1 (type: int), KEY.reducesinkkey8 (type: double), KEY.reducesinkkey2 (type: bigint), KEY.reducesinkkey3 (type: decimal(17,2)), KEY.reducesinkkey4 (type: decimal(17,2)), KEY.reducesinkkey5 (type: bigint), KEY.reducesinkkey6 (type: decimal(18,2)), KEY.reducesinkkey7 (type: decimal(18,2)) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 + Statistics: Num rows: 210828819 Data size: 18599379737 Basic stats: COMPLETE Column stats: NONE Limit Number of rows: 100 Statistics: Num rows: 100 Data size: 8800 Basic stats: COMPLETE Column stats: NONE - File Output Operator - compressed: false + Select Operator + expressions: 2000 (type: int), _col0 (type: int), _col1 (type: int), _col2 (type: double), _col3 (type: bigint), _col4 (type: decimal(17,2)), _col5 (type: decimal(17,2)), _col6 (type: bigint), _col7 (type: decimal(18,2)), _col8 (type: decimal(18,2)) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9 Statistics: Num rows: 100 Data size: 8800 Basic stats: COMPLETE Column stats: NONE - table: - input format: org.apache.hadoop.mapred.SequenceFileInputFormat - output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat - serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + File Output Operator + compressed: false + Statistics: Num rows: 100 Data size: 8800 Basic stats: COMPLETE Column stats: NONE + table: + input format: org.apache.hadoop.mapred.SequenceFileInputFormat + output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat + serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe Reducer 8 Reduce Operator Tree: Join Operator @@ -546,7 +581,7 @@ STAGE PLANS: Stage: Stage-0 Fetch Operator - limit: 100 + limit: -1 Processor Tree: ListSink diff --git ql/src/test/results/clientpositive/perf/spark/query86.q.out ql/src/test/results/clientpositive/perf/spark/query86.q.out index 835ac5c9ad..9a4a690591 100644 --- ql/src/test/results/clientpositive/perf/spark/query86.q.out +++ ql/src/test/results/clientpositive/perf/spark/query86.q.out @@ -186,9 +186,9 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3 Statistics: Num rows: 261364852 Data size: 35538061226 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator - key expressions: (grouping(_col3, 1) + grouping(_col3, 0)) (type: bigint), CASE WHEN ((grouping(_col3, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END (type: string), _col2 (type: decimal(17,2)) + key expressions: (grouping(_col3, 1) + grouping(_col3, 0)) (type: bigint), CASE WHEN ((grouping(_col3, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END (type: string), _col2 (type: decimal(17,2)) sort order: ++- - Map-reduce partition columns: (grouping(_col3, 1) + grouping(_col3, 0)) (type: bigint), CASE WHEN ((grouping(_col3, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END (type: string) + Map-reduce partition columns: (grouping(_col3, 1) + grouping(_col3, 0)) (type: bigint), CASE WHEN ((grouping(_col3, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END (type: string) Statistics: Num rows: 261364852 Data size: 35538061226 Basic stats: COMPLETE Column stats: NONE value expressions: _col0 (type: string), _col1 (type: string), _col3 (type: bigint) Reducer 5 @@ -208,7 +208,7 @@ STAGE PLANS: input alias: ptf_1 name: windowingtablefunction order by: _col2 DESC NULLS LAST - partition by: (grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END + partition by: (grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END raw input shape: window functions: window function definition diff --git ql/src/test/results/clientpositive/perf/spark/query88.q.out ql/src/test/results/clientpositive/perf/spark/query88.q.out index 029da524d0..87c319583a 100644 --- ql/src/test/results/clientpositive/perf/spark/query88.q.out +++ ql/src/test/results/clientpositive/perf/spark/query88.q.out @@ -235,15 +235,15 @@ STAGE PLANS: Map Operator Tree: TableScan alias: household_demographics - filterExpr: ((hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and (((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) + filterExpr: ((hd_dep_count) IN (3, 0, 1) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) Statistics: Num rows: 7200 Data size: 770400 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and (hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and hd_demo_sk is not null) (type: boolean) - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + predicate: ((((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (hd_dep_count) IN (3, 0, 1) and hd_demo_sk is not null) (type: boolean) + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: hd_demo_sk (type: int) outputColumnNames: _col0 - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Spark HashTable Sink Operator keys: 0 _col1 (type: int) @@ -811,15 +811,15 @@ STAGE PLANS: Map Operator Tree: TableScan alias: household_demographics - filterExpr: ((hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and (((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) + filterExpr: ((hd_dep_count) IN (3, 0, 1) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) Statistics: Num rows: 7200 Data size: 770400 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and (hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and hd_demo_sk is not null) (type: boolean) - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + predicate: ((((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (hd_dep_count) IN (3, 0, 1) and hd_demo_sk is not null) (type: boolean) + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: hd_demo_sk (type: int) outputColumnNames: _col0 - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Spark HashTable Sink Operator keys: 0 _col1 (type: int) @@ -986,15 +986,15 @@ STAGE PLANS: Map Operator Tree: TableScan alias: household_demographics - filterExpr: ((hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and (((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) + filterExpr: ((hd_dep_count) IN (3, 0, 1) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) Statistics: Num rows: 7200 Data size: 770400 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and (hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and hd_demo_sk is not null) (type: boolean) - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + predicate: ((((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (hd_dep_count) IN (3, 0, 1) and hd_demo_sk is not null) (type: boolean) + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: hd_demo_sk (type: int) outputColumnNames: _col0 - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Spark HashTable Sink Operator keys: 0 _col1 (type: int) @@ -1051,15 +1051,15 @@ STAGE PLANS: Map Operator Tree: TableScan alias: household_demographics - filterExpr: ((hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and (((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) + filterExpr: ((hd_dep_count) IN (3, 0, 1) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) Statistics: Num rows: 7200 Data size: 770400 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and (hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and hd_demo_sk is not null) (type: boolean) - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + predicate: ((((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (hd_dep_count) IN (3, 0, 1) and hd_demo_sk is not null) (type: boolean) + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: hd_demo_sk (type: int) outputColumnNames: _col0 - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Spark HashTable Sink Operator keys: 0 _col1 (type: int) @@ -1116,15 +1116,15 @@ STAGE PLANS: Map Operator Tree: TableScan alias: household_demographics - filterExpr: ((hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and (((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) + filterExpr: ((hd_dep_count) IN (3, 0, 1) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) Statistics: Num rows: 7200 Data size: 770400 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and (hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and hd_demo_sk is not null) (type: boolean) - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + predicate: ((((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (hd_dep_count) IN (3, 0, 1) and hd_demo_sk is not null) (type: boolean) + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: hd_demo_sk (type: int) outputColumnNames: _col0 - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Spark HashTable Sink Operator keys: 0 _col1 (type: int) @@ -1181,15 +1181,15 @@ STAGE PLANS: Map Operator Tree: TableScan alias: household_demographics - filterExpr: ((hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and (((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) + filterExpr: ((hd_dep_count) IN (3, 0, 1) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) Statistics: Num rows: 7200 Data size: 770400 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and (hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and hd_demo_sk is not null) (type: boolean) - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + predicate: ((((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (hd_dep_count) IN (3, 0, 1) and hd_demo_sk is not null) (type: boolean) + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: hd_demo_sk (type: int) outputColumnNames: _col0 - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Spark HashTable Sink Operator keys: 0 _col1 (type: int) @@ -1246,15 +1246,15 @@ STAGE PLANS: Map Operator Tree: TableScan alias: household_demographics - filterExpr: ((hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and (((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) + filterExpr: ((hd_dep_count) IN (3, 0, 1) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) Statistics: Num rows: 7200 Data size: 770400 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and (hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and hd_demo_sk is not null) (type: boolean) - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + predicate: ((((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (hd_dep_count) IN (3, 0, 1) and hd_demo_sk is not null) (type: boolean) + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: hd_demo_sk (type: int) outputColumnNames: _col0 - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Spark HashTable Sink Operator keys: 0 _col1 (type: int) @@ -1311,15 +1311,15 @@ STAGE PLANS: Map Operator Tree: TableScan alias: household_demographics - filterExpr: ((hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and (((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) + filterExpr: ((hd_dep_count) IN (3, 0, 1) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and hd_demo_sk is not null) (type: boolean) Statistics: Num rows: 7200 Data size: 770400 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and (hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and hd_demo_sk is not null) (type: boolean) - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + predicate: ((((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (hd_dep_count) IN (3, 0, 1) and hd_demo_sk is not null) (type: boolean) + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: hd_demo_sk (type: int) outputColumnNames: _col0 - Statistics: Num rows: 2000 Data size: 214000 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 3600 Data size: 385200 Basic stats: COMPLETE Column stats: NONE Spark HashTable Sink Operator keys: 0 _col1 (type: int) diff --git ql/src/test/results/clientpositive/perf/spark/query89.q.out ql/src/test/results/clientpositive/perf/spark/query89.q.out index 40a698aadf..00e78635ae 100644 --- ql/src/test/results/clientpositive/perf/spark/query89.q.out +++ ql/src/test/results/clientpositive/perf/spark/query89.q.out @@ -260,7 +260,7 @@ STAGE PLANS: outputColumnNames: avg_window_0, _col0, _col1, _col2, _col3, _col4, _col5, _col6 Statistics: Num rows: 383325119 Data size: 33817053293 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((avg_window_0 <> 0)) THEN (((abs((_col6 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (null) END (type: boolean) + predicate: CASE WHEN ((avg_window_0 <> 0)) THEN (((abs((_col6 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (false) END (type: boolean) Statistics: Num rows: 191662559 Data size: 16908526602 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col2 (type: string), _col1 (type: string), _col0 (type: string), _col4 (type: string), _col5 (type: string), _col3 (type: int), _col6 (type: decimal(17,2)), avg_window_0 (type: decimal(21,6)), (_col6 - avg_window_0) (type: decimal(22,6)) diff --git ql/src/test/results/clientpositive/perf/spark/query97.q.out ql/src/test/results/clientpositive/perf/spark/query97.q.out index 1ace8e8ff5..0861fc4f79 100644 --- ql/src/test/results/clientpositive/perf/spark/query97.q.out +++ ql/src/test/results/clientpositive/perf/spark/query97.q.out @@ -192,7 +192,7 @@ STAGE PLANS: outputColumnNames: _col0, _col2 Statistics: Num rows: 348477374 Data size: 30742775095 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: CASE WHEN ((_col0 is not null and _col2 is null)) THEN (1) ELSE (0) END (type: int), CASE WHEN ((_col0 is null and _col2 is not null)) THEN (1) ELSE (0) END (type: int), CASE WHEN ((_col0 is not null and _col2 is not null)) THEN (1) ELSE (0) END (type: int) + expressions: CASE WHEN ((_col2 is null and _col0 is not null)) THEN (1) ELSE (0) END (type: int), CASE WHEN ((_col0 is null and _col2 is not null)) THEN (1) ELSE (0) END (type: int), CASE WHEN ((_col0 is not null and _col2 is not null)) THEN (1) ELSE (0) END (type: int) outputColumnNames: _col0, _col1, _col2 Statistics: Num rows: 348477374 Data size: 30742775095 Basic stats: COMPLETE Column stats: NONE Group By Operator diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query11.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query11.q.out index de0783be16..441255aebf 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query11.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query11.q.out @@ -159,8 +159,8 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(c_preferred_cust_flag=[$1]) - HiveJoin(condition=[AND(=($0, $5), CASE(CAST(IS NOT NULL($6)):BOOLEAN, CASE($9, >(/($4, $8), /($2, $6)), >(null, /($2, $6))), CASE($9, >(/($4, $8), null), null)))], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0], $f4=[$3], $f9=[$7]) + HiveJoin(condition=[AND(=($0, $5), CASE(CAST(IS NOT NULL($6)):BOOLEAN, CASE($9, >(/($4, $8), /($2, $6)), null), null))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(customer_id=[$0], c_preferred_cust_flag=[$3], year_total=[$7]) HiveAggregate(group=[{1, 2, 3, 4, 5, 6, 7}], agg#0=[sum($10)]) HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], c_customer_id=[$1], c_first_name=[$8], c_last_name=[$9], c_preferred_cust_flag=[$10], c_birth_country=[$14], c_login=[$15], c_email_address=[$16]) @@ -175,7 +175,7 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveJoin(condition=[=($2, $4)], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[=($2, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0], $f8=[$7]) + HiveProject(customer_id=[$0], year_total=[$7]) HiveAggregate(group=[{1, 2, 3, 4, 5, 6, 7}], agg#0=[sum($10)]) HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], c_customer_id=[$1], c_first_name=[$8], c_last_name=[$9], c_preferred_cust_flag=[$10], c_birth_country=[$14], c_login=[$15], c_email_address=[$16]) @@ -188,7 +188,7 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(d_date_sk=[$0]) HiveFilter(condition=[AND(=($6, 2002), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject($f0=[$0], $f9=[$7]) + HiveProject(customer_id=[$0], year_total=[$7]) HiveFilter(condition=[>($7, 0)]) HiveAggregate(group=[{1, 2, 3, 4, 5, 6, 7}], agg#0=[sum($10)]) HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query13.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query13.q.out index 19f3039781..569a35425a 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query13.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query13.q.out @@ -113,7 +113,7 @@ POSTHOOK: Input: default@store POSTHOOK: Input: default@store_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: -HiveProject($f0=[/(CAST($0):DOUBLE, $1)], $f1=[/($2, $3)], $f2=[/($4, $5)], $f3=[CAST($4):DECIMAL(17, 2)]) +HiveProject(_o__c0=[/(CAST($0):DOUBLE, $1)], _o__c1=[/($2, $3)], _o__c2=[/($4, $5)], _o__c3=[CAST($4):DECIMAL(17, 2)]) HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)], agg#2=[sum($22)], agg#3=[count($22)], agg#4=[sum($23)], agg#5=[count($23)]) HiveJoin(condition=[AND(=($0, $17), OR(AND($1, $2, $27, $12), AND($3, $4, $28, $13), AND($5, $6, $29, $13)))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(cd_demo_sk=[$0], ==[=($2, _UTF-16LE'M')], =2=[=($3, _UTF-16LE'4 yr Degree')], =3=[=($2, _UTF-16LE'D')], =4=[=($3, _UTF-16LE'Primary')], =5=[=($2, _UTF-16LE'U')], =6=[=($3, _UTF-16LE'Advanced Degree')]) @@ -135,7 +135,7 @@ HiveProject($f0=[/(CAST($0):DOUBLE, $1)], $f1=[/($2, $3)], $f2=[/($4, $5)], $f3= HiveProject(d_date_sk=[$0]) HiveFilter(condition=[AND(=($6, 2001), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject(ss_sold_date_sk=[$0], ss_cdemo_sk=[$4], ss_hdemo_sk=[$5], ss_addr_sk=[$6], ss_store_sk=[$7], ss_quantity=[$10], ss_ext_sales_price=[$15], ss_ext_wholesale_cost=[$16], BETWEEN=[BETWEEN(false, $22, 100, 200)], BETWEEN9=[BETWEEN(false, $22, 150, 300)], BETWEEN10=[BETWEEN(false, $22, 50, 250)], BETWEEN11=[BETWEEN(false, $13, 100, 150)], BETWEEN12=[BETWEEN(false, $13, 50, 100)], BETWEEN13=[BETWEEN(false, $13, 150, 200)]) - HiveFilter(condition=[AND(OR(BETWEEN(false, $13, 100, 150), BETWEEN(false, $13, 50, 100), BETWEEN(false, $13, 150, 200)), OR(BETWEEN(false, $22, 100, 200), BETWEEN(false, $22, 150, 300), BETWEEN(false, $22, 50, 250)), IS NOT NULL($7), IS NOT NULL($4), IS NOT NULL($5), IS NOT NULL($6), IS NOT NULL($0))]) + HiveProject(ss_sold_date_sk=[$0], ss_cdemo_sk=[$4], ss_hdemo_sk=[$5], ss_addr_sk=[$6], ss_store_sk=[$7], ss_quantity=[$10], ss_ext_sales_price=[$15], ss_ext_wholesale_cost=[$16], BETWEEN=[BETWEEN(false, $22, CAST(100):DECIMAL(12, 2), CAST(200):DECIMAL(12, 2))], BETWEEN9=[BETWEEN(false, $22, CAST(150):DECIMAL(12, 2), CAST(300):DECIMAL(12, 2))], BETWEEN10=[BETWEEN(false, $22, CAST(50):DECIMAL(12, 2), CAST(250):DECIMAL(12, 2))], BETWEEN11=[BETWEEN(false, $13, 100, 150)], BETWEEN12=[BETWEEN(false, $13, 50, 100)], BETWEEN13=[BETWEEN(false, $13, 150, 200)]) + HiveFilter(condition=[AND(OR(BETWEEN(false, $13, 100, 150), BETWEEN(false, $13, 50, 100), BETWEEN(false, $13, 150, 200)), OR(BETWEEN(false, $22, CAST(100):DECIMAL(12, 2), CAST(200):DECIMAL(12, 2)), BETWEEN(false, $22, CAST(150):DECIMAL(12, 2), CAST(300):DECIMAL(12, 2)), BETWEEN(false, $22, CAST(50):DECIMAL(12, 2), CAST(250):DECIMAL(12, 2))), IS NOT NULL($7), IS NOT NULL($4), IS NOT NULL($5), IS NOT NULL($6), IS NOT NULL($0))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query14.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query14.q.out index c09da86ce1..8bdd2825ba 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query14.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query14.q.out @@ -291,7 +291,7 @@ HiveSortLimit(sort0=[$0], sort1=[$1], sort2=[$2], sort3=[$3], dir0=[ASC], dir1=[ HiveProject(i_item_sk=[$0], i_brand_id=[$7], i_class_id=[$9], i_category_id=[$11]) HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($7), IS NOT NULL($9), IS NOT NULL($11))]) HiveTableScan(table=[[default, item]], table:alias=[iws]) - HiveProject($f0=[/($0, $1)]) + HiveProject(average_sales=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($0)], agg#1=[count($0)]) HiveProject($f0=[*(CAST($0):DECIMAL(10, 0), $1)]) HiveUnion(all=[true]) @@ -385,7 +385,7 @@ HiveSortLimit(sort0=[$0], sort1=[$1], sort2=[$2], sort3=[$3], dir0=[ASC], dir1=[ HiveProject(i_item_sk=[$0], i_brand_id=[$7], i_class_id=[$9], i_category_id=[$11]) HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($7), IS NOT NULL($9), IS NOT NULL($11))]) HiveTableScan(table=[[default, item]], table:alias=[iws]) - HiveProject($f0=[/($0, $1)]) + HiveProject(average_sales=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($0)], agg#1=[count($0)]) HiveProject($f0=[*(CAST($0):DECIMAL(10, 0), $1)]) HiveUnion(all=[true]) @@ -479,7 +479,7 @@ HiveSortLimit(sort0=[$0], sort1=[$1], sort2=[$2], sort3=[$3], dir0=[ASC], dir1=[ HiveProject(i_item_sk=[$0], i_brand_id=[$7], i_class_id=[$9], i_category_id=[$11]) HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($7), IS NOT NULL($9), IS NOT NULL($11))]) HiveTableScan(table=[[default, item]], table:alias=[iws]) - HiveProject($f0=[/($0, $1)]) + HiveProject(average_sales=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($0)], agg#1=[count($0)]) HiveProject($f0=[*(CAST($0):DECIMAL(10, 0), $1)]) HiveUnion(all=[true]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query16.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query16.q.out index e7d1199638..5e19d15eb1 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query16.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query16.q.out @@ -89,7 +89,7 @@ HiveProject(order count=[$0], total shipping cost=[$1], total net profit=[$2]) HiveFilter(condition=[AND(IS NOT NULL($2), IS NOT NULL($10), IS NOT NULL($11), IS NOT NULL($17))]) HiveTableScan(table=[[default, catalog_sales]], table:alias=[cs1]) HiveProject(d_date_sk=[$0], d_date=[$2]) - HiveFilter(condition=[AND(BETWEEN(false, CAST($2):TIMESTAMP(9), 2001-04-01 00:00:00, 2001-05-31 00:00:00), IS NOT NULL($0))]) + HiveFilter(condition=[AND(BETWEEN(false, CAST($2):TIMESTAMP(9), CAST(_UTF-16LE'2001-4-01'):TIMESTAMP(9), 2001-05-31 00:00:00), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(cc_call_center_sk=[$0], cc_county=[$25]) HiveFilter(condition=[AND(IN($25, _UTF-16LE'Ziebach County', _UTF-16LE'Levy County', _UTF-16LE'Huron County', _UTF-16LE'Franklin Parish', _UTF-16LE'Daviess County'), IS NOT NULL($0))]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query18.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query18.q.out index ebeb13b0ee..70c2bc84e7 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query18.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query18.q.out @@ -80,7 +80,7 @@ POSTHOOK: Input: default@item POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$1], sort1=[$2], sort2=[$3], sort3=[$0], dir0=[ASC], dir1=[ASC], dir2=[ASC], dir3=[ASC], fetch=[100]) - HiveProject($f0=[$3], $f1=[$2], $f2=[$1], $f3=[$0], $f4=[/($4, $5)], $f5=[/($6, $7)], $f6=[/($8, $9)], $f7=[/($10, $11)], $f8=[/($12, $13)], $f9=[/($14, $15)], $f10=[/($16, $17)]) + HiveProject(i_item_id=[$3], ca_country=[$2], ca_state=[$1], ca_county=[$0], agg1=[/($4, $5)], agg2=[/($6, $7)], agg3=[/($8, $9)], agg4=[/($10, $11)], agg5=[/($12, $13)], agg6=[/($14, $15)], agg7=[/($16, $17)]) HiveAggregate(group=[{5, 6, 7, 10}], groups=[[{5, 6, 7, 10}, {6, 7, 10}, {7, 10}, {10}, {}]], agg#0=[sum($15)], agg#1=[count($15)], agg#2=[sum($16)], agg#3=[count($16)], agg#4=[sum($17)], agg#5=[count($17)], agg#6=[sum($18)], agg#7=[count($18)], agg#8=[sum($19)], agg#9=[count($19)], agg#10=[sum($3)], agg#11=[count($3)], agg#12=[sum($22)], agg#13=[count($22)]) HiveJoin(condition=[=($12, $0)], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[=($1, $8)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query21.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query21.q.out index 3a675034ef..bf24236d57 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query21.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query21.q.out @@ -69,7 +69,7 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], sort1=[$1], dir0=[ASC], dir1=[ASC], fetch=[100]) HiveProject($f0=[$0], $f1=[$1], $f2=[$2], $f3=[$3]) - HiveFilter(condition=[CASE(>($2, 0), BETWEEN(false, /(CAST($3):DOUBLE, CAST($2):DOUBLE), 6.66667E-1, 1.5E0), null)]) + HiveFilter(condition=[CASE(>($2, 0), BETWEEN(false, /(CAST($3):DOUBLE, CAST($2):DOUBLE), 6.66667E-1, 1.5E0), false)]) HiveAggregate(group=[{0, 1}], agg#0=[sum($2)], agg#1=[sum($3)]) HiveProject($f0=[$1], $f1=[$10], $f2=[CASE($7, $5, 0)], $f3=[CASE($8, $5, 0)]) HiveJoin(condition=[=($4, $0)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query22.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query22.q.out index 7231d6e16d..ab662ae34d 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query22.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query22.q.out @@ -52,7 +52,7 @@ POSTHOOK: Input: default@warehouse POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$4], sort1=[$0], sort2=[$1], sort3=[$2], sort4=[$3], dir0=[ASC], dir1=[ASC], dir2=[ASC], dir3=[ASC], dir4=[ASC], fetch=[100]) - HiveProject($f0=[$3], $f1=[$0], $f2=[$1], $f3=[$2], $f4=[/(CAST($4):DOUBLE, $5)]) + HiveProject(i_product_name=[$3], i_brand=[$0], i_class=[$1], i_category=[$2], qoh=[/(CAST($4):DOUBLE, $5)]) HiveAggregate(group=[{1, 2, 3, 4}], groups=[[{1, 2, 3, 4}, {1, 2, 4}, {1, 4}, {4}, {}]], agg#0=[sum($8)], agg#1=[count($8)]) HiveJoin(condition=[=($6, $0)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(i_item_sk=[$0], i_brand=[$8], i_class=[$10], i_category=[$12], i_product_name=[$21]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query23.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query23.q.out index 4019b26f17..907059f25f 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query23.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query23.q.out @@ -126,7 +126,7 @@ HiveSortLimit(fetch=[100]) HiveUnion(all=[true]) HiveProject(sales=[*(CAST($5):DECIMAL(10, 0), $6)]) HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0]) + HiveProject(c_customer_sk=[$0]) HiveJoin(condition=[>($1, *(0.95, $3))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], $f1=[$1]) HiveAggregate(group=[{2}], agg#0=[sum($1)]) @@ -199,7 +199,7 @@ HiveSortLimit(fetch=[100]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(sales=[*(CAST($5):DECIMAL(10, 0), $6)]) HiveJoin(condition=[=($4, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0]) + HiveProject(c_customer_sk=[$0]) HiveJoin(condition=[>($1, *(0.95, $3))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], $f1=[$1]) HiveAggregate(group=[{2}], agg#0=[sum($1)]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query24.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query24.q.out index 3add88ad25..57eb10a859 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query24.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query24.q.out @@ -114,7 +114,7 @@ POSTHOOK: Input: default@store_returns POSTHOOK: Input: default@store_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: -HiveProject($f0=[$0], $f1=[$1], $f2=[$2], $f3=[$3]) +HiveProject(c_last_name=[$0], c_first_name=[$1], s_store_name=[$2], paid=[$3]) HiveJoin(condition=[>($3, $4)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_last_name=[$1], c_first_name=[$0], s_store_name=[$2], $f3=[$3]) HiveAggregate(group=[{4, 5, 7}], agg#0=[sum($9)]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query26.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query26.q.out index 9f51402caf..d84a7cb826 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query26.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query26.q.out @@ -52,7 +52,7 @@ POSTHOOK: Input: default@promotion POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) - HiveProject($f0=[$0], $f1=[/(CAST($1):DOUBLE, $2)], $f2=[/($3, $4)], $f3=[/($5, $6)], $f4=[/($7, $8)]) + HiveProject(i_item_id=[$0], agg1=[/(CAST($1):DOUBLE, $2)], agg2=[/($3, $4)], agg3=[/($5, $6)], agg4=[/($7, $8)]) HiveAggregate(group=[{1}], agg#0=[sum($6)], agg#1=[count($6)], agg#2=[sum($7)], agg#3=[count($7)], agg#4=[sum($9)], agg#5=[count($9)], agg#6=[sum($8)], agg#7=[count($8)]) HiveJoin(condition=[=($4, $0)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(i_item_sk=[$0], i_item_id=[$1]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query28.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query28.q.out index 643e5b6259..14cfaf2c34 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query28.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query28.q.out @@ -113,34 +113,34 @@ POSTHOOK: Input: default@store_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(fetch=[100]) - HiveProject($f0=[$0], $f1=[$1], $f2=[$2], $f00=[$15], $f10=[$16], $f20=[$17], $f01=[$12], $f11=[$13], $f21=[$14], $f02=[$9], $f12=[$10], $f22=[$11], $f03=[$6], $f13=[$7], $f23=[$8], $f04=[$3], $f14=[$4], $f24=[$5]) + HiveProject(b1_lp=[$0], b1_cnt=[$1], b1_cntd=[$2], b2_lp=[$15], b2_cnt=[$16], b2_cntd=[$17], b3_lp=[$12], b3_cnt=[$13], b3_cntd=[$14], b4_lp=[$9], b4_cnt=[$10], b4_cntd=[$11], b5_lp=[$6], b5_cnt=[$7], b5_cntd=[$8], b6_lp=[$3], b6_cnt=[$4], b6_cntd=[$5]) HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[/($0, $1)], $f1=[$1], $f2=[$2]) + HiveProject(b1_lp=[/($0, $1)], b1_cnt=[$1], b1_cntd=[$2]) HiveAggregate(group=[{}], agg#0=[sum($12)], agg#1=[count($12)], agg#2=[count(DISTINCT $12)]) - HiveFilter(condition=[AND(BETWEEN(false, $10, 0, 5), OR(BETWEEN(false, $12, 11, 21), BETWEEN(false, $19, 460, 1460), BETWEEN(false, $11, 14, 34)))]) + HiveFilter(condition=[AND(BETWEEN(false, $10, 0, 5), OR(BETWEEN(false, $12, CAST(11):DECIMAL(12, 2), 21), BETWEEN(false, $19, CAST(460):DECIMAL(12, 2), 1460), BETWEEN(false, $11, CAST(14):DECIMAL(12, 2), 34)))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)], $f1=[$1], $f2=[$2]) + HiveProject(b6_lp=[/($0, $1)], b6_cnt=[$1], b6_cntd=[$2]) HiveAggregate(group=[{}], agg#0=[sum($12)], agg#1=[count($12)], agg#2=[count(DISTINCT $12)]) - HiveFilter(condition=[AND(BETWEEN(false, $10, 26, 30), OR(BETWEEN(false, $12, 28, 38), BETWEEN(false, $19, 2513, 3513), BETWEEN(false, $11, 42, 62)))]) + HiveFilter(condition=[AND(BETWEEN(false, $10, 26, 30), OR(BETWEEN(false, $12, CAST(28):DECIMAL(12, 2), 38), BETWEEN(false, $19, CAST(2513):DECIMAL(12, 2), 3513), BETWEEN(false, $11, CAST(42):DECIMAL(12, 2), 62)))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)], $f1=[$1], $f2=[$2]) + HiveProject(b5_lp=[/($0, $1)], b5_cnt=[$1], b5_cntd=[$2]) HiveAggregate(group=[{}], agg#0=[sum($12)], agg#1=[count($12)], agg#2=[count(DISTINCT $12)]) - HiveFilter(condition=[AND(BETWEEN(false, $10, 21, 25), OR(BETWEEN(false, $12, 135, 145), BETWEEN(false, $19, 14180, 15180), BETWEEN(false, $11, 38, 58)))]) + HiveFilter(condition=[AND(BETWEEN(false, $10, 21, 25), OR(BETWEEN(false, $12, CAST(135):DECIMAL(12, 2), 145), BETWEEN(false, $19, CAST(14180):DECIMAL(12, 2), 15180), BETWEEN(false, $11, CAST(38):DECIMAL(12, 2), 58)))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)], $f1=[$1], $f2=[$2]) + HiveProject(b4_lp=[/($0, $1)], b4_cnt=[$1], b4_cntd=[$2]) HiveAggregate(group=[{}], agg#0=[sum($12)], agg#1=[count($12)], agg#2=[count(DISTINCT $12)]) - HiveFilter(condition=[AND(BETWEEN(false, $10, 16, 20), OR(BETWEEN(false, $12, 142, 152), BETWEEN(false, $19, 3054, 4054), BETWEEN(false, $11, 80, 100)))]) + HiveFilter(condition=[AND(BETWEEN(false, $10, 16, 20), OR(BETWEEN(false, $12, CAST(142):DECIMAL(12, 2), 152), BETWEEN(false, $19, CAST(3054):DECIMAL(12, 2), 4054), BETWEEN(false, $11, CAST(80):DECIMAL(12, 2), 100)))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)], $f1=[$1], $f2=[$2]) + HiveProject(b3_lp=[/($0, $1)], b3_cnt=[$1], b3_cntd=[$2]) HiveAggregate(group=[{}], agg#0=[sum($12)], agg#1=[count($12)], agg#2=[count(DISTINCT $12)]) - HiveFilter(condition=[AND(BETWEEN(false, $10, 11, 15), OR(BETWEEN(false, $12, 66, 76), BETWEEN(false, $19, 920, 1920), BETWEEN(false, $11, 4, 24)))]) + HiveFilter(condition=[AND(BETWEEN(false, $10, 11, 15), OR(BETWEEN(false, $12, CAST(66):DECIMAL(12, 2), 76), BETWEEN(false, $19, CAST(920):DECIMAL(12, 2), 1920), BETWEEN(false, $11, CAST(4):DECIMAL(12, 2), 24)))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)], $f1=[$1], $f2=[$2]) + HiveProject(b2_lp=[/($0, $1)], b2_cnt=[$1], b2_cntd=[$2]) HiveAggregate(group=[{}], agg#0=[sum($12)], agg#1=[count($12)], agg#2=[count(DISTINCT $12)]) - HiveFilter(condition=[AND(BETWEEN(false, $10, 6, 10), OR(BETWEEN(false, $12, 91, 101), BETWEEN(false, $19, 1430, 2430), BETWEEN(false, $11, 32, 52)))]) + HiveFilter(condition=[AND(BETWEEN(false, $10, 6, 10), OR(BETWEEN(false, $12, CAST(91):DECIMAL(12, 2), 101), BETWEEN(false, $19, CAST(1430):DECIMAL(12, 2), 2430), BETWEEN(false, $11, CAST(32):DECIMAL(12, 2), 52)))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query31.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query31.q.out index 8907b8d6cd..a275e868dc 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query31.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query31.q.out @@ -112,7 +112,7 @@ POSTHOOK: Input: default@web_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveProject(ca_county=[$8], d_year=[CAST(2000):INTEGER], web_q1_q2_increase=[/($6, $1)], store_q1_q2_increase=[/($9, $11)], web_q2_q3_increase=[/($4, $6)], store_q2_q3_increase=[/($13, $9)]) - HiveJoin(condition=[AND(AND(=($8, $0), CASE(>($11, 0), CASE($2, >(/($6, $1), /($9, $11)), >(null, /($9, $11))), CASE($2, >(/($6, $1), null), null))), CASE(>($9, 0), CASE($7, >(/($4, $6), /($13, $9)), >(null, /($13, $9))), CASE($7, >(/($4, $6), null), null)))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[AND(AND(=($8, $0), CASE(>($11, 0), CASE($2, >(/($6, $1), /($9, $11)), null), null)), CASE(>($9, 0), CASE($7, >(/($4, $6), /($13, $9)), null), null))], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[=($0, $5)], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject($f0=[$0], $f3=[$1], >=[>($1, 0)]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query32.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query32.q.out index 837a743154..e07877c86c 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query32.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query32.q.out @@ -70,7 +70,7 @@ HiveSortLimit(fetch=[100]) HiveFilter(condition=[AND(IS NOT NULL($15), IS NOT NULL($0))]) HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales]) HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[AND(BETWEEN(false, CAST($2):TIMESTAMP(9), 1998-03-18 00:00:00, 1998-06-16 00:00:00), IS NOT NULL($0))]) + HiveFilter(condition=[AND(BETWEEN(false, CAST($2):TIMESTAMP(9), CAST(_UTF-16LE'1998-03-18'):TIMESTAMP(9), 1998-06-16 00:00:00), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(cs_item_sk=[$0], CAST=[$1], i_item_sk=[$2]) HiveJoin(condition=[=($0, $2)], joinType=[inner], algorithm=[none], cost=[not available]) @@ -81,7 +81,7 @@ HiveSortLimit(fetch=[100]) HiveFilter(condition=[AND(IS NOT NULL($15), IS NOT NULL($0))]) HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales]) HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[AND(BETWEEN(false, CAST($2):TIMESTAMP(9), 1998-03-18 00:00:00, 1998-06-16 00:00:00), IS NOT NULL($0))]) + HiveFilter(condition=[AND(BETWEEN(false, CAST($2):TIMESTAMP(9), CAST(_UTF-16LE'1998-03-18'):TIMESTAMP(9), 1998-06-16 00:00:00), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(i_item_sk=[$0]) HiveFilter(condition=[AND(=($13, 269), IS NOT NULL($0))]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query34.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query34.q.out index 9299409a89..07edffe7f7 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query34.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query34.q.out @@ -78,7 +78,7 @@ HiveSortLimit(sort0=[$0], sort1=[$1], sort2=[$2], sort3=[$3], dir0=[ASC], dir1=[ HiveFilter(condition=[IS NOT NULL($0)]) HiveTableScan(table=[[default, customer]], table:alias=[customer]) HiveProject(ss_ticket_number=[$0], ss_customer_sk=[$1], $f2=[$2]) - HiveFilter(condition=[BETWEEN(false, $2, 15, 20)]) + HiveFilter(condition=[BETWEEN(false, $2, CAST(15):BIGINT, CAST(20):BIGINT)]) HiveProject(ss_ticket_number=[$1], ss_customer_sk=[$0], $f2=[$2]) HiveAggregate(group=[{1, 4}], agg#0=[count()]) HiveJoin(condition=[=($3, $7)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query36.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query36.q.out index 9a74bed470..be191124a4 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query36.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query36.q.out @@ -69,7 +69,7 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveProject(gross_margin=[$0], i_category=[$1], i_class=[$2], lochierarchy=[$3], rank_within_parent=[$4]) HiveSortLimit(sort0=[$3], sort1=[$5], sort2=[$4], dir0=[DESC-nulls-last], dir1=[ASC], dir2=[ASC], fetch=[100]) - HiveProject(gross_margin=[/($2, $3)], i_category=[$0], i_class=[$1], lochierarchy=[+(grouping($4, 1), grouping($4, 0))], rank_within_parent=[rank() OVER (PARTITION BY +(grouping($4, 1), grouping($4, 0)), CASE(=(grouping($4, 0), 0), $0, null) ORDER BY /($2, $3) NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)], (tok_function when (= (tok_table_or_col lochierarchy) 0) (tok_table_or_col i_category))=[CASE(=(+(grouping($4, 1), grouping($4, 0)), 0), $0, null)]) + HiveProject(gross_margin=[/($2, $3)], i_category=[$0], i_class=[$1], lochierarchy=[+(grouping($4, 1), grouping($4, 0))], rank_within_parent=[rank() OVER (PARTITION BY +(grouping($4, 1), grouping($4, 0)), CASE(=(grouping($4, 0), CAST(0):BIGINT), $0, null) ORDER BY /($2, $3) NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)], (tok_function when (= (tok_table_or_col lochierarchy) 0) (tok_table_or_col i_category))=[CASE(=(+(grouping($4, 1), grouping($4, 0)), 0), $0, null)]) HiveProject($f0=[$0], $f1=[$1], $f2=[$2], $f3=[$3], GROUPING__ID=[$4]) HiveAggregate(group=[{0, 1}], groups=[[{0, 1}, {0}, {}]], agg#0=[sum($2)], agg#1=[sum($3)], GROUPING__ID=[GROUPING__ID()]) HiveProject($f0=[$9], $f1=[$8], $f2=[$4], $f3=[$3]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query37.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query37.q.out index 07b9901520..c0180ab88b 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query37.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query37.q.out @@ -50,7 +50,7 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveFilter(condition=[IS NOT NULL($15)]) HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales]) HiveProject(i_item_sk=[$0], i_item_id=[$1], i_item_desc=[$4], i_current_price=[$5]) - HiveFilter(condition=[AND(IN($13, 678, 964, 918, 849), BETWEEN(false, $5, 22, 52), IS NOT NULL($0))]) + HiveFilter(condition=[AND(IN($13, 678, 964, 918, 849), BETWEEN(false, $5, CAST(22):DECIMAL(12, 2), 52), IS NOT NULL($0))]) HiveTableScan(table=[[default, item]], table:alias=[item]) HiveProject(inv_date_sk=[$0], inv_item_sk=[$1], d_date_sk=[$2]) HiveJoin(condition=[=($2, $0)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query4.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query4.q.out index 4b388653ae..0056d35c56 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query4.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query4.q.out @@ -229,8 +229,8 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(customer_preferred_cust_flag=[$1]) - HiveJoin(condition=[AND(=($0, $7), CASE(CAST(IS NOT NULL($8)):BOOLEAN, CASE($14, >(/($4, $13), /($2, $8)), >(null, /($2, $8))), CASE($14, >(/($4, $13), null), null)))], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0], $f3=[$3], $f8=[$7]) + HiveJoin(condition=[AND(=($0, $7), CASE(CAST(IS NOT NULL($8)):BOOLEAN, CASE($14, >(/($4, $13), /($2, $8)), null), null))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(customer_id=[$0], customer_preferred_cust_flag=[$3], year_total=[$7]) HiveAggregate(group=[{1, 2, 3, 4, 5, 6, 7}], agg#0=[sum($10)]) HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], c_customer_id=[$1], c_first_name=[$8], c_last_name=[$9], c_preferred_cust_flag=[$10], c_birth_country=[$14], c_login=[$15], c_email_address=[$16]) @@ -243,8 +243,8 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(d_date_sk=[$0]) HiveFilter(condition=[AND(=($6, 2002), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveJoin(condition=[AND(=($4, $0), CASE($8, CASE($11, >(/($1, $10), /($3, $7)), >(null, /($3, $7))), CASE($11, >(/($1, $10), null), null)))], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0], $f8=[$7]) + HiveJoin(condition=[AND(=($4, $0), CASE($8, CASE($11, >(/($1, $10), /($3, $7)), null), null))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(customer_id=[$0], year_total=[$7]) HiveAggregate(group=[{1, 2, 3, 4, 5, 6, 7}], agg#0=[sum($10)]) HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], c_customer_id=[$1], c_first_name=[$8], c_last_name=[$9], c_preferred_cust_flag=[$10], c_birth_country=[$14], c_login=[$15], c_email_address=[$16]) @@ -260,7 +260,7 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveJoin(condition=[=($2, $7)], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[=($2, $4)], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[=($2, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0], $f8=[$7]) + HiveProject(customer_id=[$0], year_total=[$7]) HiveAggregate(group=[{1, 2, 3, 4, 5, 6, 7}], agg#0=[sum($10)]) HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], c_customer_id=[$1], c_first_name=[$8], c_last_name=[$9], c_preferred_cust_flag=[$10], c_birth_country=[$14], c_login=[$15], c_email_address=[$16]) @@ -273,7 +273,7 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(d_date_sk=[$0]) HiveFilter(condition=[AND(=($6, 2002), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject($f0=[$0], $f8=[$7]) + HiveProject(customer_id=[$0], year_total=[$7]) HiveFilter(condition=[>($7, 0)]) HiveAggregate(group=[{1, 2, 3, 4, 5, 6, 7}], agg#0=[sum($10)]) HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query42.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query42.q.out index 0a7dac0336..773193df12 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query42.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query42.q.out @@ -49,20 +49,19 @@ POSTHOOK: Input: default@item POSTHOOK: Input: default@store_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: -HiveSortLimit(fetch=[100]) - HiveProject(d_year=[CAST(1998):INTEGER], i_category_id=[$0], i_category=[$1], _o__c3=[$2]) - HiveSortLimit(sort0=[$3], sort1=[$0], sort2=[$1], dir0=[DESC-nulls-last], dir1=[ASC], dir2=[ASC]) - HiveProject(i_category_id=[$0], i_category=[$1], _o__c3=[$2], (tok_function sum (tok_table_or_col ss_ext_sales_price))=[$2]) - HiveAggregate(group=[{5, 6}], agg#0=[sum($2)]) - HiveJoin(condition=[=($1, $4)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_ext_sales_price=[$15]) - HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($2))]) - HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[AND(=($8, 12), =($6, 1998), IS NOT NULL($0))]) - HiveTableScan(table=[[default, date_dim]], table:alias=[dt]) - HiveProject(i_item_sk=[$0], i_category_id=[$11], i_category=[$12]) - HiveFilter(condition=[AND(=($20, 1), IS NOT NULL($0))]) - HiveTableScan(table=[[default, item]], table:alias=[item]) +HiveProject(d_year=[CAST(1998):INTEGER], i_category_id=[$0], i_category=[$1], _o__c3=[$2]) + HiveSortLimit(sort0=[$3], sort1=[$0], sort2=[$1], dir0=[DESC-nulls-last], dir1=[ASC], dir2=[ASC], fetch=[100]) + HiveProject(i_category_id=[$0], i_category=[$1], _o__c3=[$2], (tok_function sum (tok_table_or_col ss_ext_sales_price))=[$2]) + HiveAggregate(group=[{5, 6}], agg#0=[sum($2)]) + HiveJoin(condition=[=($1, $4)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_ext_sales_price=[$15]) + HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($2))]) + HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) + HiveProject(d_date_sk=[$0]) + HiveFilter(condition=[AND(=($8, 12), =($6, 1998), IS NOT NULL($0))]) + HiveTableScan(table=[[default, date_dim]], table:alias=[dt]) + HiveProject(i_item_sk=[$0], i_category_id=[$11], i_category=[$12]) + HiveFilter(condition=[AND(=($20, 1), IS NOT NULL($0))]) + HiveTableScan(table=[[default, item]], table:alias=[item]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query48.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query48.q.out index 079556ec99..e9ca4556e3 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query48.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query48.q.out @@ -158,7 +158,7 @@ HiveAggregate(group=[{}], agg#0=[sum($11)]) HiveProject(cd_demo_sk=[$0]) HiveFilter(condition=[AND(=($2, _UTF-16LE'M'), =($3, _UTF-16LE'4 yr Degree'), IS NOT NULL($0))]) HiveTableScan(table=[[default, customer_demographics]], table:alias=[customer_demographics]) - HiveProject(ss_sold_date_sk=[$0], ss_cdemo_sk=[$4], ss_addr_sk=[$6], ss_store_sk=[$7], ss_quantity=[$10], BETWEEN=[BETWEEN(false, $22, 0, 2000)], BETWEEN6=[BETWEEN(false, $22, 150, 3000)], BETWEEN7=[BETWEEN(false, $22, 50, 25000)]) - HiveFilter(condition=[AND(OR(BETWEEN(false, $13, 100, 150), BETWEEN(false, $13, 50, 100), BETWEEN(false, $13, 150, 200)), OR(BETWEEN(false, $22, 0, 2000), BETWEEN(false, $22, 150, 3000), BETWEEN(false, $22, 50, 25000)), IS NOT NULL($7), IS NOT NULL($4), IS NOT NULL($6), IS NOT NULL($0))]) + HiveProject(ss_sold_date_sk=[$0], ss_cdemo_sk=[$4], ss_addr_sk=[$6], ss_store_sk=[$7], ss_quantity=[$10], BETWEEN=[BETWEEN(false, $22, CAST(0):DECIMAL(12, 2), CAST(2000):DECIMAL(12, 2))], BETWEEN6=[BETWEEN(false, $22, CAST(150):DECIMAL(12, 2), CAST(3000):DECIMAL(12, 2))], BETWEEN7=[BETWEEN(false, $22, CAST(50):DECIMAL(12, 2), CAST(25000):DECIMAL(12, 2))]) + HiveFilter(condition=[AND(OR(BETWEEN(false, $13, 100, 150), BETWEEN(false, $13, 50, 100), BETWEEN(false, $13, 150, 200)), OR(BETWEEN(false, $22, CAST(0):DECIMAL(12, 2), CAST(2000):DECIMAL(12, 2)), BETWEEN(false, $22, CAST(150):DECIMAL(12, 2), CAST(3000):DECIMAL(12, 2)), BETWEEN(false, $22, CAST(50):DECIMAL(12, 2), CAST(25000):DECIMAL(12, 2))), IS NOT NULL($7), IS NOT NULL($4), IS NOT NULL($6), IS NOT NULL($0))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query51.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query51.q.out index 79c5f992ce..b4da9ca947 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query51.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query51.q.out @@ -100,8 +100,8 @@ HiveSortLimit(sort0=[$0], sort1=[$1], dir0=[ASC], dir1=[ASC], fetch=[100]) HiveFilter(condition=[>($4, $5)]) HiveProject(item_sk=[CASE(IS NOT NULL($3), $3, $0)], d_date=[CASE(IS NOT NULL($4), $4, $1)], web_sales=[$5], store_sales=[$2], max_window_0=[max($5) OVER (PARTITION BY CASE(IS NOT NULL($3), $3, $0) ORDER BY CASE(IS NOT NULL($4), $4, $1) NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)], max_window_1=[max($2) OVER (PARTITION BY CASE(IS NOT NULL($3), $3, $0) ORDER BY CASE(IS NOT NULL($4), $4, $1) NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)]) HiveJoin(condition=[AND(=($3, $0), =($4, $1))], joinType=[full], algorithm=[none], cost=[not available]) - HiveProject((tok_table_or_col ss_item_sk)=[$0], (tok_table_or_col d_date)=[$1], sum_window_0=[$2]) - HiveProject((tok_table_or_col ss_item_sk)=[$0], (tok_table_or_col d_date)=[$1], sum_window_0=[sum($2) OVER (PARTITION BY $0 ORDER BY $1 NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)], window_col_0=[$2]) + HiveProject(item_sk=[$0], d_date=[$1], cume_sales=[$2]) + HiveProject(item_sk=[$0], d_date=[$1], cume_sales=[sum($2) OVER (PARTITION BY $0 ORDER BY $1 NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)], window_col_0=[$2]) HiveProject(ss_item_sk=[$0], d_date=[$1], $f2=[$2]) HiveAggregate(group=[{1, 4}], agg#0=[sum($2)]) HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) @@ -111,8 +111,8 @@ HiveSortLimit(sort0=[$0], sort1=[$1], dir0=[ASC], dir1=[ASC], fetch=[100]) HiveProject(d_date_sk=[$0], d_date=[$2]) HiveFilter(condition=[AND(BETWEEN(false, $3, 1212, 1223), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject((tok_table_or_col ws_item_sk)=[$0], (tok_table_or_col d_date)=[$1], sum_window_0=[$2]) - HiveProject((tok_table_or_col ws_item_sk)=[$0], (tok_table_or_col d_date)=[$1], sum_window_0=[sum($2) OVER (PARTITION BY $0 ORDER BY $1 NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)], window_col_0=[$2]) + HiveProject(item_sk=[$0], d_date=[$1], cume_sales=[$2]) + HiveProject(item_sk=[$0], d_date=[$1], cume_sales=[sum($2) OVER (PARTITION BY $0 ORDER BY $1 NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)], window_col_0=[$2]) HiveProject(ws_item_sk=[$0], d_date=[$1], $f2=[$2]) HiveAggregate(group=[{1, 4}], agg#0=[sum($2)]) HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query53.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query53.q.out index 9b42428097..e90a0ee169 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query53.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query53.q.out @@ -65,7 +65,7 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$2], sort1=[$1], sort2=[$0], dir0=[ASC], dir1=[ASC], dir2=[ASC], fetch=[100]) HiveProject((tok_table_or_col i_manufact_id)=[$0], (tok_function sum (tok_table_or_col ss_sales_price))=[$1], avg_window_0=[$2]) - HiveFilter(condition=[CASE(>($2, 0), >(/(ABS(-($1, $2)), $2), 0.1), null)]) + HiveFilter(condition=[CASE(>($2, 0), >(/(ABS(-($1, $2)), $2), 0.1), false)]) HiveProject((tok_table_or_col i_manufact_id)=[$0], (tok_function sum (tok_table_or_col ss_sales_price))=[$2], avg_window_0=[avg($2) OVER (PARTITION BY $0 ORDER BY $0 NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)]) HiveProject(i_manufact_id=[$0], d_qoy=[$1], $f2=[$2]) HiveAggregate(group=[{6, 8}], agg#0=[sum($4)]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query54.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query54.q.out index 50fa078159..918935765d 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query54.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query54.q.out @@ -134,7 +134,7 @@ CBO PLAN: HiveSortLimit(sort0=[$0], sort1=[$1], dir0=[ASC], dir1=[ASC], fetch=[100]) HiveProject(segment=[$0], num_customers=[$1], segment_base=[*($0, 50)]) HiveAggregate(group=[{0}], agg#0=[count()]) - HiveProject(segment=[CAST(/($1, CAST(50):DECIMAL(10, 0))):INTEGER]) + HiveProject($f0=[CAST(/($1, CAST(50):DECIMAL(10, 0))):INTEGER]) HiveAggregate(group=[{0}], agg#0=[sum($1)]) HiveFilter(condition=[BETWEEN(false, $2, $3, $4)]) HiveProject(c_customer_sk=[$0], ss_ext_sales_price=[$4], d_month_seq=[$11], _o__c0=[$13], $f0=[$14]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query6.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query6.q.out index f502c004cf..dbd946f22d 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query6.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query6.q.out @@ -94,7 +94,7 @@ HiveSortLimit(sort0=[$1], dir0=[ASC], fetch=[100]) HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($12))]) HiveTableScan(table=[[default, item]], table:alias=[i]) HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(i_category=[$0], *=[*(1.2, CAST(/($1, $2)):DECIMAL(16, 6))]) + HiveProject(i_category=[$0], *=[*(1.2, CASE(false, null, /($1, $2)))]) HiveAggregate(group=[{12}], agg#0=[sum($5)], agg#1=[count($5)]) HiveFilter(condition=[IS NOT NULL($12)]) HiveTableScan(table=[[default, item]], table:alias=[j]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query63.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query63.q.out index 78c9b13111..3152a13ef2 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query63.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query63.q.out @@ -67,7 +67,7 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], sort1=[$2], sort2=[$1], dir0=[ASC], dir1=[ASC], dir2=[ASC], fetch=[100]) HiveProject((tok_table_or_col i_manager_id)=[$0], (tok_function sum (tok_table_or_col ss_sales_price))=[$1], avg_window_0=[$2]) - HiveFilter(condition=[CASE(>($2, 0), >(/(ABS(-($1, $2)), $2), 0.1), null)]) + HiveFilter(condition=[CASE(>($2, 0), >(/(ABS(-($1, $2)), $2), 0.1), false)]) HiveProject((tok_table_or_col i_manager_id)=[$0], (tok_function sum (tok_table_or_col ss_sales_price))=[$2], avg_window_0=[avg($2) OVER (PARTITION BY $0 ORDER BY $0 NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)]) HiveProject(i_manager_id=[$0], d_moy=[$1], $f2=[$2]) HiveAggregate(group=[{6, 8}], agg#0=[sum($4)]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query64.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query64.q.out index 5a5bb797a1..9b43bc6a20 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query64.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query64.q.out @@ -335,13 +335,13 @@ HiveProject(product_name=[$0], store_name=[$1], store_zip=[$2], b_street_number= HiveFilter(condition=[AND(IS NOT NULL($2), IS NOT NULL($9), IS NOT NULL($0), IS NOT NULL($7), IS NOT NULL($3), IS NOT NULL($4), IS NOT NULL($8), IS NOT NULL($5), IS NOT NULL($6))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(i_item_sk=[$0], i_product_name=[$21]) - HiveFilter(condition=[AND(IN($17, _UTF-16LE'maroon', _UTF-16LE'burnished', _UTF-16LE'dim', _UTF-16LE'steel', _UTF-16LE'navajo', _UTF-16LE'chocolate'), BETWEEN(false, $5, 35, 45), BETWEEN(false, $5, 36, 50), IS NOT NULL($0))]) + HiveFilter(condition=[AND(IN($17, _UTF-16LE'maroon', _UTF-16LE'burnished', _UTF-16LE'dim', _UTF-16LE'steel', _UTF-16LE'navajo', _UTF-16LE'chocolate'), BETWEEN(false, $5, CAST(35):DECIMAL(12, 2), 45), BETWEEN(false, $5, 36, 50), IS NOT NULL($0))]) HiveTableScan(table=[[default, item]], table:alias=[item]) HiveProject(d_date_sk=[$0]) HiveFilter(condition=[AND(=($6, 2000), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[d1]) HiveProject($f0=[$0]) - HiveFilter(condition=[>($1, *(2, $2))]) + HiveFilter(condition=[>($1, *(CAST(2):DECIMAL(10, 0), $2))]) HiveAggregate(group=[{0}], agg#0=[sum($2)], agg#1=[sum($5)]) HiveJoin(condition=[AND(=($0, $3), =($1, $4))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(cs_item_sk=[$15], cs_order_number=[$17], cs_ext_list_price=[$25]) @@ -418,13 +418,13 @@ HiveProject(product_name=[$0], store_name=[$1], store_zip=[$2], b_street_number= HiveFilter(condition=[AND(IS NOT NULL($2), IS NOT NULL($9), IS NOT NULL($0), IS NOT NULL($7), IS NOT NULL($3), IS NOT NULL($4), IS NOT NULL($8), IS NOT NULL($5), IS NOT NULL($6))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(i_item_sk=[$0], i_product_name=[$21]) - HiveFilter(condition=[AND(IN($17, _UTF-16LE'maroon', _UTF-16LE'burnished', _UTF-16LE'dim', _UTF-16LE'steel', _UTF-16LE'navajo', _UTF-16LE'chocolate'), BETWEEN(false, $5, 35, 45), BETWEEN(false, $5, 36, 50), IS NOT NULL($0))]) + HiveFilter(condition=[AND(IN($17, _UTF-16LE'maroon', _UTF-16LE'burnished', _UTF-16LE'dim', _UTF-16LE'steel', _UTF-16LE'navajo', _UTF-16LE'chocolate'), BETWEEN(false, $5, CAST(35):DECIMAL(12, 2), 45), BETWEEN(false, $5, 36, 50), IS NOT NULL($0))]) HiveTableScan(table=[[default, item]], table:alias=[item]) HiveProject(d_date_sk=[$0]) HiveFilter(condition=[AND(=($6, 2001), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[d1]) HiveProject($f0=[$0]) - HiveFilter(condition=[>($1, *(2, $2))]) + HiveFilter(condition=[>($1, *(CAST(2):DECIMAL(10, 0), $2))]) HiveAggregate(group=[{0}], agg#0=[sum($2)], agg#1=[sum($5)]) HiveJoin(condition=[AND(=($0, $3), =($1, $4))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(cs_item_sk=[$15], cs_order_number=[$17], cs_ext_list_price=[$25]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query7.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query7.q.out index d4c3ac61c1..1cd2ee7b6a 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query7.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query7.q.out @@ -52,7 +52,7 @@ POSTHOOK: Input: default@store_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) - HiveProject($f0=[$0], $f1=[/(CAST($1):DOUBLE, $2)], $f2=[/($3, $4)], $f3=[/($5, $6)], $f4=[/($7, $8)]) + HiveProject(i_item_id=[$0], agg1=[/(CAST($1):DOUBLE, $2)], agg2=[/($3, $4)], agg3=[/($5, $6)], agg4=[/($7, $8)]) HiveAggregate(group=[{1}], agg#0=[sum($6)], agg#1=[count($6)], agg#2=[sum($7)], agg#3=[count($7)], agg#4=[sum($9)], agg#5=[count($9)], agg#6=[sum($8)], agg#7=[count($8)]) HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(i_item_sk=[$0], i_item_id=[$1]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query72.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query72.q.out index e49b44bf32..f7a718e84c 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query72.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query72.q.out @@ -110,7 +110,7 @@ HiveSortLimit(sort0=[$5], sort1=[$0], sort2=[$1], sort3=[$2], dir0=[DESC-nulls-l HiveProject(cs_sold_date_sk=[$0], cs_ship_date_sk=[$2], cs_bill_cdemo_sk=[$4], cs_bill_hdemo_sk=[$5], cs_item_sk=[$15], cs_promo_sk=[$16], cs_order_number=[$17], cs_quantity=[$18]) HiveFilter(condition=[AND(IS NOT NULL($15), IS NOT NULL($4), IS NOT NULL($5), IS NOT NULL($0), IS NOT NULL($2))]) HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales]) - HiveProject(d_date_sk=[$0], d_week_seq=[$4], +=[+(CAST($2):DOUBLE, 5)]) + HiveProject(d_date_sk=[$0], d_week_seq=[$4], +=[+(CAST($2):DOUBLE, CAST(5):DOUBLE)]) HiveFilter(condition=[AND(=($6, 2001), IS NOT NULL($0), IS NOT NULL($4))]) HiveTableScan(table=[[default, date_dim]], table:alias=[d1]) HiveProject(cd_demo_sk=[$0]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query73.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query73.q.out index 2639cf22b4..16b353808c 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query73.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query73.q.out @@ -72,7 +72,7 @@ HiveSortLimit(sort0=[$5], dir0=[DESC-nulls-last]) HiveFilter(condition=[IS NOT NULL($0)]) HiveTableScan(table=[[default, customer]], table:alias=[customer]) HiveProject(ss_ticket_number=[$0], ss_customer_sk=[$1], $f2=[$2]) - HiveFilter(condition=[BETWEEN(false, $2, 1, 5)]) + HiveFilter(condition=[BETWEEN(false, $2, CAST(1):BIGINT, CAST(5):BIGINT)]) HiveProject(ss_ticket_number=[$1], ss_customer_sk=[$0], $f2=[$2]) HiveAggregate(group=[{1, 4}], agg#0=[count()]) HiveJoin(condition=[=($3, $7)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query74.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query74.q.out index 4a9a1127b3..9317182c93 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query74.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query74.q.out @@ -131,7 +131,7 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$1], sort1=[$0], sort2=[$2], dir0=[ASC], dir1=[ASC], dir2=[ASC], fetch=[100]) HiveProject(customer_id=[$0], customer_first_name=[$1], customer_last_name=[$2]) - HiveJoin(condition=[AND(=($0, $6), CASE(CAST(IS NOT NULL($7)):BOOLEAN, CASE($10, >(/($5, $9), /($3, $7)), >(null, /($3, $7))), CASE($10, >(/($5, $9), null), null)))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[AND(=($0, $6), CASE(CAST(IS NOT NULL($7)):BOOLEAN, CASE($10, >(/($5, $9), /($3, $7)), null), null))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_id=[$0], c_first_name=[$1], c_last_name=[$2], $f3=[$3]) HiveAggregate(group=[{1, 2, 3}], agg#0=[max($6)]) HiveJoin(condition=[=($0, $5)], joinType=[inner], algorithm=[none], cost=[not available]) @@ -147,7 +147,7 @@ HiveSortLimit(sort0=[$1], sort1=[$0], sort2=[$2], dir0=[ASC], dir1=[ASC], dir2=[ HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveJoin(condition=[=($2, $4)], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[=($2, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0], $f4=[$3]) + HiveProject(customer_id=[$0], year_total=[$3]) HiveAggregate(group=[{1, 2, 3}], agg#0=[max($6)]) HiveJoin(condition=[=($0, $5)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], c_customer_id=[$1], c_first_name=[$8], c_last_name=[$9]) @@ -160,7 +160,7 @@ HiveSortLimit(sort0=[$1], sort1=[$0], sort2=[$2], dir0=[ASC], dir1=[ASC], dir2=[ HiveProject(d_date_sk=[$0]) HiveFilter(condition=[AND(IN($6, 2001, 2002), =($6, 2002), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject($f0=[$0], $f4=[$3]) + HiveProject(customer_id=[$0], year_total=[$3]) HiveFilter(condition=[>($3, 0)]) HiveAggregate(group=[{1, 2, 3}], agg#0=[max($6)]) HiveJoin(condition=[=($0, $5)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query78.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query78.q.out index 02635826f0..882dc102d8 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query78.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query78.q.out @@ -129,44 +129,45 @@ POSTHOOK: Input: default@web_returns POSTHOOK: Input: default@web_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: -HiveSortLimit(fetch=[100]) - HiveProject(ss_sold_year=[CAST(2000):INTEGER], ss_item_sk=[$0], ss_customer_sk=[$1], ratio=[$2], store_qty=[$3], store_wholesale_cost=[$4], store_sales_price=[$5], other_chan_qty=[$6], other_chan_wholesale_cost=[$7], other_chan_sales_price=[$8]) - HiveSortLimit(sort0=[$0], sort1=[$1], sort2=[$9], sort3=[$10], sort4=[$11], sort5=[$6], sort6=[$7], sort7=[$8], sort8=[$12], dir0=[ASC], dir1=[ASC], dir2=[DESC-nulls-last], dir3=[DESC-nulls-last], dir4=[DESC-nulls-last], dir5=[ASC], dir6=[ASC], dir7=[ASC], dir8=[ASC]) - HiveProject(ss_item_sk=[$0], ss_customer_sk=[$1], ratio=[round(/(CAST($2):DOUBLE, CAST(CASE(AND(IS NOT NULL($7), IS NOT NULL($11)), +($7, $11), 1)):DOUBLE), 2)], store_qty=[$2], store_wholesale_cost=[$3], store_sales_price=[$4], other_chan_qty=[+(CASE(IS NOT NULL($7), $7, 0), CASE(IS NOT NULL($11), $11, 0))], other_chan_wholesale_cost=[+(CASE(IS NOT NULL($8), $8, 0), CASE(IS NOT NULL($12), $12, 0))], other_chan_sales_price=[+(CASE(IS NOT NULL($9), $9, 0), CASE(IS NOT NULL($13), $13, 0))], ss_qty=[$2], ss_wc=[$3], ss_sp=[$4], (tok_function round (/ (tok_table_or_col ss_qty) (tok_function coalesce (+ (tok_table_or_col ws_qty) (tok_table_or_col cs_qty)) 1)) 2)=[round(/(CAST($2):DOUBLE, CAST(CASE(AND(IS NOT NULL($7), IS NOT NULL($11)), +($7, $11), 1)):DOUBLE), 2)]) - HiveFilter(condition=[CASE(IS NOT NULL($11), >($11, 0), false)]) - HiveJoin(condition=[=($10, $1)], joinType=[left], algorithm=[none], cost=[not available]) - HiveProject(ss_item_sk=[$0], ss_customer_sk=[$1], $f2=[$2], $f3=[$3], $f4=[$4], ws_item_sk=[$5], ws_bill_customer_sk=[$6], $f20=[$7], $f30=[$8], $f40=[$9]) - HiveFilter(condition=[CASE(IS NOT NULL($7), >($7, 0), false)]) - HiveJoin(condition=[AND(=($5, $0), =($6, $1))], joinType=[left], algorithm=[none], cost=[not available]) - HiveProject(ss_item_sk=[$0], ss_customer_sk=[$1], $f2=[$2], $f3=[$3], $f4=[$4]) - HiveAggregate(group=[{2, 3}], agg#0=[sum($4)], agg#1=[sum($5)], agg#2=[sum($6)]) - HiveJoin(condition=[=($1, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[AND(=($6, 2000), IS NOT NULL($0))]) - HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$1], ss_customer_sk=[$2], ss_quantity=[$4], ss_wholesale_cost=[$5], ss_sales_price=[$6]) - HiveFilter(condition=[IS NULL($8)]) - HiveJoin(condition=[AND(=($8, $3), =($1, $7))], joinType=[left], algorithm=[none], cost=[not available]) - HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_customer_sk=[$3], ss_ticket_number=[$9], ss_quantity=[$10], ss_wholesale_cost=[$11], ss_sales_price=[$13]) - HiveFilter(condition=[IS NOT NULL($0)]) - HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject(sr_item_sk=[$2], sr_ticket_number=[$9]) - HiveTableScan(table=[[default, store_returns]], table:alias=[store_returns]) - HiveProject(ws_item_sk=[$0], ws_bill_customer_sk=[$1], $f2=[$2], $f3=[$3], $f4=[$4]) - HiveAggregate(group=[{2, 3}], agg#0=[sum($4)], agg#1=[sum($5)], agg#2=[sum($6)]) - HiveJoin(condition=[=($1, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[AND(=($6, 2000), IS NOT NULL($0))]) - HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$1], ws_bill_customer_sk=[$2], ws_quantity=[$4], ws_wholesale_cost=[$5], ws_sales_price=[$6]) - HiveFilter(condition=[IS NULL($8)]) - HiveJoin(condition=[AND(=($8, $3), =($1, $7))], joinType=[left], algorithm=[none], cost=[not available]) - HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$3], ws_bill_customer_sk=[$4], ws_order_number=[$17], ws_quantity=[$18], ws_wholesale_cost=[$19], ws_sales_price=[$21]) - HiveFilter(condition=[IS NOT NULL($0)]) - HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales]) - HiveProject(wr_item_sk=[$2], wr_order_number=[$13]) - HiveTableScan(table=[[default, web_returns]], table:alias=[web_returns]) - HiveProject($f2=[$0], $f3=[$2], $f4=[$3], $f5=[$4]) +HiveProject(ss_sold_year=[CAST(2000):INTEGER], ss_item_sk=[$0], ss_customer_sk=[$1], ratio=[$2], store_qty=[$3], store_wholesale_cost=[$4], store_sales_price=[$5], other_chan_qty=[$6], other_chan_wholesale_cost=[$7], other_chan_sales_price=[$8]) + HiveSortLimit(sort0=[$0], sort1=[$1], sort2=[$9], sort3=[$10], sort4=[$11], sort5=[$6], sort6=[$7], sort7=[$8], sort8=[$12], dir0=[ASC], dir1=[ASC], dir2=[DESC-nulls-last], dir3=[DESC-nulls-last], dir4=[DESC-nulls-last], dir5=[ASC], dir6=[ASC], dir7=[ASC], dir8=[ASC], fetch=[100]) + HiveProject(ss_item_sk=[$0], ss_customer_sk=[$1], ratio=[round(/(CAST($2):DOUBLE, CAST(CASE(IS NOT NULL(+($7, $11)), +($7, $11), 1)):DOUBLE), 2)], store_qty=[$2], store_wholesale_cost=[$3], store_sales_price=[$4], other_chan_qty=[+(CASE(IS NOT NULL($7), $7, 0), $12)], other_chan_wholesale_cost=[+(CASE(IS NOT NULL($8), $8, 0), $13)], other_chan_sales_price=[+(CASE(IS NOT NULL($9), $9, 0), $14)], ss_qty=[$2], ss_wc=[$3], ss_sp=[$4], (tok_function round (/ (tok_table_or_col ss_qty) (tok_function coalesce (+ (tok_table_or_col ws_qty) (tok_table_or_col cs_qty)) 1)) 2)=[round(/(CAST($2):DOUBLE, CAST(CASE(IS NOT NULL(+($7, $11)), +($7, $11), 1)):DOUBLE), 2)]) + HiveJoin(condition=[=($10, $1)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[AND(=($5, $0), =($6, $1))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(ss_item_sk=[$0], ss_customer_sk=[$1], $f2=[$2], $f3=[$3], $f4=[$4]) + HiveAggregate(group=[{2, 3}], agg#0=[sum($4)], agg#1=[sum($5)], agg#2=[sum($6)]) + HiveJoin(condition=[=($1, $0)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(d_date_sk=[$0]) + HiveFilter(condition=[AND(=($6, 2000), IS NOT NULL($0))]) + HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) + HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$1], ss_customer_sk=[$2], ss_quantity=[$4], ss_wholesale_cost=[$5], ss_sales_price=[$6]) + HiveFilter(condition=[IS NULL($8)]) + HiveJoin(condition=[AND(=($8, $3), =($1, $7))], joinType=[left], algorithm=[none], cost=[not available]) + HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_customer_sk=[$3], ss_ticket_number=[$9], ss_quantity=[$10], ss_wholesale_cost=[$11], ss_sales_price=[$13]) + HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($2), IS NOT NULL($3))]) + HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) + HiveProject(sr_item_sk=[$2], sr_ticket_number=[$9]) + HiveFilter(condition=[IS NOT NULL($2)]) + HiveTableScan(table=[[default, store_returns]], table:alias=[store_returns]) + HiveProject(ws_item_sk=[$0], ws_bill_customer_sk=[$1], $f2=[$2], $f3=[$3], $f4=[$4]) + HiveFilter(condition=[>($2, 0)]) + HiveAggregate(group=[{2, 3}], agg#0=[sum($4)], agg#1=[sum($5)], agg#2=[sum($6)]) + HiveJoin(condition=[=($1, $0)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(d_date_sk=[$0]) + HiveFilter(condition=[AND(=($6, 2000), IS NOT NULL($0))]) + HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) + HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$1], ws_bill_customer_sk=[$2], ws_quantity=[$4], ws_wholesale_cost=[$5], ws_sales_price=[$6]) + HiveFilter(condition=[IS NULL($8)]) + HiveJoin(condition=[AND(=($8, $3), =($1, $7))], joinType=[left], algorithm=[none], cost=[not available]) + HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$3], ws_bill_customer_sk=[$4], ws_order_number=[$17], ws_quantity=[$18], ws_wholesale_cost=[$19], ws_sales_price=[$21]) + HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($3), IS NOT NULL($4))]) + HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales]) + HiveProject(wr_item_sk=[$2], wr_order_number=[$13]) + HiveFilter(condition=[IS NOT NULL($2)]) + HiveTableScan(table=[[default, web_returns]], table:alias=[web_returns]) + HiveProject($f2=[$1], $f3=[$2], CASE=[CASE(IS NOT NULL($2), $2, 0)], CASE6=[CASE(IS NOT NULL($3), $3, 0)], CASE7=[CASE(IS NOT NULL($4), $4, 0)]) + HiveFilter(condition=[>($2, 0)]) + HiveProject(cs_item_sk=[$1], cs_bill_customer_sk=[$0], $f2=[$2], $f3=[$3], $f4=[$4]) HiveAggregate(group=[{2, 3}], agg#0=[sum($4)], agg#1=[sum($5)], agg#2=[sum($6)]) HiveJoin(condition=[=($1, $0)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(d_date_sk=[$0]) @@ -176,7 +177,7 @@ HiveSortLimit(fetch=[100]) HiveFilter(condition=[IS NULL($8)]) HiveJoin(condition=[AND(=($8, $3), =($2, $7))], joinType=[left], algorithm=[none], cost=[not available]) HiveProject(cs_sold_date_sk=[$0], cs_bill_customer_sk=[$3], cs_item_sk=[$15], cs_order_number=[$17], cs_quantity=[$18], cs_wholesale_cost=[$19], cs_sales_price=[$21]) - HiveFilter(condition=[AND(=($15, $15), IS NOT NULL($0))]) + HiveFilter(condition=[AND(=($15, $15), IS NOT NULL($0), IS NOT NULL($3))]) HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales]) HiveProject(cr_item_sk=[$2], cr_order_number=[$16]) HiveTableScan(table=[[default, catalog_returns]], table:alias=[catalog_returns]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query8.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query8.q.out index d80d3365d9..2170bbb9f5 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query8.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query8.q.out @@ -241,16 +241,16 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(substr=[substr($0, 1, 2)]) HiveFilter(condition=[=($1, 2)]) HiveAggregate(group=[{0}], agg#0=[count($1)]) - HiveProject(ca_zip=[$0], $f1=[$1]) + HiveProject($f0=[$0], $f1=[$1]) HiveUnion(all=[true]) - HiveProject(ca_zip=[$0], $f1=[$1]) + HiveProject($f0=[$0], $f1=[$1]) HiveAggregate(group=[{0}], agg#0=[count()]) - HiveProject(ca_zip=[substr($9, 1, 5)]) + HiveProject($f0=[substr($9, 1, 5)]) HiveFilter(condition=[AND(IN(substr($9, 1, 5), _UTF-16LE'89436', _UTF-16LE'30868', _UTF-16LE'65085', _UTF-16LE'22977', _UTF-16LE'83927', _UTF-16LE'77557', _UTF-16LE'58429', _UTF-16LE'40697', _UTF-16LE'80614', _UTF-16LE'10502', _UTF-16LE'32779', _UTF-16LE'91137', _UTF-16LE'61265', _UTF-16LE'98294', _UTF-16LE'17921', _UTF-16LE'18427', _UTF-16LE'21203', _UTF-16LE'59362', _UTF-16LE'87291', _UTF-16LE'84093', _UTF-16LE'21505', _UTF-16LE'17184', _UTF-16LE'10866', _UTF-16LE'67898', _UTF-16LE'25797', _UTF-16LE'28055', _UTF-16LE'18377', _UTF-16LE'80332', _UTF-16LE'74535', _UTF-16LE'21757', _UTF-16LE'29742', _UTF-16LE'90885', _UTF-16LE'29898', _UTF-16LE'17819', _UTF-16LE'40811', _UTF-16LE'25990', _UTF-16LE'47513', _UTF-16LE'89531', _UTF-16LE'91068', _UTF-16LE'10391', _UTF-16LE'18846', _UTF-16LE'99223', _UTF-16LE'82637', _UTF-16LE'41368', _UTF-16LE'83658', _UTF-16LE'86199', _UTF-16LE'81625', _UTF-16LE'26696', _UTF-16LE'89338', _UTF-16LE'88425', _UTF-16LE'32200', _UTF-16LE'81427', _UTF-16LE'19053', _UTF-16LE'77471', _UTF-16LE'36610', _UTF-16LE'99823', _UTF-16LE'43276', _UTF-16LE'41249', _UTF-16LE'48584', _UTF-16LE'83550', _UTF-16LE'82276', _UTF-16LE'18842', _UTF-16LE'78890', _UTF-16LE'14090', _UTF-16LE'38123', _UTF-16LE'40936', _UTF-16LE'34425', _UTF-16LE'19850', _UTF-16LE'43286', _UTF-16LE'80072', _UTF-16LE'79188', _UTF-16LE'54191', _UTF-16LE'11395', _UTF-16LE'50497', _UTF-16LE'84861', _UTF-16LE'90733', _UTF-16LE'21068', _UTF-16LE'57666', _UTF-16LE'37119', _UTF-16LE'25004', _UTF-16LE'57835', _UTF-16LE'70067', _UTF-16LE'62878', _UTF-16LE'95806', _UTF-16LE'19303', _UTF-16LE'18840', _UTF-16LE'19124', _UTF-16LE'29785', _UTF-16LE'16737', _UTF-16LE'16022', _UTF-16LE'49613', _UTF-16LE'89977', _UTF-16LE'68310', _UTF-16LE'60069', _UTF-16LE'98360', _UTF-16LE'48649', _UTF-16LE'39050', _UTF-16LE'41793', _UTF-16LE'25002', _UTF-16LE'27413', _UTF-16LE'39736', _UTF-16LE'47208', _UTF-16LE'16515', _UTF-16LE'94808', _UTF-16LE'57648', _UTF-16LE'15009', _UTF-16LE'80015', _UTF-16LE'42961', _UTF-16LE'63982', _UTF-16LE'21744', _UTF-16LE'71853', _UTF-16LE'81087', _UTF-16LE'67468', _UTF-16LE'34175', _UTF-16LE'64008', _UTF-16LE'20261', _UTF-16LE'11201', _UTF-16LE'51799', _UTF-16LE'48043', _UTF-16LE'45645', _UTF-16LE'61163', _UTF-16LE'48375', _UTF-16LE'36447', _UTF-16LE'57042', _UTF-16LE'21218', _UTF-16LE'41100', _UTF-16LE'89951', _UTF-16LE'22745', _UTF-16LE'35851', _UTF-16LE'83326', _UTF-16LE'61125', _UTF-16LE'78298', _UTF-16LE'80752', _UTF-16LE'49858', _UTF-16LE'52940', _UTF-16LE'96976', _UTF-16LE'63792', _UTF-16LE'11376', _UTF-16LE'53582', _UTF-16LE'18717', _UTF-16LE'90226', _UTF-16LE'50530', _UTF-16LE'94203', _UTF-16LE'99447', _UTF-16LE'27670', _UTF-16LE'96577', _UTF-16LE'57856', _UTF-16LE'56372', _UTF-16LE'16165', _UTF-16LE'23427', _UTF-16LE'54561', _UTF-16LE'28806', _UTF-16LE'44439', _UTF-16LE'22926', _UTF-16LE'30123', _UTF-16LE'61451', _UTF-16LE'92397', _UTF-16LE'56979', _UTF-16LE'92309', _UTF-16LE'70873', _UTF-16LE'13355', _UTF-16LE'21801', _UTF-16LE'46346', _UTF-16LE'37562', _UTF-16LE'56458', _UTF-16LE'28286', _UTF-16LE'47306', _UTF-16LE'99555', _UTF-16LE'69399', _UTF-16LE'26234', _UTF-16LE'47546', _UTF-16LE'49661', _UTF-16LE'88601', _UTF-16LE'35943', _UTF-16LE'39936', _UTF-16LE'25632', _UTF-16LE'24611', _UTF-16LE'44166', _UTF-16LE'56648', _UTF-16LE'30379', _UTF-16LE'59785', _UTF-16LE'11110', _UTF-16LE'14329', _UTF-16LE'93815', _UTF-16LE'52226', _UTF-16LE'71381', _UTF-16LE'13842', _UTF-16LE'25612', _UTF-16LE'63294', _UTF-16LE'14664', _UTF-16LE'21077', _UTF-16LE'82626', _UTF-16LE'18799', _UTF-16LE'60915', _UTF-16LE'81020', _UTF-16LE'56447', _UTF-16LE'76619', _UTF-16LE'11433', _UTF-16LE'13414', _UTF-16LE'42548', _UTF-16LE'92713', _UTF-16LE'70467', _UTF-16LE'30884', _UTF-16LE'47484', _UTF-16LE'16072', _UTF-16LE'38936', _UTF-16LE'13036', _UTF-16LE'88376', _UTF-16LE'45539', _UTF-16LE'35901', _UTF-16LE'19506', _UTF-16LE'65690', _UTF-16LE'73957', _UTF-16LE'71850', _UTF-16LE'49231', _UTF-16LE'14276', _UTF-16LE'20005', _UTF-16LE'18384', _UTF-16LE'76615', _UTF-16LE'11635', _UTF-16LE'38177', _UTF-16LE'55607', _UTF-16LE'41369', _UTF-16LE'95447', _UTF-16LE'58581', _UTF-16LE'58149', _UTF-16LE'91946', _UTF-16LE'33790', _UTF-16LE'76232', _UTF-16LE'75692', _UTF-16LE'95464', _UTF-16LE'22246', _UTF-16LE'51061', _UTF-16LE'56692', _UTF-16LE'53121', _UTF-16LE'77209', _UTF-16LE'15482', _UTF-16LE'10688', _UTF-16LE'14868', _UTF-16LE'45907', _UTF-16LE'73520', _UTF-16LE'72666', _UTF-16LE'25734', _UTF-16LE'17959', _UTF-16LE'24677', _UTF-16LE'66446', _UTF-16LE'94627', _UTF-16LE'53535', _UTF-16LE'15560', _UTF-16LE'41967', _UTF-16LE'69297', _UTF-16LE'11929', _UTF-16LE'59403', _UTF-16LE'33283', _UTF-16LE'52232', _UTF-16LE'57350', _UTF-16LE'43933', _UTF-16LE'40921', _UTF-16LE'36635', _UTF-16LE'10827', _UTF-16LE'71286', _UTF-16LE'19736', _UTF-16LE'80619', _UTF-16LE'25251', _UTF-16LE'95042', _UTF-16LE'15526', _UTF-16LE'36496', _UTF-16LE'55854', _UTF-16LE'49124', _UTF-16LE'81980', _UTF-16LE'35375', _UTF-16LE'49157', _UTF-16LE'63512', _UTF-16LE'28944', _UTF-16LE'14946', _UTF-16LE'36503', _UTF-16LE'54010', _UTF-16LE'18767', _UTF-16LE'23969', _UTF-16LE'43905', _UTF-16LE'66979', _UTF-16LE'33113', _UTF-16LE'21286', _UTF-16LE'58471', _UTF-16LE'59080', _UTF-16LE'13395', _UTF-16LE'79144', _UTF-16LE'70373', _UTF-16LE'67031', _UTF-16LE'38360', _UTF-16LE'26705', _UTF-16LE'50906', _UTF-16LE'52406', _UTF-16LE'26066', _UTF-16LE'73146', _UTF-16LE'15884', _UTF-16LE'31897', _UTF-16LE'30045', _UTF-16LE'61068', _UTF-16LE'45550', _UTF-16LE'92454', _UTF-16LE'13376', _UTF-16LE'14354', _UTF-16LE'19770', _UTF-16LE'22928', _UTF-16LE'97790', _UTF-16LE'50723', _UTF-16LE'46081', _UTF-16LE'30202', _UTF-16LE'14410', _UTF-16LE'20223', _UTF-16LE'88500', _UTF-16LE'67298', _UTF-16LE'13261', _UTF-16LE'14172', _UTF-16LE'81410', _UTF-16LE'93578', _UTF-16LE'83583', _UTF-16LE'46047', _UTF-16LE'94167', _UTF-16LE'82564', _UTF-16LE'21156', _UTF-16LE'15799', _UTF-16LE'86709', _UTF-16LE'37931', _UTF-16LE'74703', _UTF-16LE'83103', _UTF-16LE'23054', _UTF-16LE'70470', _UTF-16LE'72008', _UTF-16LE'49247', _UTF-16LE'91911', _UTF-16LE'69998', _UTF-16LE'20961', _UTF-16LE'70070', _UTF-16LE'63197', _UTF-16LE'54853', _UTF-16LE'88191', _UTF-16LE'91830', _UTF-16LE'49521', _UTF-16LE'19454', _UTF-16LE'81450', _UTF-16LE'89091', _UTF-16LE'62378', _UTF-16LE'25683', _UTF-16LE'61869', _UTF-16LE'51744', _UTF-16LE'36580', _UTF-16LE'85778', _UTF-16LE'36871', _UTF-16LE'48121', _UTF-16LE'28810', _UTF-16LE'83712', _UTF-16LE'45486', _UTF-16LE'67393', _UTF-16LE'26935', _UTF-16LE'42393', _UTF-16LE'20132', _UTF-16LE'55349', _UTF-16LE'86057', _UTF-16LE'21309', _UTF-16LE'80218', _UTF-16LE'10094', _UTF-16LE'11357', _UTF-16LE'48819', _UTF-16LE'39734', _UTF-16LE'40758', _UTF-16LE'30432', _UTF-16LE'21204', _UTF-16LE'29467', _UTF-16LE'30214', _UTF-16LE'61024', _UTF-16LE'55307', _UTF-16LE'74621', _UTF-16LE'11622', _UTF-16LE'68908', _UTF-16LE'33032', _UTF-16LE'52868', _UTF-16LE'99194', _UTF-16LE'99900', _UTF-16LE'84936', _UTF-16LE'69036', _UTF-16LE'99149', _UTF-16LE'45013', _UTF-16LE'32895', _UTF-16LE'59004', _UTF-16LE'32322', _UTF-16LE'14933', _UTF-16LE'32936', _UTF-16LE'33562', _UTF-16LE'72550', _UTF-16LE'27385', _UTF-16LE'58049', _UTF-16LE'58200', _UTF-16LE'16808', _UTF-16LE'21360', _UTF-16LE'32961', _UTF-16LE'18586', _UTF-16LE'79307', _UTF-16LE'15492'), IS NOT NULL(substr(substr($9, 1, 5), 1, 2)))]) HiveTableScan(table=[[default, customer_address]], table:alias=[customer_address]) - HiveProject(ca_zip=[$0], $f1=[$1]) + HiveProject($f0=[$0], $f1=[$1]) HiveAggregate(group=[{0}], agg#0=[count()]) - HiveProject(ca_zip=[substr($0, 1, 5)]) + HiveProject($f0=[substr($0, 1, 5)]) HiveFilter(condition=[>($1, 10)]) HiveAggregate(group=[{1}], agg#0=[count()]) HiveJoin(condition=[=($0, $2)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query82.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query82.q.out index a60312f11b..7a3083d2a3 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query82.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query82.q.out @@ -50,7 +50,7 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveFilter(condition=[IS NOT NULL($2)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(i_item_sk=[$0], i_item_id=[$1], i_item_desc=[$4], i_current_price=[$5]) - HiveFilter(condition=[AND(IN($13, 437, 129, 727, 663), BETWEEN(false, $5, 30, 60), IS NOT NULL($0))]) + HiveFilter(condition=[AND(IN($13, 437, 129, 727, 663), BETWEEN(false, $5, CAST(30):DECIMAL(12, 2), 60), IS NOT NULL($0))]) HiveTableScan(table=[[default, item]], table:alias=[item]) HiveProject(inv_date_sk=[$0], inv_item_sk=[$1], d_date_sk=[$2]) HiveJoin(condition=[=($2, $0)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query85.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query85.q.out index f5a71b422b..d8275d21f6 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query85.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query85.q.out @@ -213,7 +213,7 @@ HiveProject(_o__c0=[$0], _o__c1=[$1], _o__c2=[$2], _o__c3=[$3]) HiveProject(wr_item_sk=[$2], wr_refunded_cdemo_sk=[$4], wr_refunded_addr_sk=[$6], wr_returning_cdemo_sk=[$8], wr_reason_sk=[$12], wr_order_number=[$13], wr_fee=[$18], wr_refunded_cash=[$20]) HiveFilter(condition=[AND(IS NOT NULL($2), IS NOT NULL($13), IS NOT NULL($4), IS NOT NULL($8), IS NOT NULL($6), IS NOT NULL($12))]) HiveTableScan(table=[[default, web_returns]], table:alias=[web_returns]) - HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$3], ws_web_page_sk=[$12], ws_order_number=[$17], ws_quantity=[$18], BETWEEN=[BETWEEN(false, $33, 100, 200)], BETWEEN6=[BETWEEN(false, $33, 150, 300)], BETWEEN7=[BETWEEN(false, $33, 50, 250)], BETWEEN8=[BETWEEN(false, $21, 100, 150)], BETWEEN9=[BETWEEN(false, $21, 50, 100)], BETWEEN10=[BETWEEN(false, $21, 150, 200)]) - HiveFilter(condition=[AND(OR(BETWEEN(false, $21, 100, 150), BETWEEN(false, $21, 50, 100), BETWEEN(false, $21, 150, 200)), OR(BETWEEN(false, $33, 100, 200), BETWEEN(false, $33, 150, 300), BETWEEN(false, $33, 50, 250)), IS NOT NULL($3), IS NOT NULL($17), IS NOT NULL($12), IS NOT NULL($0))]) + HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$3], ws_web_page_sk=[$12], ws_order_number=[$17], ws_quantity=[$18], BETWEEN=[BETWEEN(false, $33, CAST(100):DECIMAL(12, 2), CAST(200):DECIMAL(12, 2))], BETWEEN6=[BETWEEN(false, $33, CAST(150):DECIMAL(12, 2), CAST(300):DECIMAL(12, 2))], BETWEEN7=[BETWEEN(false, $33, CAST(50):DECIMAL(12, 2), CAST(250):DECIMAL(12, 2))], BETWEEN8=[BETWEEN(false, $21, 100, 150)], BETWEEN9=[BETWEEN(false, $21, 50, 100)], BETWEEN10=[BETWEEN(false, $21, 150, 200)]) + HiveFilter(condition=[AND(OR(BETWEEN(false, $21, 100, 150), BETWEEN(false, $21, 50, 100), BETWEEN(false, $21, 150, 200)), OR(BETWEEN(false, $33, CAST(100):DECIMAL(12, 2), CAST(200):DECIMAL(12, 2)), BETWEEN(false, $33, CAST(150):DECIMAL(12, 2), CAST(300):DECIMAL(12, 2)), BETWEEN(false, $33, CAST(50):DECIMAL(12, 2), CAST(250):DECIMAL(12, 2))), IS NOT NULL($3), IS NOT NULL($17), IS NOT NULL($12), IS NOT NULL($0))]) HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query88.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query88.q.out index 1f4471e8ae..5dbc2bcfc6 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query88.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query88.q.out @@ -217,7 +217,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 8), >=($4, 30), IS NOT NULL($0))]) @@ -234,7 +234,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 12), <($4, 30), IS NOT NULL($0))]) @@ -251,7 +251,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 11), >=($4, 30), IS NOT NULL($0))]) @@ -268,7 +268,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 11), <($4, 30), IS NOT NULL($0))]) @@ -285,7 +285,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 10), >=($4, 30), IS NOT NULL($0))]) @@ -302,7 +302,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 10), <($4, 30), IS NOT NULL($0))]) @@ -319,7 +319,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 9), >=($4, 30), IS NOT NULL($0))]) @@ -336,7 +336,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))), IS NOT NULL($0))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 9), <($4, 30), IS NOT NULL($0))]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query89.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query89.q.out index 7cfb3ecdec..5b77d1db9b 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query89.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query89.q.out @@ -66,7 +66,7 @@ CBO PLAN: HiveProject(i_category=[$0], i_class=[$1], i_brand=[$2], s_store_name=[$3], s_company_name=[$4], d_moy=[$5], sum_sales=[$6], avg_monthly_sales=[$7]) HiveSortLimit(sort0=[$8], sort1=[$3], dir0=[ASC], dir1=[ASC], fetch=[100]) HiveProject(i_category=[$0], i_class=[$1], i_brand=[$2], s_store_name=[$3], s_company_name=[$4], d_moy=[$5], sum_sales=[$6], avg_monthly_sales=[$7], (- (tok_table_or_col sum_sales) (tok_table_or_col avg_monthly_sales))=[-($6, $7)]) - HiveFilter(condition=[CASE(<>($7, 0), >(/(ABS(-($6, $7)), $7), 0.1), null)]) + HiveFilter(condition=[CASE(<>($7, 0), >(/(ABS(-($6, $7)), $7), 0.1), false)]) HiveProject((tok_table_or_col i_category)=[$2], (tok_table_or_col i_class)=[$1], (tok_table_or_col i_brand)=[$0], (tok_table_or_col s_store_name)=[$4], (tok_table_or_col s_company_name)=[$5], (tok_table_or_col d_moy)=[$3], (tok_function sum (tok_table_or_col ss_sales_price))=[$6], avg_window_0=[avg($6) OVER (PARTITION BY $2, $0, $4, $5 ORDER BY $2 NULLS FIRST, $0 NULLS FIRST, $4 NULLS FIRST, $5 NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)]) HiveProject(i_brand=[$0], i_class=[$1], i_category=[$2], d_moy=[$3], s_store_name=[$4], s_company_name=[$5], $f6=[$6]) HiveAggregate(group=[{5, 6, 7, 9, 11, 12}], agg#0=[sum($3)]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query9.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query9.q.out index 3a1e1990ef..02aaaae4e2 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query9.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query9.q.out @@ -141,11 +141,11 @@ HiveProject(bucket1=[CASE($1, $2, $3)], bucket2=[CASE($4, $5, $6)], bucket3=[CAS HiveAggregate(group=[{}], agg#0=[count()]) HiveFilter(condition=[BETWEEN(false, $10, 1, 20)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($17)], agg#1=[count($17)]) HiveFilter(condition=[BETWEEN(false, $10, 1, 20)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)]) HiveFilter(condition=[BETWEEN(false, $10, 1, 20)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) @@ -153,11 +153,11 @@ HiveProject(bucket1=[CASE($1, $2, $3)], bucket2=[CASE($4, $5, $6)], bucket3=[CAS HiveAggregate(group=[{}], agg#0=[count()]) HiveFilter(condition=[BETWEEN(false, $10, 21, 40)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($17)], agg#1=[count($17)]) HiveFilter(condition=[BETWEEN(false, $10, 21, 40)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)]) HiveFilter(condition=[BETWEEN(false, $10, 21, 40)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) @@ -165,11 +165,11 @@ HiveProject(bucket1=[CASE($1, $2, $3)], bucket2=[CASE($4, $5, $6)], bucket3=[CAS HiveAggregate(group=[{}], agg#0=[count()]) HiveFilter(condition=[BETWEEN(false, $10, 41, 60)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($17)], agg#1=[count($17)]) HiveFilter(condition=[BETWEEN(false, $10, 41, 60)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)]) HiveFilter(condition=[BETWEEN(false, $10, 41, 60)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) @@ -177,11 +177,11 @@ HiveProject(bucket1=[CASE($1, $2, $3)], bucket2=[CASE($4, $5, $6)], bucket3=[CAS HiveAggregate(group=[{}], agg#0=[count()]) HiveFilter(condition=[BETWEEN(false, $10, 61, 80)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($17)], agg#1=[count($17)]) HiveFilter(condition=[BETWEEN(false, $10, 61, 80)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)]) HiveFilter(condition=[BETWEEN(false, $10, 61, 80)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) @@ -189,11 +189,11 @@ HiveProject(bucket1=[CASE($1, $2, $3)], bucket2=[CASE($4, $5, $6)], bucket3=[CAS HiveAggregate(group=[{}], agg#0=[count()]) HiveFilter(condition=[BETWEEN(false, $10, 81, 100)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($17)], agg#1=[count($17)]) HiveFilter(condition=[BETWEEN(false, $10, 81, 100)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)]) HiveFilter(condition=[BETWEEN(false, $10, 81, 100)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query92.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query92.q.out index 2a21fbaf4e..17f198e7d3 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query92.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query92.q.out @@ -75,7 +75,7 @@ HiveProject(excess discount amount=[$0]) HiveFilter(condition=[AND(IS NOT NULL($3), IS NOT NULL($0))]) HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales]) HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[AND(BETWEEN(false, CAST($2):TIMESTAMP(9), 1998-03-18 00:00:00, 1998-06-16 00:00:00), IS NOT NULL($0))]) + HiveFilter(condition=[AND(BETWEEN(false, CAST($2):TIMESTAMP(9), CAST(_UTF-16LE'1998-03-18'):TIMESTAMP(9), 1998-06-16 00:00:00), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(ws_item_sk=[$0], CAST=[$1], i_item_sk=[$2]) HiveJoin(condition=[=($0, $2)], joinType=[inner], algorithm=[none], cost=[not available]) @@ -86,7 +86,7 @@ HiveProject(excess discount amount=[$0]) HiveFilter(condition=[AND(IS NOT NULL($3), IS NOT NULL($0))]) HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales]) HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[AND(BETWEEN(false, CAST($2):TIMESTAMP(9), 1998-03-18 00:00:00, 1998-06-16 00:00:00), IS NOT NULL($0))]) + HiveFilter(condition=[AND(BETWEEN(false, CAST($2):TIMESTAMP(9), CAST(_UTF-16LE'1998-03-18'):TIMESTAMP(9), 1998-06-16 00:00:00), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(i_item_sk=[$0]) HiveFilter(condition=[AND(=($13, 269), IS NOT NULL($0))]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query93.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query93.q.out index 6a8ed39e29..5f5ad86083 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query93.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query93.q.out @@ -42,9 +42,9 @@ POSTHOOK: Input: default@store_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$1], sort1=[$0], dir0=[ASC], dir1=[ASC], fetch=[100]) - HiveProject(ss_customer_sk=[$0], $f1=[$1]) + HiveProject($f0=[$0], $f1=[$1]) HiveAggregate(group=[{0}], agg#0=[sum($1)]) - HiveProject(ss_customer_sk=[$1], act_sales=[CASE($10, *(CAST(-($3, $9)):DECIMAL(10, 0), $4), $5)]) + HiveProject($f0=[$1], $f1=[CASE($10, *(CAST(-($3, $9)):DECIMAL(10, 0), $4), $5)]) HiveJoin(condition=[AND(=($6, $0), =($8, $2))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(ss_item_sk=[$2], ss_customer_sk=[$3], ss_ticket_number=[$9], ss_quantity=[$10], ss_sales_price=[$13], *=[*(CAST($10):DECIMAL(10, 0), $13)]) HiveFilter(condition=[AND(IS NOT NULL($2), IS NOT NULL($9))]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query94.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query94.q.out index 4f97a67466..862b6116c2 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query94.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query94.q.out @@ -85,7 +85,7 @@ HiveProject(order count=[$0], total shipping cost=[$1], total net profit=[$2]) HiveFilter(condition=[AND(IS NOT NULL($2), IS NOT NULL($11), IS NOT NULL($13), IS NOT NULL($17))]) HiveTableScan(table=[[default, web_sales]], table:alias=[ws1]) HiveProject(d_date_sk=[$0], d_date=[$2]) - HiveFilter(condition=[AND(BETWEEN(false, CAST($2):TIMESTAMP(9), 1999-05-01 00:00:00, 1999-06-30 00:00:00), IS NOT NULL($0))]) + HiveFilter(condition=[AND(BETWEEN(false, CAST($2):TIMESTAMP(9), CAST(_UTF-16LE'1999-5-01'):TIMESTAMP(9), 1999-06-30 00:00:00), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(web_site_sk=[$0], web_company_name=[CAST(_UTF-16LE'pri'):VARCHAR(2147483647) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary"]) HiveFilter(condition=[AND(=($14, _UTF-16LE'pri'), IS NOT NULL($0))]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query95.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query95.q.out index 6a201658df..69bf63a15a 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query95.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query95.q.out @@ -112,7 +112,7 @@ HiveProject(order count=[$0], total shipping cost=[$1], total net profit=[$2]) HiveFilter(condition=[AND(IS NOT NULL($17), IS NOT NULL($2), IS NOT NULL($11), IS NOT NULL($13))]) HiveTableScan(table=[[default, web_sales]], table:alias=[ws1]) HiveProject(d_date_sk=[$0], d_date=[$2]) - HiveFilter(condition=[AND(BETWEEN(false, CAST($2):TIMESTAMP(9), 1999-05-01 00:00:00, 1999-06-30 00:00:00), IS NOT NULL($0))]) + HiveFilter(condition=[AND(BETWEEN(false, CAST($2):TIMESTAMP(9), CAST(_UTF-16LE'1999-5-01'):TIMESTAMP(9), 1999-06-30 00:00:00), IS NOT NULL($0))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(web_site_sk=[$0]) HiveFilter(condition=[AND(=($14, _UTF-16LE'pri'), IS NOT NULL($0))]) diff --git ql/src/test/results/clientpositive/perf/tez/cbo_query97.q.out ql/src/test/results/clientpositive/perf/tez/cbo_query97.q.out index f79dffbdc8..b1b88ab47b 100644 --- ql/src/test/results/clientpositive/perf/tez/cbo_query97.q.out +++ ql/src/test/results/clientpositive/perf/tez/cbo_query97.q.out @@ -58,7 +58,7 @@ CBO PLAN: HiveSortLimit(fetch=[100]) HiveProject($f0=[$0], $f1=[$1], $f2=[$2]) HiveAggregate(group=[{}], agg#0=[sum($0)], agg#1=[sum($1)], agg#2=[sum($2)]) - HiveProject($f0=[CASE(AND(IS NOT NULL($0), IS NULL($2)), 1, 0)], $f1=[CASE(AND(IS NULL($0), IS NOT NULL($2)), 1, 0)], $f2=[CASE(AND(IS NOT NULL($0), IS NOT NULL($2)), 1, 0)]) + HiveProject($f0=[CAST(CASE(AND(IS NULL($2), IS NOT NULL($0)), 1, 0)):INTEGER], $f1=[CASE(AND(IS NULL($0), IS NOT NULL($2)), 1, 0)], $f2=[CASE(AND(IS NOT NULL($0), IS NOT NULL($2)), 1, 0)]) HiveJoin(condition=[AND(=($0, $2), =($1, $3))], joinType=[full], algorithm=[none], cost=[not available]) HiveProject(ss_customer_sk=[$1], ss_item_sk=[$0]) HiveAggregate(group=[{1, 2}]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query1.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query1.q.out index 13801ffc6c..92b40c95e0 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query1.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query1.q.out @@ -59,10 +59,10 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(c_customer_id=[$1]) - HiveJoin(condition=[AND(=($3, $7), >($4, $6))], joinType=[inner], algorithm=[none], cost=[not available]) - HiveJoin(condition=[=($2, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(c_customer_sk=[$0], c_customer_id=[$1]) - HiveTableScan(table=[[default, customer]], table:alias=[customer]) + HiveJoin(condition=[=($2, $0)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(c_customer_sk=[$0], c_customer_id=[$1]) + HiveTableScan(table=[[default, customer]], table:alias=[customer]) + HiveJoin(condition=[AND(=($1, $5), >($2, $4))], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[=($3, $1)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(sr_customer_sk=[$0], sr_store_sk=[$1], $f2=[$2]) HiveAggregate(group=[{1, 2}], agg#0=[sum($3)]) @@ -76,15 +76,15 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(s_store_sk=[$0]) HiveFilter(condition=[=($24, _UTF-16LE'NM')]) HiveTableScan(table=[[default, store]], table:alias=[store]) - HiveProject(_o__c0=[*(/($1, $2), 1.2)], ctr_store_sk=[$0]) - HiveAggregate(group=[{1}], agg#0=[sum($2)], agg#1=[count($2)]) - HiveProject(sr_customer_sk=[$0], sr_store_sk=[$1], $f2=[$2]) - HiveAggregate(group=[{1, 2}], agg#0=[sum($3)]) - HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(sr_returned_date_sk=[$0], sr_customer_sk=[$3], sr_store_sk=[$7], sr_fee=[$14]) - HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($7))]) - HiveTableScan(table=[[default, store_returns]], table:alias=[store_returns]) - HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[=($6, 2000)]) - HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) + HiveProject(_o__c0=[*(/($1, $2), 1.2)], ctr_store_sk=[$0]) + HiveAggregate(group=[{1}], agg#0=[sum($2)], agg#1=[count($2)]) + HiveProject(sr_customer_sk=[$0], sr_store_sk=[$1], $f2=[$2]) + HiveAggregate(group=[{1, 2}], agg#0=[sum($3)]) + HiveJoin(condition=[=($0, $4)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(sr_returned_date_sk=[$0], sr_customer_sk=[$3], sr_store_sk=[$7], sr_fee=[$14]) + HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($7))]) + HiveTableScan(table=[[default, store_returns]], table:alias=[store_returns]) + HiveProject(d_date_sk=[$0]) + HiveFilter(condition=[=($6, 2000)]) + HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query11.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query11.q.out index f315e3c455..8c07930b52 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query11.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query11.q.out @@ -159,8 +159,8 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(c_preferred_cust_flag=[$1]) - HiveJoin(condition=[AND(=($0, $8), CASE(CAST(IS NOT NULL($9)):BOOLEAN, CASE($7, >(/($4, $6), /($2, $9)), >(null, /($2, $9))), CASE($7, >(/($4, $6), null), null)))], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0], $f4=[$3], $f9=[$7]) + HiveJoin(condition=[AND(=($0, $8), CASE(CAST(IS NOT NULL($9)):BOOLEAN, CASE($7, >(/($4, $6), /($2, $9)), null), null))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(customer_id=[$0], c_preferred_cust_flag=[$3], year_total=[$7]) HiveAggregate(group=[{1, 2, 3, 4, 5, 6, 7}], agg#0=[sum($10)]) HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], c_customer_id=[$1], c_first_name=[$8], c_last_name=[$9], c_preferred_cust_flag=[$10], c_birth_country=[$14], c_login=[$15], c_email_address=[$16]) @@ -173,7 +173,7 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveFilter(condition=[=($6, 2002)]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveJoin(condition=[=($5, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0], $f8=[$7]) + HiveProject(customer_id=[$0], year_total=[$7]) HiveAggregate(group=[{1, 2, 3, 4, 5, 6, 7}], agg#0=[sum($10)]) HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], c_customer_id=[$1], c_first_name=[$8], c_last_name=[$9], c_preferred_cust_flag=[$10], c_birth_country=[$14], c_login=[$15], c_email_address=[$16]) @@ -199,7 +199,7 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(d_date_sk=[$0]) HiveFilter(condition=[=($6, 2001)]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject($f0=[$0], $f9=[$7]) + HiveProject(customer_id=[$0], year_total=[$7]) HiveFilter(condition=[>($7, 0)]) HiveAggregate(group=[{1, 2, 3, 4, 5, 6, 7}], agg#0=[sum($10)]) HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query13.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query13.q.out index 811a5184aa..4a8e2a1f86 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query13.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query13.q.out @@ -113,7 +113,7 @@ POSTHOOK: Input: default@store POSTHOOK: Input: default@store_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: -HiveProject($f0=[/(CAST($0):DOUBLE, $1)], $f1=[/($2, $3)], $f2=[/($4, $5)], $f3=[CAST($4):DECIMAL(17, 2)]) +HiveProject(_o__c0=[/(CAST($0):DOUBLE, $1)], _o__c1=[/($2, $3)], _o__c2=[/($4, $5)], _o__c3=[CAST($4):DECIMAL(17, 2)]) HiveAggregate(group=[{}], agg#0=[sum($19)], agg#1=[count($19)], agg#2=[sum($20)], agg#3=[count($20)], agg#4=[sum($21)], agg#5=[count($21)]) HiveJoin(condition=[AND(=($0, $16), OR(AND($1, $2, $25, $12), AND($3, $4, $26, $13), AND($5, $6, $27, $13)))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(cd_demo_sk=[$0], ==[=($2, _UTF-16LE'M')], =2=[=($3, _UTF-16LE'4 yr Degree')], =3=[=($2, _UTF-16LE'D')], =4=[=($3, _UTF-16LE'Primary')], =5=[=($2, _UTF-16LE'U')], =6=[=($3, _UTF-16LE'Advanced Degree')]) @@ -131,7 +131,7 @@ HiveProject($f0=[/(CAST($0):DOUBLE, $1)], $f1=[/($2, $3)], $f2=[/($4, $5)], $f3= HiveProject(d_date_sk=[$0]) HiveFilter(condition=[=($6, 2001)]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject(ss_sold_date_sk=[$0], ss_cdemo_sk=[$4], ss_hdemo_sk=[$5], ss_addr_sk=[$6], ss_quantity=[$10], ss_ext_sales_price=[$15], ss_ext_wholesale_cost=[$16], BETWEEN=[BETWEEN(false, $22, 100, 200)], BETWEEN9=[BETWEEN(false, $22, 150, 300)], BETWEEN10=[BETWEEN(false, $22, 50, 250)], BETWEEN11=[BETWEEN(false, $13, 100, 150)], BETWEEN12=[BETWEEN(false, $13, 50, 100)], BETWEEN13=[BETWEEN(false, $13, 150, 200)]) - HiveFilter(condition=[AND(OR(BETWEEN(false, $13, 100, 150), BETWEEN(false, $13, 50, 100), BETWEEN(false, $13, 150, 200)), OR(BETWEEN(false, $22, 100, 200), BETWEEN(false, $22, 150, 300), BETWEEN(false, $22, 50, 250)), IS NOT NULL($7), IS NOT NULL($4), IS NOT NULL($5), IS NOT NULL($6), IS NOT NULL($0))]) + HiveProject(ss_sold_date_sk=[$0], ss_cdemo_sk=[$4], ss_hdemo_sk=[$5], ss_addr_sk=[$6], ss_quantity=[$10], ss_ext_sales_price=[$15], ss_ext_wholesale_cost=[$16], BETWEEN=[BETWEEN(false, $22, CAST(100):DECIMAL(12, 2), CAST(200):DECIMAL(12, 2))], BETWEEN9=[BETWEEN(false, $22, CAST(150):DECIMAL(12, 2), CAST(300):DECIMAL(12, 2))], BETWEEN10=[BETWEEN(false, $22, CAST(50):DECIMAL(12, 2), CAST(250):DECIMAL(12, 2))], BETWEEN11=[BETWEEN(false, $13, 100, 150)], BETWEEN12=[BETWEEN(false, $13, 50, 100)], BETWEEN13=[BETWEEN(false, $13, 150, 200)]) + HiveFilter(condition=[AND(OR(BETWEEN(false, $13, 100, 150), BETWEEN(false, $13, 50, 100), BETWEEN(false, $13, 150, 200)), OR(BETWEEN(false, $22, CAST(100):DECIMAL(12, 2), CAST(200):DECIMAL(12, 2)), BETWEEN(false, $22, CAST(150):DECIMAL(12, 2), CAST(300):DECIMAL(12, 2)), BETWEEN(false, $22, CAST(50):DECIMAL(12, 2), CAST(250):DECIMAL(12, 2))), IS NOT NULL($7), IS NOT NULL($4), IS NOT NULL($5), IS NOT NULL($6), IS NOT NULL($0))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query14.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query14.q.out index 118d23b577..00f6122549 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query14.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query14.q.out @@ -290,7 +290,7 @@ HiveSortLimit(sort0=[$0], sort1=[$1], sort2=[$2], sort3=[$3], dir0=[ASC], dir1=[ HiveProject(d_date_sk=[$0]) HiveFilter(condition=[AND(=($6, 2000), =($8, 11))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject($f0=[/($0, $1)]) + HiveProject(average_sales=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($0)], agg#1=[count($0)]) HiveProject($f0=[*(CAST($0):DECIMAL(10, 0), $1)]) HiveUnion(all=[true]) @@ -383,7 +383,7 @@ HiveSortLimit(sort0=[$0], sort1=[$1], sort2=[$2], sort3=[$3], dir0=[ASC], dir1=[ HiveProject(d_date_sk=[$0]) HiveFilter(condition=[AND(=($6, 2000), =($8, 11))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject($f0=[/($0, $1)]) + HiveProject(average_sales=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($0)], agg#1=[count($0)]) HiveProject($f0=[*(CAST($0):DECIMAL(10, 0), $1)]) HiveUnion(all=[true]) @@ -476,7 +476,7 @@ HiveSortLimit(sort0=[$0], sort1=[$1], sort2=[$2], sort3=[$3], dir0=[ASC], dir1=[ HiveProject(d_date_sk=[$0]) HiveFilter(condition=[AND(=($6, 2000), =($8, 11))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject($f0=[/($0, $1)]) + HiveProject(average_sales=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($0)], agg#1=[count($0)]) HiveProject($f0=[*(CAST($0):DECIMAL(10, 0), $1)]) HiveUnion(all=[true]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query16.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query16.q.out index 251fd6861d..2155944973 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query16.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query16.q.out @@ -89,7 +89,7 @@ HiveProject(order count=[$0], total shipping cost=[$1], total net profit=[$2]) HiveFilter(condition=[AND(IS NOT NULL($2), IS NOT NULL($10), IS NOT NULL($11))]) HiveTableScan(table=[[default, catalog_sales]], table:alias=[cs1]) HiveProject(d_date_sk=[$0], d_date=[$2]) - HiveFilter(condition=[BETWEEN(false, CAST($2):TIMESTAMP(9), 2001-04-01 00:00:00, 2001-05-31 00:00:00)]) + HiveFilter(condition=[BETWEEN(false, CAST($2):TIMESTAMP(9), CAST(_UTF-16LE'2001-4-01'):TIMESTAMP(9), 2001-05-31 00:00:00)]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(cc_call_center_sk=[$0], cc_county=[$25]) HiveFilter(condition=[IN($25, _UTF-16LE'Ziebach County', _UTF-16LE'Levy County', _UTF-16LE'Huron County', _UTF-16LE'Franklin Parish', _UTF-16LE'Daviess County')]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query18.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query18.q.out index 1aeb29aaf6..c7d0c08fbd 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query18.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query18.q.out @@ -80,7 +80,7 @@ POSTHOOK: Input: default@item POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$1], sort1=[$2], sort2=[$3], sort3=[$0], dir0=[ASC], dir1=[ASC], dir2=[ASC], dir3=[ASC], fetch=[100]) - HiveProject($f0=[$0], $f1=[$3], $f2=[$2], $f3=[$1], $f4=[/($4, $5)], $f5=[/($6, $7)], $f6=[/($8, $9)], $f7=[/($10, $11)], $f8=[/($12, $13)], $f9=[/($14, $15)], $f10=[/($16, $17)]) + HiveProject(i_item_id=[$0], ca_country=[$3], ca_state=[$2], ca_county=[$1], agg1=[/($4, $5)], agg2=[/($6, $7)], agg3=[/($8, $9)], agg4=[/($10, $11)], agg5=[/($12, $13)], agg6=[/($14, $15)], agg7=[/($16, $17)]) HiveAggregate(group=[{1, 7, 8, 9}], groups=[[{1, 7, 8, 9}, {1, 8, 9}, {1, 9}, {1}, {}]], agg#0=[sum($14)], agg#1=[count($14)], agg#2=[sum($15)], agg#3=[count($15)], agg#4=[sum($16)], agg#5=[count($16)], agg#6=[sum($17)], agg#7=[count($17)], agg#8=[sum($18)], agg#9=[count($18)], agg#10=[sum($5)], agg#11=[count($5)], agg#12=[sum($21)], agg#13=[count($21)]) HiveJoin(condition=[=($3, $22)], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[=($13, $0)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query21.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query21.q.out index f304762b14..a2302ccae1 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query21.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query21.q.out @@ -69,7 +69,7 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], sort1=[$1], dir0=[ASC], dir1=[ASC], fetch=[100]) HiveProject($f0=[$0], $f1=[$1], $f2=[$2], $f3=[$3]) - HiveFilter(condition=[CASE(>($2, 0), BETWEEN(false, /(CAST($3):DOUBLE, CAST($2):DOUBLE), 6.66667E-1, 1.5E0), null)]) + HiveFilter(condition=[CASE(>($2, 0), BETWEEN(false, /(CAST($3):DOUBLE, CAST($2):DOUBLE), 6.66667E-1, 1.5E0), false)]) HiveAggregate(group=[{0, 1}], agg#0=[sum($2)], agg#1=[sum($3)]) HiveProject($f0=[$1], $f1=[$10], $f2=[CASE($7, $5, 0)], $f3=[CASE($8, $5, 0)]) HiveJoin(condition=[=($4, $0)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query22.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query22.q.out index 77f91f696c..94ce690ac5 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query22.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query22.q.out @@ -52,7 +52,7 @@ POSTHOOK: Input: default@warehouse POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$4], sort1=[$0], sort2=[$1], sort3=[$2], sort4=[$3], dir0=[ASC], dir1=[ASC], dir2=[ASC], dir3=[ASC], dir4=[ASC], fetch=[100]) - HiveProject($f0=[$3], $f1=[$0], $f2=[$1], $f3=[$2], $f4=[/(CAST($4):DOUBLE, $5)]) + HiveProject(i_product_name=[$3], i_brand=[$0], i_class=[$1], i_category=[$2], qoh=[/(CAST($4):DOUBLE, $5)]) HiveAggregate(group=[{1, 2, 3, 4}], groups=[[{1, 2, 3, 4}, {1, 2, 4}, {1, 4}, {4}, {}]], agg#0=[sum($7)], agg#1=[count($7)]) HiveJoin(condition=[=($6, $0)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(i_item_sk=[$0], i_brand=[$8], i_class=[$10], i_category=[$12], i_product_name=[$21]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query23.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query23.q.out index e5b0d19715..6ebcadf614 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query23.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query23.q.out @@ -127,7 +127,7 @@ HiveSortLimit(fetch=[100]) HiveProject($f0=[*(CAST($4):DECIMAL(10, 0), $5)]) HiveSemiJoin(condition=[=($3, $8)], joinType=[inner]) HiveJoin(condition=[=($2, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0]) + HiveProject(c_customer_sk=[$0]) HiveJoin(condition=[>($1, *(0.95, $3))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(ss_customer_sk=[$0], $f1=[$1]) HiveAggregate(group=[{0}], agg#0=[sum($1)]) @@ -186,7 +186,7 @@ HiveSortLimit(fetch=[100]) HiveProject($f0=[*(CAST($4):DECIMAL(10, 0), $5)]) HiveSemiJoin(condition=[=($2, $8)], joinType=[inner]) HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0]) + HiveProject(c_customer_sk=[$0]) HiveJoin(condition=[>($1, *(0.95, $3))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(ss_customer_sk=[$0], $f1=[$1]) HiveAggregate(group=[{0}], agg#0=[sum($1)]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query24.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query24.q.out index 41d96ea303..51be1ca9a5 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query24.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query24.q.out @@ -114,7 +114,7 @@ POSTHOOK: Input: default@store_returns POSTHOOK: Input: default@store_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: -HiveProject($f0=[$0], $f1=[$1], $f2=[$2], $f3=[$3]) +HiveProject(c_last_name=[$0], c_first_name=[$1], s_store_name=[$2], paid=[$3]) HiveJoin(condition=[>($3, $4)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_last_name=[$1], c_first_name=[$0], s_store_name=[$2], $f3=[$3]) HiveAggregate(group=[{0, 1, 3}], agg#0=[sum($9)]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query26.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query26.q.out index f89362300e..008a47920f 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query26.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query26.q.out @@ -52,7 +52,7 @@ POSTHOOK: Input: default@promotion POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) - HiveProject($f0=[$0], $f1=[/(CAST($1):DOUBLE, $2)], $f2=[/($3, $4)], $f3=[/($5, $6)], $f4=[/($7, $8)]) + HiveProject(i_item_id=[$0], agg1=[/(CAST($1):DOUBLE, $2)], agg2=[/($3, $4)], agg3=[/($5, $6)], agg4=[/($7, $8)]) HiveAggregate(group=[{1}], agg#0=[sum($6)], agg#1=[count($6)], agg#2=[sum($7)], agg#3=[count($7)], agg#4=[sum($9)], agg#5=[count($9)], agg#6=[sum($8)], agg#7=[count($8)]) HiveJoin(condition=[=($4, $0)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(i_item_sk=[$0], i_item_id=[$1]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query28.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query28.q.out index 643e5b6259..14cfaf2c34 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query28.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query28.q.out @@ -113,34 +113,34 @@ POSTHOOK: Input: default@store_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(fetch=[100]) - HiveProject($f0=[$0], $f1=[$1], $f2=[$2], $f00=[$15], $f10=[$16], $f20=[$17], $f01=[$12], $f11=[$13], $f21=[$14], $f02=[$9], $f12=[$10], $f22=[$11], $f03=[$6], $f13=[$7], $f23=[$8], $f04=[$3], $f14=[$4], $f24=[$5]) + HiveProject(b1_lp=[$0], b1_cnt=[$1], b1_cntd=[$2], b2_lp=[$15], b2_cnt=[$16], b2_cntd=[$17], b3_lp=[$12], b3_cnt=[$13], b3_cntd=[$14], b4_lp=[$9], b4_cnt=[$10], b4_cntd=[$11], b5_lp=[$6], b5_cnt=[$7], b5_cntd=[$8], b6_lp=[$3], b6_cnt=[$4], b6_cntd=[$5]) HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[/($0, $1)], $f1=[$1], $f2=[$2]) + HiveProject(b1_lp=[/($0, $1)], b1_cnt=[$1], b1_cntd=[$2]) HiveAggregate(group=[{}], agg#0=[sum($12)], agg#1=[count($12)], agg#2=[count(DISTINCT $12)]) - HiveFilter(condition=[AND(BETWEEN(false, $10, 0, 5), OR(BETWEEN(false, $12, 11, 21), BETWEEN(false, $19, 460, 1460), BETWEEN(false, $11, 14, 34)))]) + HiveFilter(condition=[AND(BETWEEN(false, $10, 0, 5), OR(BETWEEN(false, $12, CAST(11):DECIMAL(12, 2), 21), BETWEEN(false, $19, CAST(460):DECIMAL(12, 2), 1460), BETWEEN(false, $11, CAST(14):DECIMAL(12, 2), 34)))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)], $f1=[$1], $f2=[$2]) + HiveProject(b6_lp=[/($0, $1)], b6_cnt=[$1], b6_cntd=[$2]) HiveAggregate(group=[{}], agg#0=[sum($12)], agg#1=[count($12)], agg#2=[count(DISTINCT $12)]) - HiveFilter(condition=[AND(BETWEEN(false, $10, 26, 30), OR(BETWEEN(false, $12, 28, 38), BETWEEN(false, $19, 2513, 3513), BETWEEN(false, $11, 42, 62)))]) + HiveFilter(condition=[AND(BETWEEN(false, $10, 26, 30), OR(BETWEEN(false, $12, CAST(28):DECIMAL(12, 2), 38), BETWEEN(false, $19, CAST(2513):DECIMAL(12, 2), 3513), BETWEEN(false, $11, CAST(42):DECIMAL(12, 2), 62)))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)], $f1=[$1], $f2=[$2]) + HiveProject(b5_lp=[/($0, $1)], b5_cnt=[$1], b5_cntd=[$2]) HiveAggregate(group=[{}], agg#0=[sum($12)], agg#1=[count($12)], agg#2=[count(DISTINCT $12)]) - HiveFilter(condition=[AND(BETWEEN(false, $10, 21, 25), OR(BETWEEN(false, $12, 135, 145), BETWEEN(false, $19, 14180, 15180), BETWEEN(false, $11, 38, 58)))]) + HiveFilter(condition=[AND(BETWEEN(false, $10, 21, 25), OR(BETWEEN(false, $12, CAST(135):DECIMAL(12, 2), 145), BETWEEN(false, $19, CAST(14180):DECIMAL(12, 2), 15180), BETWEEN(false, $11, CAST(38):DECIMAL(12, 2), 58)))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)], $f1=[$1], $f2=[$2]) + HiveProject(b4_lp=[/($0, $1)], b4_cnt=[$1], b4_cntd=[$2]) HiveAggregate(group=[{}], agg#0=[sum($12)], agg#1=[count($12)], agg#2=[count(DISTINCT $12)]) - HiveFilter(condition=[AND(BETWEEN(false, $10, 16, 20), OR(BETWEEN(false, $12, 142, 152), BETWEEN(false, $19, 3054, 4054), BETWEEN(false, $11, 80, 100)))]) + HiveFilter(condition=[AND(BETWEEN(false, $10, 16, 20), OR(BETWEEN(false, $12, CAST(142):DECIMAL(12, 2), 152), BETWEEN(false, $19, CAST(3054):DECIMAL(12, 2), 4054), BETWEEN(false, $11, CAST(80):DECIMAL(12, 2), 100)))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)], $f1=[$1], $f2=[$2]) + HiveProject(b3_lp=[/($0, $1)], b3_cnt=[$1], b3_cntd=[$2]) HiveAggregate(group=[{}], agg#0=[sum($12)], agg#1=[count($12)], agg#2=[count(DISTINCT $12)]) - HiveFilter(condition=[AND(BETWEEN(false, $10, 11, 15), OR(BETWEEN(false, $12, 66, 76), BETWEEN(false, $19, 920, 1920), BETWEEN(false, $11, 4, 24)))]) + HiveFilter(condition=[AND(BETWEEN(false, $10, 11, 15), OR(BETWEEN(false, $12, CAST(66):DECIMAL(12, 2), 76), BETWEEN(false, $19, CAST(920):DECIMAL(12, 2), 1920), BETWEEN(false, $11, CAST(4):DECIMAL(12, 2), 24)))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)], $f1=[$1], $f2=[$2]) + HiveProject(b2_lp=[/($0, $1)], b2_cnt=[$1], b2_cntd=[$2]) HiveAggregate(group=[{}], agg#0=[sum($12)], agg#1=[count($12)], agg#2=[count(DISTINCT $12)]) - HiveFilter(condition=[AND(BETWEEN(false, $10, 6, 10), OR(BETWEEN(false, $12, 91, 101), BETWEEN(false, $19, 1430, 2430), BETWEEN(false, $11, 32, 52)))]) + HiveFilter(condition=[AND(BETWEEN(false, $10, 6, 10), OR(BETWEEN(false, $12, CAST(91):DECIMAL(12, 2), 101), BETWEEN(false, $19, CAST(1430):DECIMAL(12, 2), 2430), BETWEEN(false, $11, CAST(32):DECIMAL(12, 2), 52)))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query31.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query31.q.out index f8e31a23aa..98e1bf5972 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query31.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query31.q.out @@ -112,7 +112,7 @@ POSTHOOK: Input: default@web_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveProject(ca_county=[$8], d_year=[CAST(2000):INTEGER], web_q1_q2_increase=[/($6, $1)], store_q1_q2_increase=[/($9, $11)], web_q2_q3_increase=[/($4, $6)], store_q2_q3_increase=[/($13, $9)]) - HiveJoin(condition=[AND(AND(=($8, $0), CASE(>($11, 0), CASE($2, >(/($6, $1), /($9, $11)), >(null, /($9, $11))), CASE($2, >(/($6, $1), null), null))), CASE(>($9, 0), CASE($7, >(/($4, $6), /($13, $9)), >(null, /($13, $9))), CASE($7, >(/($4, $6), null), null)))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[AND(AND(=($8, $0), CASE(>($11, 0), CASE($2, >(/($6, $1), /($9, $11)), null), null)), CASE(>($9, 0), CASE($7, >(/($4, $6), /($13, $9)), null), null))], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[=($0, $5)], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject($f0=[$0], $f3=[$1], >=[>($1, 0)]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query32.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query32.q.out index c7fb1dd7a8..1e638c7114 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query32.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query32.q.out @@ -70,7 +70,7 @@ HiveSortLimit(fetch=[100]) HiveFilter(condition=[IS NOT NULL($0)]) HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales]) HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[BETWEEN(false, CAST($2):TIMESTAMP(9), 1998-03-18 00:00:00, 1998-06-16 00:00:00)]) + HiveFilter(condition=[BETWEEN(false, CAST($2):TIMESTAMP(9), CAST(_UTF-16LE'1998-03-18'):TIMESTAMP(9), 1998-06-16 00:00:00)]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(cs_item_sk=[$0], CAST3=[$1], i_item_sk=[$2]) HiveJoin(condition=[=($0, $2)], joinType=[inner], algorithm=[none], cost=[not available]) @@ -81,7 +81,7 @@ HiveSortLimit(fetch=[100]) HiveFilter(condition=[IS NOT NULL($0)]) HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales]) HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[BETWEEN(false, CAST($2):TIMESTAMP(9), 1998-03-18 00:00:00, 1998-06-16 00:00:00)]) + HiveFilter(condition=[BETWEEN(false, CAST($2):TIMESTAMP(9), CAST(_UTF-16LE'1998-03-18'):TIMESTAMP(9), 1998-06-16 00:00:00)]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(i_item_sk=[$0]) HiveFilter(condition=[=($13, 269)]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query34.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query34.q.out index 6e7384e1dd..6ee15173ef 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query34.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query34.q.out @@ -77,7 +77,7 @@ HiveSortLimit(sort0=[$0], sort1=[$1], sort2=[$2], sort3=[$3], dir0=[ASC], dir1=[ HiveProject(c_customer_sk=[$0], c_salutation=[$7], c_first_name=[$8], c_last_name=[$9], c_preferred_cust_flag=[$10]) HiveTableScan(table=[[default, customer]], table:alias=[customer]) HiveProject(ss_ticket_number=[$0], ss_customer_sk=[$1], $f2=[$2]) - HiveFilter(condition=[BETWEEN(false, $2, 15, 20)]) + HiveFilter(condition=[BETWEEN(false, $2, CAST(15):BIGINT, CAST(20):BIGINT)]) HiveProject(ss_ticket_number=[$1], ss_customer_sk=[$0], $f2=[$2]) HiveAggregate(group=[{1, 4}], agg#0=[count()]) HiveJoin(condition=[=($3, $7)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query36.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query36.q.out index d4031261c7..d2f9280da5 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query36.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query36.q.out @@ -69,7 +69,7 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveProject(gross_margin=[$0], i_category=[$1], i_class=[$2], lochierarchy=[$3], rank_within_parent=[$4]) HiveSortLimit(sort0=[$3], sort1=[$5], sort2=[$4], dir0=[DESC-nulls-last], dir1=[ASC], dir2=[ASC], fetch=[100]) - HiveProject(gross_margin=[/($2, $3)], i_category=[$0], i_class=[$1], lochierarchy=[+(grouping($4, 1), grouping($4, 0))], rank_within_parent=[rank() OVER (PARTITION BY +(grouping($4, 1), grouping($4, 0)), CASE(=(grouping($4, 0), 0), $0, null) ORDER BY /($2, $3) NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)], (tok_function when (= (tok_table_or_col lochierarchy) 0) (tok_table_or_col i_category))=[CASE(=(+(grouping($4, 1), grouping($4, 0)), 0), $0, null)]) + HiveProject(gross_margin=[/($2, $3)], i_category=[$0], i_class=[$1], lochierarchy=[+(grouping($4, 1), grouping($4, 0))], rank_within_parent=[rank() OVER (PARTITION BY +(grouping($4, 1), grouping($4, 0)), CASE(=(grouping($4, 0), CAST(0):BIGINT), $0, null) ORDER BY /($2, $3) NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)], (tok_function when (= (tok_table_or_col lochierarchy) 0) (tok_table_or_col i_category))=[CASE(=(+(grouping($4, 1), grouping($4, 0)), 0), $0, null)]) HiveProject($f0=[$0], $f1=[$1], $f2=[$2], $f3=[$3], GROUPING__ID=[$4]) HiveAggregate(group=[{0, 1}], groups=[[{0, 1}, {0}, {}]], agg#0=[sum($2)], agg#1=[sum($3)], GROUPING__ID=[GROUPING__ID()]) HiveProject($f0=[$9], $f1=[$8], $f2=[$4], $f3=[$3]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query37.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query37.q.out index f054717d70..b9f6132c34 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query37.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query37.q.out @@ -49,7 +49,7 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(cs_item_sk=[$15]) HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales]) HiveProject(i_item_sk=[$0], i_item_id=[$1], i_item_desc=[$4], i_current_price=[$5]) - HiveFilter(condition=[AND(IN($13, 678, 964, 918, 849), BETWEEN(false, $5, 22, 52))]) + HiveFilter(condition=[AND(IN($13, 678, 964, 918, 849), BETWEEN(false, $5, CAST(22):DECIMAL(12, 2), 52))]) HiveTableScan(table=[[default, item]], table:alias=[item]) HiveProject(inv_date_sk=[$0], inv_item_sk=[$1], d_date_sk=[$2]) HiveJoin(condition=[=($2, $0)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query4.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query4.q.out index 9668e0f4a1..312445ab99 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query4.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query4.q.out @@ -229,8 +229,8 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(customer_preferred_cust_flag=[$1]) - HiveJoin(condition=[AND(=($0, $10), CASE(CAST(IS NOT NULL($11)):BOOLEAN, CASE($14, >(/($6, $13), /($2, $11)), >(null, /($2, $11))), CASE($14, >(/($6, $13), null), null)))], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0], $f3=[$3], $f8=[$7]) + HiveJoin(condition=[AND(=($0, $10), CASE(CAST(IS NOT NULL($11)):BOOLEAN, CASE($14, >(/($6, $13), /($2, $11)), null), null))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(customer_id=[$0], customer_preferred_cust_flag=[$3], year_total=[$7]) HiveAggregate(group=[{1, 2, 3, 4, 5, 6, 7}], agg#0=[sum($10)]) HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], c_customer_id=[$1], c_first_name=[$8], c_last_name=[$9], c_preferred_cust_flag=[$10], c_birth_country=[$14], c_login=[$15], c_email_address=[$16]) @@ -242,8 +242,8 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(d_date_sk=[$0]) HiveFilter(condition=[=($6, 2002)]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveJoin(condition=[AND(=($7, $0), CASE($6, CASE($11, >(/($3, $10), /($1, $5)), >(null, /($1, $5))), CASE($11, >(/($3, $10), null), null)))], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0], $f8=[$7]) + HiveJoin(condition=[AND(=($7, $0), CASE($6, CASE($11, >(/($3, $10), /($1, $5)), null), null))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(customer_id=[$0], year_total=[$7]) HiveAggregate(group=[{1, 2, 3, 4, 5, 6, 7}], agg#0=[sum($10)]) HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], c_customer_id=[$1], c_first_name=[$8], c_last_name=[$9], c_preferred_cust_flag=[$10], c_birth_country=[$14], c_login=[$15], c_email_address=[$16]) @@ -256,7 +256,7 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveFilter(condition=[=($6, 2002)]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveJoin(condition=[=($5, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0], $f8=[$7]) + HiveProject(customer_id=[$0], year_total=[$7]) HiveAggregate(group=[{1, 2, 3, 4, 5, 6, 7}], agg#0=[sum($10)]) HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], c_customer_id=[$1], c_first_name=[$8], c_last_name=[$9], c_preferred_cust_flag=[$10], c_birth_country=[$14], c_login=[$15], c_email_address=[$16]) @@ -283,7 +283,7 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(d_date_sk=[$0]) HiveFilter(condition=[=($6, 2001)]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject($f0=[$0], $f8=[$7]) + HiveProject(customer_id=[$0], year_total=[$7]) HiveFilter(condition=[>($7, 0)]) HiveAggregate(group=[{1, 2, 3, 4, 5, 6, 7}], agg#0=[sum($10)]) HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query42.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query42.q.out index 8f2f79f346..b1c5d87c2d 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query42.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query42.q.out @@ -49,20 +49,19 @@ POSTHOOK: Input: default@item POSTHOOK: Input: default@store_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: -HiveSortLimit(fetch=[100]) - HiveProject(d_year=[CAST(1998):INTEGER], i_category_id=[$0], i_category=[$1], _o__c3=[$2]) - HiveSortLimit(sort0=[$3], sort1=[$0], sort2=[$1], dir0=[DESC-nulls-last], dir1=[ASC], dir2=[ASC]) - HiveProject(i_category_id=[$0], i_category=[$1], _o__c3=[$2], (tok_function sum (tok_table_or_col ss_ext_sales_price))=[$2]) - HiveAggregate(group=[{5, 6}], agg#0=[sum($2)]) - HiveJoin(condition=[=($1, $4)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_ext_sales_price=[$15]) - HiveFilter(condition=[IS NOT NULL($0)]) - HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[AND(=($8, 12), =($6, 1998))]) - HiveTableScan(table=[[default, date_dim]], table:alias=[dt]) - HiveProject(i_item_sk=[$0], i_category_id=[$11], i_category=[$12]) - HiveFilter(condition=[=($20, 1)]) - HiveTableScan(table=[[default, item]], table:alias=[item]) +HiveProject(d_year=[CAST(1998):INTEGER], i_category_id=[$0], i_category=[$1], _o__c3=[$2]) + HiveSortLimit(sort0=[$3], sort1=[$0], sort2=[$1], dir0=[DESC-nulls-last], dir1=[ASC], dir2=[ASC], fetch=[100]) + HiveProject(i_category_id=[$0], i_category=[$1], _o__c3=[$2], (tok_function sum (tok_table_or_col ss_ext_sales_price))=[$2]) + HiveAggregate(group=[{5, 6}], agg#0=[sum($2)]) + HiveJoin(condition=[=($1, $4)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_ext_sales_price=[$15]) + HiveFilter(condition=[IS NOT NULL($0)]) + HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) + HiveProject(d_date_sk=[$0]) + HiveFilter(condition=[AND(=($8, 12), =($6, 1998))]) + HiveTableScan(table=[[default, date_dim]], table:alias=[dt]) + HiveProject(i_item_sk=[$0], i_category_id=[$11], i_category=[$12]) + HiveFilter(condition=[=($20, 1)]) + HiveTableScan(table=[[default, item]], table:alias=[item]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query46.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query46.q.out index 9d21449b65..df36f9ba14 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query46.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query46.q.out @@ -82,32 +82,32 @@ POSTHOOK: Input: default@store_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], sort1=[$1], sort2=[$2], sort3=[$3], sort4=[$4], dir0=[ASC], dir1=[ASC], dir2=[ASC], dir3=[ASC], dir4=[ASC], fetch=[100]) - HiveProject(c_last_name=[$5], c_first_name=[$4], ca_city=[$1], bought_city=[$8], ss_ticket_number=[$6], amt=[$9], profit=[$10]) - HiveJoin(condition=[AND(=($3, $0), <>($1, $8))], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(ca_address_sk=[$0], ca_city=[$6]) - HiveTableScan(table=[[default, customer_address]], table:alias=[current_addr]) - HiveJoin(condition=[=($5, $0)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(c_last_name=[$3], c_first_name=[$2], ca_city=[$5], bought_city=[$8], ss_ticket_number=[$6], amt=[$9], profit=[$10]) + HiveJoin(condition=[AND(<>($5, $8), =($7, $0))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[=($1, $4)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], c_current_addr_sk=[$4], c_first_name=[$8], c_last_name=[$9]) HiveFilter(condition=[IS NOT NULL($4)]) HiveTableScan(table=[[default, customer]], table:alias=[customer]) - HiveProject(ss_ticket_number=[$3], ss_customer_sk=[$1], bought_city=[$0], amt=[$4], profit=[$5]) - HiveAggregate(group=[{1, 3, 5, 7}], agg#0=[sum($8)], agg#1=[sum($9)]) - HiveJoin(condition=[=($5, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(ca_address_sk=[$0], ca_city=[$6]) - HiveTableScan(table=[[default, customer_address]], table:alias=[customer_address]) - HiveJoin(condition=[=($2, $10)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveJoin(condition=[=($4, $9)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveJoin(condition=[=($0, $8)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(ss_sold_date_sk=[$0], ss_customer_sk=[$3], ss_hdemo_sk=[$5], ss_addr_sk=[$6], ss_store_sk=[$7], ss_ticket_number=[$9], ss_coupon_amt=[$19], ss_net_profit=[$22]) - HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($7), IS NOT NULL($5), IS NOT NULL($6), IS NOT NULL($3))]) - HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[AND(IN($7, 6, 0), IN($6, 1998, 1999, 2000))]) - HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject(s_store_sk=[$0]) - HiveFilter(condition=[IN($22, _UTF-16LE'Cedar Grove', _UTF-16LE'Wildwood', _UTF-16LE'Union', _UTF-16LE'Salem', _UTF-16LE'Highland Park')]) - HiveTableScan(table=[[default, store]], table:alias=[store]) - HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[OR(=($3, 2), =($4, 1))]) - HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) + HiveProject(ca_address_sk=[$0], ca_city=[$6]) + HiveTableScan(table=[[default, customer_address]], table:alias=[current_addr]) + HiveProject(ss_ticket_number=[$3], ss_customer_sk=[$1], bought_city=[$0], amt=[$4], profit=[$5]) + HiveAggregate(group=[{1, 3, 5, 7}], agg#0=[sum($8)], agg#1=[sum($9)]) + HiveJoin(condition=[=($5, $0)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(ca_address_sk=[$0], ca_city=[$6]) + HiveTableScan(table=[[default, customer_address]], table:alias=[customer_address]) + HiveJoin(condition=[=($2, $10)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[=($4, $9)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[=($0, $8)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(ss_sold_date_sk=[$0], ss_customer_sk=[$3], ss_hdemo_sk=[$5], ss_addr_sk=[$6], ss_store_sk=[$7], ss_ticket_number=[$9], ss_coupon_amt=[$19], ss_net_profit=[$22]) + HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($7), IS NOT NULL($5), IS NOT NULL($6), IS NOT NULL($3))]) + HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) + HiveProject(d_date_sk=[$0]) + HiveFilter(condition=[AND(IN($7, 6, 0), IN($6, 1998, 1999, 2000))]) + HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) + HiveProject(s_store_sk=[$0]) + HiveFilter(condition=[IN($22, _UTF-16LE'Cedar Grove', _UTF-16LE'Wildwood', _UTF-16LE'Union', _UTF-16LE'Salem', _UTF-16LE'Highland Park')]) + HiveTableScan(table=[[default, store]], table:alias=[store]) + HiveProject(hd_demo_sk=[$0]) + HiveFilter(condition=[OR(=($3, 2), =($4, 1))]) + HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query48.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query48.q.out index 12d59348f7..5d04e21417 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query48.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query48.q.out @@ -154,7 +154,7 @@ HiveAggregate(group=[{}], agg#0=[sum($9)]) HiveProject(cd_demo_sk=[$0]) HiveFilter(condition=[AND(=($2, _UTF-16LE'M'), =($3, _UTF-16LE'4 yr Degree'))]) HiveTableScan(table=[[default, customer_demographics]], table:alias=[customer_demographics]) - HiveProject(ss_sold_date_sk=[$0], ss_cdemo_sk=[$4], ss_addr_sk=[$6], ss_quantity=[$10], BETWEEN=[BETWEEN(false, $22, 0, 2000)], BETWEEN6=[BETWEEN(false, $22, 150, 3000)], BETWEEN7=[BETWEEN(false, $22, 50, 25000)]) - HiveFilter(condition=[AND(OR(BETWEEN(false, $13, 100, 150), BETWEEN(false, $13, 50, 100), BETWEEN(false, $13, 150, 200)), OR(BETWEEN(false, $22, 0, 2000), BETWEEN(false, $22, 150, 3000), BETWEEN(false, $22, 50, 25000)), IS NOT NULL($7), IS NOT NULL($4), IS NOT NULL($6), IS NOT NULL($0))]) + HiveProject(ss_sold_date_sk=[$0], ss_cdemo_sk=[$4], ss_addr_sk=[$6], ss_quantity=[$10], BETWEEN=[BETWEEN(false, $22, CAST(0):DECIMAL(12, 2), CAST(2000):DECIMAL(12, 2))], BETWEEN6=[BETWEEN(false, $22, CAST(150):DECIMAL(12, 2), CAST(3000):DECIMAL(12, 2))], BETWEEN7=[BETWEEN(false, $22, CAST(50):DECIMAL(12, 2), CAST(25000):DECIMAL(12, 2))]) + HiveFilter(condition=[AND(OR(BETWEEN(false, $13, 100, 150), BETWEEN(false, $13, 50, 100), BETWEEN(false, $13, 150, 200)), OR(BETWEEN(false, $22, CAST(0):DECIMAL(12, 2), CAST(2000):DECIMAL(12, 2)), BETWEEN(false, $22, CAST(150):DECIMAL(12, 2), CAST(3000):DECIMAL(12, 2)), BETWEEN(false, $22, CAST(50):DECIMAL(12, 2), CAST(25000):DECIMAL(12, 2))), IS NOT NULL($7), IS NOT NULL($4), IS NOT NULL($6), IS NOT NULL($0))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query51.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query51.q.out index 3d81b6bcb5..d06e6e5869 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query51.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query51.q.out @@ -100,8 +100,8 @@ HiveSortLimit(sort0=[$0], sort1=[$1], dir0=[ASC], dir1=[ASC], fetch=[100]) HiveFilter(condition=[>($4, $5)]) HiveProject(item_sk=[CASE(IS NOT NULL($3), $3, $0)], d_date=[CASE(IS NOT NULL($4), $4, $1)], web_sales=[$5], store_sales=[$2], max_window_0=[max($5) OVER (PARTITION BY CASE(IS NOT NULL($3), $3, $0) ORDER BY CASE(IS NOT NULL($4), $4, $1) NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)], max_window_1=[max($2) OVER (PARTITION BY CASE(IS NOT NULL($3), $3, $0) ORDER BY CASE(IS NOT NULL($4), $4, $1) NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)]) HiveJoin(condition=[AND(=($3, $0), =($4, $1))], joinType=[full], algorithm=[none], cost=[not available]) - HiveProject((tok_table_or_col ss_item_sk)=[$0], (tok_table_or_col d_date)=[$1], sum_window_0=[$2]) - HiveProject((tok_table_or_col ss_item_sk)=[$0], (tok_table_or_col d_date)=[$1], sum_window_0=[sum($2) OVER (PARTITION BY $0 ORDER BY $1 NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)], window_col_0=[$2]) + HiveProject(item_sk=[$0], d_date=[$1], cume_sales=[$2]) + HiveProject(item_sk=[$0], d_date=[$1], cume_sales=[sum($2) OVER (PARTITION BY $0 ORDER BY $1 NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)], window_col_0=[$2]) HiveProject(ss_item_sk=[$0], d_date=[$1], $f2=[$2]) HiveAggregate(group=[{1, 4}], agg#0=[sum($2)]) HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) @@ -111,8 +111,8 @@ HiveSortLimit(sort0=[$0], sort1=[$1], dir0=[ASC], dir1=[ASC], fetch=[100]) HiveProject(d_date_sk=[$0], d_date=[$2]) HiveFilter(condition=[BETWEEN(false, $3, 1212, 1223)]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject((tok_table_or_col ws_item_sk)=[$0], (tok_table_or_col d_date)=[$1], sum_window_0=[$2]) - HiveProject((tok_table_or_col ws_item_sk)=[$0], (tok_table_or_col d_date)=[$1], sum_window_0=[sum($2) OVER (PARTITION BY $0 ORDER BY $1 NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)], window_col_0=[$2]) + HiveProject(item_sk=[$0], d_date=[$1], cume_sales=[$2]) + HiveProject(item_sk=[$0], d_date=[$1], cume_sales=[sum($2) OVER (PARTITION BY $0 ORDER BY $1 NULLS LAST ROWS BETWEEN CURRENT ROW AND 2147483647 PRECEDING)], window_col_0=[$2]) HiveProject(ws_item_sk=[$0], d_date=[$1], $f2=[$2]) HiveAggregate(group=[{1, 4}], agg#0=[sum($2)]) HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query53.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query53.q.out index bac3f77538..930025f0b5 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query53.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query53.q.out @@ -65,7 +65,7 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$2], sort1=[$1], sort2=[$0], dir0=[ASC], dir1=[ASC], dir2=[ASC], fetch=[100]) HiveProject((tok_table_or_col i_manufact_id)=[$0], (tok_function sum (tok_table_or_col ss_sales_price))=[$1], avg_window_0=[$2]) - HiveFilter(condition=[CASE(>($2, 0), >(/(ABS(-($1, $2)), $2), 0.1), null)]) + HiveFilter(condition=[CASE(>($2, 0), >(/(ABS(-($1, $2)), $2), 0.1), false)]) HiveProject((tok_table_or_col i_manufact_id)=[$0], (tok_function sum (tok_table_or_col ss_sales_price))=[$2], avg_window_0=[avg($2) OVER (PARTITION BY $0 ORDER BY $0 NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)]) HiveProject(i_manufact_id=[$0], d_qoy=[$1], $f2=[$2]) HiveAggregate(group=[{4, 6}], agg#0=[sum($2)]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query54.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query54.q.out index 6af3162b28..f2fdc36d6a 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query54.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query54.q.out @@ -1,7 +1,7 @@ -Warning: Shuffle Join MERGEJOIN[269][tables = [$hdt$_0, $hdt$_1]] in Stage 'Reducer 2' is a cross product -Warning: Shuffle Join MERGEJOIN[278][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5]] in Stage 'Reducer 6' is a cross product -Warning: Shuffle Join MERGEJOIN[277][tables = [$hdt$_1, $hdt$_2]] in Stage 'Reducer 15' is a cross product -Warning: Shuffle Join MERGEJOIN[279][tables = [$hdt$_1, $hdt$_2, $hdt$_0]] in Stage 'Reducer 7' is a cross product +Warning: Shuffle Join MERGEJOIN[268][tables = [$hdt$_2, $hdt$_3]] in Stage 'Reducer 3' is a cross product +Warning: Shuffle Join MERGEJOIN[269][tables = [$hdt$_2, $hdt$_3, $hdt$_1]] in Stage 'Reducer 4' is a cross product +Warning: Shuffle Join MERGEJOIN[277][tables = [$hdt$_1, $hdt$_2]] in Stage 'Reducer 14' is a cross product +Warning: Shuffle Join MERGEJOIN[278][tables = [$hdt$_1, $hdt$_2, $hdt$_0]] in Stage 'Reducer 8' is a cross product PREHOOK: query: explain cbo with my_customers as ( select distinct c_customer_sk @@ -134,20 +134,27 @@ CBO PLAN: HiveSortLimit(sort0=[$0], sort1=[$1], dir0=[ASC], dir1=[ASC], fetch=[100]) HiveProject(segment=[$0], num_customers=[$1], segment_base=[*($0, 50)]) HiveAggregate(group=[{0}], agg#0=[count()]) - HiveProject(segment=[CAST(/($1, CAST(50):DECIMAL(10, 0))):INTEGER]) + HiveProject($f0=[CAST(/($1, CAST(50):DECIMAL(10, 0))):INTEGER]) HiveAggregate(group=[{0}], agg#0=[sum($1)]) HiveFilter(condition=[BETWEEN(false, $2, $3, $4)]) HiveProject(c_customer_sk=[$0], ss_ext_sales_price=[$4], d_month_seq=[$11], _o__c0=[$13], $f0=[$14]) HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$4], $f1=[$5], ss_sold_date_sk=[$0], ss_customer_sk=[$1], ss_ext_sales_price=[$2], ca_address_sk=[$8], ca_county=[$9], ca_state=[$10], s_county=[$11], s_state=[$12], d_date_sk=[$6], d_month_seq=[$7], cnt=[$3], $f00=[$13]) - HiveJoin(condition=[true], joinType=[left], algorithm=[none], cost=[not available]) - HiveJoin(condition=[=($5, $8)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveJoin(condition=[=($0, $6)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveJoin(condition=[=($4, $1)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(ss_sold_date_sk=[$0], ss_customer_sk=[$3], ss_ext_sales_price=[$15]) - HiveFilter(condition=[AND(IS NOT NULL($3), IS NOT NULL($0))]) - HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) + HiveProject($f0=[$7], $f1=[$8], ss_sold_date_sk=[$0], ss_customer_sk=[$1], ss_ext_sales_price=[$2], ca_address_sk=[$9], ca_county=[$10], ca_state=[$11], s_county=[$12], s_state=[$13], d_date_sk=[$3], d_month_seq=[$4], cnt=[$6], $f00=[$5]) + HiveJoin(condition=[=($8, $9)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[=($7, $1)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(ss_sold_date_sk=[$0], ss_customer_sk=[$3], ss_ext_sales_price=[$15]) + HiveFilter(condition=[AND(IS NOT NULL($3), IS NOT NULL($0))]) + HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) + HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(d_date_sk=[$0], d_month_seq=[$3]) + HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) + HiveJoin(condition=[true], joinType=[right], algorithm=[none], cost=[not available]) + HiveProject($f0=[$0]) + HiveAggregate(group=[{0}]) + HiveProject($f0=[+($3, 1)]) + HiveFilter(condition=[AND(=($6, 1999), =($8, 3))]) + HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(cnt=[$0]) HiveFilter(condition=[<=(sq_count_check($0), 1)]) HiveProject(cnt=[$0]) @@ -157,43 +164,36 @@ HiveSortLimit(sort0=[$0], sort1=[$1], dir0=[ASC], dir1=[ASC], fetch=[100]) HiveProject($f0=[+($3, 1)]) HiveFilter(condition=[AND(=($6, 1999), =($8, 3))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject(c_customer_sk=[$0], c_current_addr_sk=[$1]) - HiveAggregate(group=[{0, 1}]) + HiveProject(c_customer_sk=[$0], c_current_addr_sk=[$1]) + HiveAggregate(group=[{0, 1}]) + HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(c_customer_sk=[$0], c_current_addr_sk=[$4]) + HiveFilter(condition=[IS NOT NULL($4)]) + HiveTableScan(table=[[default, customer]], table:alias=[customer]) + HiveJoin(condition=[=($2, $4)], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(c_customer_sk=[$0], c_current_addr_sk=[$4]) - HiveFilter(condition=[IS NOT NULL($4)]) - HiveTableScan(table=[[default, customer]], table:alias=[customer]) - HiveJoin(condition=[=($2, $4)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(cs_sold_date_sk=[$0], cs_bill_customer_sk=[$1], cs_item_sk=[$2]) - HiveUnion(all=[true]) - HiveProject(cs_sold_date_sk=[$0], cs_bill_customer_sk=[$3], cs_item_sk=[$15]) - HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($3))]) - HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales]) - HiveProject(sold_date_sk=[$0], customer_sk=[$4], item_sk=[$3]) - HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($4))]) - HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales]) - HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[AND(=($8, 3), =($6, 1999))]) - HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject(i_item_sk=[$0]) - HiveFilter(condition=[AND(=($12, _UTF-16LE'Jewelry'), =($10, _UTF-16LE'consignment'))]) - HiveTableScan(table=[[default, item]], table:alias=[item]) - HiveProject(d_date_sk=[$0], d_month_seq=[$3]) - HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject(ca_address_sk=[$0], ca_county=[$1], ca_state=[$2], s_county=[$3], s_state=[$4]) - HiveJoin(condition=[AND(=($1, $3), =($2, $4))], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(ca_address_sk=[$0], ca_county=[$7], ca_state=[$8]) - HiveFilter(condition=[AND(IS NOT NULL($7), IS NOT NULL($8))]) - HiveTableScan(table=[[default, customer_address]], table:alias=[customer_address]) - HiveProject(s_county=[$23], s_state=[$24]) - HiveFilter(condition=[AND(IS NOT NULL($23), IS NOT NULL($24))]) - HiveTableScan(table=[[default, store]], table:alias=[store]) - HiveProject($f0=[$0]) - HiveAggregate(group=[{0}]) - HiveProject($f0=[+($3, 1)]) - HiveFilter(condition=[AND(=($6, 1999), =($8, 3))]) - HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) + HiveProject(cs_sold_date_sk=[$0], cs_bill_customer_sk=[$1], cs_item_sk=[$2]) + HiveUnion(all=[true]) + HiveProject(cs_sold_date_sk=[$0], cs_bill_customer_sk=[$3], cs_item_sk=[$15]) + HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($3))]) + HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales]) + HiveProject(sold_date_sk=[$0], customer_sk=[$4], item_sk=[$3]) + HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($4))]) + HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales]) + HiveProject(d_date_sk=[$0]) + HiveFilter(condition=[AND(=($8, 3), =($6, 1999))]) + HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) + HiveProject(i_item_sk=[$0]) + HiveFilter(condition=[AND(=($12, _UTF-16LE'Jewelry'), =($10, _UTF-16LE'consignment'))]) + HiveTableScan(table=[[default, item]], table:alias=[item]) + HiveProject(ca_address_sk=[$0], ca_county=[$1], ca_state=[$2], s_county=[$3], s_state=[$4]) + HiveJoin(condition=[AND(=($1, $3), =($2, $4))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(ca_address_sk=[$0], ca_county=[$7], ca_state=[$8]) + HiveFilter(condition=[AND(IS NOT NULL($7), IS NOT NULL($8))]) + HiveTableScan(table=[[default, customer_address]], table:alias=[customer_address]) + HiveProject(s_county=[$23], s_state=[$24]) + HiveFilter(condition=[AND(IS NOT NULL($23), IS NOT NULL($24))]) + HiveTableScan(table=[[default, store]], table:alias=[store]) HiveJoin(condition=[true], joinType=[right], algorithm=[none], cost=[not available]) HiveProject($f0=[$0]) HiveAggregate(group=[{0}]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query6.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query6.q.out index 5e3deb3eb9..d34b7ab6b8 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query6.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query6.q.out @@ -1,4 +1,4 @@ -Warning: Map Join MAPJOIN[170][bigTable=?] in task 'Map 11' is a cross product +Warning: Map Join MAPJOIN[168][bigTable=?] in task 'Map 1' is a cross product PREHOOK: query: explain cbo select a.ca_state state, count(*) cnt from customer_address a @@ -65,43 +65,43 @@ CBO PLAN: HiveSortLimit(sort0=[$1], dir0=[ASC], fetch=[100]) HiveProject(ca_state=[$0], $f1=[$1]) HiveFilter(condition=[>=($1, 10)]) - HiveAggregate(group=[{10}], agg#0=[count()]) - HiveJoin(condition=[=($1, $11)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveJoin(condition=[=($6, $2)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_customer_sk=[$3]) - HiveFilter(condition=[AND(IS NOT NULL($3), IS NOT NULL($0))]) - HiveTableScan(table=[[default, store_sales]], table:alias=[s]) - HiveJoin(condition=[=($1, $2)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(d_date_sk=[$0], d_month_seq=[$3]) - HiveFilter(condition=[IS NOT NULL($3)]) - HiveTableScan(table=[[default, date_dim]], table:alias=[d]) - HiveProject(d_month_seq=[$0]) - HiveAggregate(group=[{3}]) - HiveFilter(condition=[AND(=($6, 2000), =($8, 2), IS NOT NULL($3))]) - HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject(c_customer_sk=[$0], c_current_addr_sk=[$1], cnt=[$2], ca_address_sk=[$3], ca_state=[$4]) - HiveJoin(condition=[=($3, $1)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(c_customer_sk=[$0], c_current_addr_sk=[$4]) - HiveFilter(condition=[IS NOT NULL($4)]) - HiveTableScan(table=[[default, customer]], table:alias=[c]) - HiveProject(cnt=[$0]) - HiveFilter(condition=[<=(sq_count_check($0), 1)]) - HiveProject(cnt=[$0]) - HiveAggregate(group=[{}], cnt=[COUNT()]) - HiveProject(d_month_seq=[$0]) - HiveAggregate(group=[{3}]) - HiveFilter(condition=[AND(=($6, 2000), =($8, 2))]) - HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject(ca_address_sk=[$0], ca_state=[$8]) - HiveTableScan(table=[[default, customer_address]], table:alias=[a]) + HiveAggregate(group=[{4}], agg#0=[count()]) + HiveJoin(condition=[=($6, $11)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[=($0, $7)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[=($3, $1)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[true], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(c_customer_sk=[$0], c_current_addr_sk=[$4]) + HiveFilter(condition=[IS NOT NULL($4)]) + HiveTableScan(table=[[default, customer]], table:alias=[c]) + HiveProject(cnt=[$0]) + HiveFilter(condition=[<=(sq_count_check($0), 1)]) + HiveProject(cnt=[$0]) + HiveAggregate(group=[{}], cnt=[COUNT()]) + HiveProject(d_month_seq=[$0]) + HiveAggregate(group=[{3}]) + HiveFilter(condition=[AND(=($6, 2000), =($8, 2))]) + HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) + HiveProject(ca_address_sk=[$0], ca_state=[$8]) + HiveTableScan(table=[[default, customer_address]], table:alias=[a]) + HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$1], ss_customer_sk=[$2], d_date_sk=[$3], d_month_seq=[$4], d_month_seq0=[$5]) + HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_customer_sk=[$3]) + HiveFilter(condition=[AND(IS NOT NULL($3), IS NOT NULL($0))]) + HiveTableScan(table=[[default, store_sales]], table:alias=[s]) + HiveJoin(condition=[=($1, $2)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(d_date_sk=[$0], d_month_seq=[$3]) + HiveFilter(condition=[IS NOT NULL($3)]) + HiveTableScan(table=[[default, date_dim]], table:alias=[d]) + HiveProject(d_month_seq=[$0]) + HiveAggregate(group=[{3}]) + HiveFilter(condition=[AND(=($6, 2000), =($8, 2), IS NOT NULL($3))]) + HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(i_item_sk=[$0], i_current_price=[$1], i_category=[$2], i_category0=[$3], *=[$4]) HiveJoin(condition=[AND(=($3, $2), >($1, $4))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(i_item_sk=[$0], i_current_price=[$5], i_category=[$12]) HiveFilter(condition=[IS NOT NULL($12)]) HiveTableScan(table=[[default, item]], table:alias=[i]) - HiveProject(i_category=[$0], *=[*(1.2, CAST(/($1, $2)):DECIMAL(16, 6))]) + HiveProject(i_category=[$0], *=[*(1.2, CASE(false, null, /($1, $2)))]) HiveAggregate(group=[{12}], agg#0=[sum($5)], agg#1=[count($5)]) HiveFilter(condition=[IS NOT NULL($12)]) HiveTableScan(table=[[default, item]], table:alias=[j]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query63.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query63.q.out index e22d812f78..c820e7f207 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query63.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query63.q.out @@ -67,7 +67,7 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], sort1=[$2], sort2=[$1], dir0=[ASC], dir1=[ASC], dir2=[ASC], fetch=[100]) HiveProject((tok_table_or_col i_manager_id)=[$0], (tok_function sum (tok_table_or_col ss_sales_price))=[$1], avg_window_0=[$2]) - HiveFilter(condition=[CASE(>($2, 0), >(/(ABS(-($1, $2)), $2), 0.1), null)]) + HiveFilter(condition=[CASE(>($2, 0), >(/(ABS(-($1, $2)), $2), 0.1), false)]) HiveProject((tok_table_or_col i_manager_id)=[$0], (tok_function sum (tok_table_or_col ss_sales_price))=[$2], avg_window_0=[avg($2) OVER (PARTITION BY $0 ORDER BY $0 NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)]) HiveProject(i_manager_id=[$0], d_moy=[$1], $f2=[$2]) HiveAggregate(group=[{4, 6}], agg#0=[sum($2)]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query64.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query64.q.out index 4261d0655d..563fbfc1f6 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query64.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query64.q.out @@ -292,13 +292,13 @@ HiveProject(product_name=[$0], store_name=[$1], store_zip=[$2], b_street_number= HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($7), IS NOT NULL($3), IS NOT NULL($4), IS NOT NULL($8), IS NOT NULL($5), IS NOT NULL($6))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(i_item_sk=[$0], i_product_name=[$21]) - HiveFilter(condition=[AND(IN($17, _UTF-16LE'maroon', _UTF-16LE'burnished', _UTF-16LE'dim', _UTF-16LE'steel', _UTF-16LE'navajo', _UTF-16LE'chocolate'), BETWEEN(false, $5, 35, 45), BETWEEN(false, $5, 36, 50))]) + HiveFilter(condition=[AND(IN($17, _UTF-16LE'maroon', _UTF-16LE'burnished', _UTF-16LE'dim', _UTF-16LE'steel', _UTF-16LE'navajo', _UTF-16LE'chocolate'), BETWEEN(false, $5, CAST(35):DECIMAL(12, 2), 45), BETWEEN(false, $5, 36, 50))]) HiveTableScan(table=[[default, item]], table:alias=[item]) HiveProject(d_date_sk=[$0]) HiveFilter(condition=[=($6, 2000)]) HiveTableScan(table=[[default, date_dim]], table:alias=[d1]) HiveProject(cs_item_sk=[$0]) - HiveFilter(condition=[>($1, *(2, $2))]) + HiveFilter(condition=[>($1, *(CAST(2):DECIMAL(10, 0), $2))]) HiveAggregate(group=[{0}], agg#0=[sum($2)], agg#1=[sum($5)]) HiveJoin(condition=[AND(=($0, $3), =($1, $4))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(cs_item_sk=[$15], cs_order_number=[$17], cs_ext_list_price=[$25]) @@ -351,13 +351,13 @@ HiveProject(product_name=[$0], store_name=[$1], store_zip=[$2], b_street_number= HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($7), IS NOT NULL($3), IS NOT NULL($4), IS NOT NULL($8), IS NOT NULL($5), IS NOT NULL($6))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(i_item_sk=[$0], i_product_name=[$21]) - HiveFilter(condition=[AND(IN($17, _UTF-16LE'maroon', _UTF-16LE'burnished', _UTF-16LE'dim', _UTF-16LE'steel', _UTF-16LE'navajo', _UTF-16LE'chocolate'), BETWEEN(false, $5, 35, 45), BETWEEN(false, $5, 36, 50))]) + HiveFilter(condition=[AND(IN($17, _UTF-16LE'maroon', _UTF-16LE'burnished', _UTF-16LE'dim', _UTF-16LE'steel', _UTF-16LE'navajo', _UTF-16LE'chocolate'), BETWEEN(false, $5, CAST(35):DECIMAL(12, 2), 45), BETWEEN(false, $5, 36, 50))]) HiveTableScan(table=[[default, item]], table:alias=[item]) HiveProject(d_date_sk=[$0]) HiveFilter(condition=[=($6, 2001)]) HiveTableScan(table=[[default, date_dim]], table:alias=[d1]) HiveProject(cs_item_sk=[$0]) - HiveFilter(condition=[>($1, *(2, $2))]) + HiveFilter(condition=[>($1, *(CAST(2):DECIMAL(10, 0), $2))]) HiveAggregate(group=[{0}], agg#0=[sum($2)], agg#1=[sum($5)]) HiveJoin(condition=[AND(=($0, $3), =($1, $4))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(cs_item_sk=[$15], cs_order_number=[$17], cs_ext_list_price=[$25]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query65.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query65.q.out index 3e906b73b0..88b64f29d1 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query65.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query65.q.out @@ -66,10 +66,8 @@ POSTHOOK: Input: default@store_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], sort1=[$1], dir0=[ASC], dir1=[ASC], fetch=[100]) - HiveProject(s_store_name=[$11], i_item_desc=[$1], revenue=[$7], i_current_price=[$2], i_wholesale_cost=[$3], i_brand=[$4]) - HiveJoin(condition=[=($0, $6)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(i_item_sk=[$0], i_item_desc=[$4], i_current_price=[$5], i_wholesale_cost=[$6], i_brand=[$8]) - HiveTableScan(table=[[default, item]], table:alias=[item]) + HiveProject(s_store_name=[$6], i_item_desc=[$8], revenue=[$2], i_current_price=[$9], i_wholesale_cost=[$10], i_brand=[$11]) + HiveJoin(condition=[=($7, $1)], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[=($5, $0)], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[AND(=($3, $0), <=($2, $4))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(ss_store_sk=[$1], ss_item_sk=[$0], $f2=[$2]) @@ -94,4 +92,6 @@ HiveSortLimit(sort0=[$0], sort1=[$1], dir0=[ASC], dir1=[ASC], fetch=[100]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(s_store_sk=[$0], s_store_name=[$5]) HiveTableScan(table=[[default, store]], table:alias=[store]) + HiveProject(i_item_sk=[$0], i_item_desc=[$4], i_current_price=[$5], i_wholesale_cost=[$6], i_brand=[$8]) + HiveTableScan(table=[[default, item]], table:alias=[item]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query68.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query68.q.out index 1b25235c8a..e5c182273b 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query68.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query68.q.out @@ -96,32 +96,32 @@ POSTHOOK: Input: default@store_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], sort1=[$4], dir0=[ASC], dir1=[ASC], fetch=[100]) - HiveProject(c_last_name=[$5], c_first_name=[$4], ca_city=[$1], bought_city=[$8], ss_ticket_number=[$6], extended_price=[$9], extended_tax=[$11], list_price=[$10]) - HiveJoin(condition=[AND(=($3, $0), <>($1, $8))], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(ca_address_sk=[$0], ca_city=[$6]) - HiveTableScan(table=[[default, customer_address]], table:alias=[current_addr]) - HiveJoin(condition=[=($5, $0)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(c_last_name=[$3], c_first_name=[$2], ca_city=[$5], bought_city=[$8], ss_ticket_number=[$6], extended_price=[$9], extended_tax=[$11], list_price=[$10]) + HiveJoin(condition=[AND(<>($5, $8), =($7, $0))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[=($1, $4)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], c_current_addr_sk=[$4], c_first_name=[$8], c_last_name=[$9]) HiveFilter(condition=[IS NOT NULL($4)]) HiveTableScan(table=[[default, customer]], table:alias=[customer]) - HiveProject(ss_ticket_number=[$3], ss_customer_sk=[$1], bought_city=[$0], extended_price=[$4], list_price=[$5], extended_tax=[$6]) - HiveAggregate(group=[{1, 3, 5, 7}], agg#0=[sum($8)], agg#1=[sum($9)], agg#2=[sum($10)]) - HiveJoin(condition=[=($5, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(ca_address_sk=[$0], ca_city=[$6]) - HiveTableScan(table=[[default, customer_address]], table:alias=[customer_address]) - HiveJoin(condition=[=($2, $11)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveJoin(condition=[=($4, $10)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(ss_sold_date_sk=[$0], ss_customer_sk=[$3], ss_hdemo_sk=[$5], ss_addr_sk=[$6], ss_store_sk=[$7], ss_ticket_number=[$9], ss_ext_sales_price=[$15], ss_ext_list_price=[$17], ss_ext_tax=[$18]) - HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($7), IS NOT NULL($5), IS NOT NULL($6), IS NOT NULL($3))]) - HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[AND(IN($6, 1998, 1999, 2000), BETWEEN(false, $9, 1, 2))]) - HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject(s_store_sk=[$0]) - HiveFilter(condition=[IN($22, _UTF-16LE'Cedar Grove', _UTF-16LE'Wildwood')]) - HiveTableScan(table=[[default, store]], table:alias=[store]) - HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[OR(=($3, 2), =($4, 1))]) - HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) + HiveProject(ca_address_sk=[$0], ca_city=[$6]) + HiveTableScan(table=[[default, customer_address]], table:alias=[current_addr]) + HiveProject(ss_ticket_number=[$3], ss_customer_sk=[$1], bought_city=[$0], extended_price=[$4], list_price=[$5], extended_tax=[$6]) + HiveAggregate(group=[{1, 3, 5, 7}], agg#0=[sum($8)], agg#1=[sum($9)], agg#2=[sum($10)]) + HiveJoin(condition=[=($5, $0)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(ca_address_sk=[$0], ca_city=[$6]) + HiveTableScan(table=[[default, customer_address]], table:alias=[customer_address]) + HiveJoin(condition=[=($2, $11)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[=($4, $10)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[=($0, $9)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(ss_sold_date_sk=[$0], ss_customer_sk=[$3], ss_hdemo_sk=[$5], ss_addr_sk=[$6], ss_store_sk=[$7], ss_ticket_number=[$9], ss_ext_sales_price=[$15], ss_ext_list_price=[$17], ss_ext_tax=[$18]) + HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($7), IS NOT NULL($5), IS NOT NULL($6), IS NOT NULL($3))]) + HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) + HiveProject(d_date_sk=[$0]) + HiveFilter(condition=[AND(IN($6, 1998, 1999, 2000), BETWEEN(false, $9, 1, 2))]) + HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) + HiveProject(s_store_sk=[$0]) + HiveFilter(condition=[IN($22, _UTF-16LE'Cedar Grove', _UTF-16LE'Wildwood')]) + HiveTableScan(table=[[default, store]], table:alias=[store]) + HiveProject(hd_demo_sk=[$0]) + HiveFilter(condition=[OR(=($3, 2), =($4, 1))]) + HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query7.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query7.q.out index bdd86fcfb4..41809cf747 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query7.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query7.q.out @@ -52,7 +52,7 @@ POSTHOOK: Input: default@store_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) - HiveProject($f0=[$0], $f1=[/(CAST($1):DOUBLE, $2)], $f2=[/($3, $4)], $f3=[/($5, $6)], $f4=[/($7, $8)]) + HiveProject(i_item_id=[$0], agg1=[/(CAST($1):DOUBLE, $2)], agg2=[/($3, $4)], agg3=[/($5, $6)], agg4=[/($7, $8)]) HiveAggregate(group=[{1}], agg#0=[sum($6)], agg#1=[count($6)], agg#2=[sum($7)], agg#3=[count($7)], agg#4=[sum($9)], agg#5=[count($9)], agg#6=[sum($8)], agg#7=[count($8)]) HiveJoin(condition=[=($3, $0)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(i_item_sk=[$0], i_item_id=[$1]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query72.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query72.q.out index 206b0f1972..1bec46e549 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query72.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query72.q.out @@ -84,10 +84,10 @@ HiveSortLimit(sort0=[$5], sort1=[$0], sort2=[$1], sort3=[$2], dir0=[DESC-nulls-l HiveAggregate(group=[{0, 1, 2}], agg#0=[count($3)], agg#1=[count($4)], agg#2=[count()]) HiveProject($f0=[$15], $f1=[$13], $f2=[$19], $f3=[CASE(IS NULL($25), 1, 0)], $f4=[CASE(IS NOT NULL($25), 1, 0)]) HiveJoin(condition=[AND(=($26, $4), =($27, $6))], joinType=[left], algorithm=[none], cost=[not available]) - HiveProject(cs_sold_date_sk=[$4], cs_ship_date_sk=[$5], cs_bill_cdemo_sk=[$6], cs_bill_hdemo_sk=[$7], cs_item_sk=[$8], cs_promo_sk=[$9], cs_order_number=[$10], cs_quantity=[$11], inv_date_sk=[$0], inv_item_sk=[$1], inv_warehouse_sk=[$2], inv_quantity_on_hand=[$3], w_warehouse_sk=[$19], w_warehouse_name=[$20], i_item_sk=[$23], i_item_desc=[$24], cd_demo_sk=[$12], hd_demo_sk=[$13], d_date_sk=[$16], d_week_seq=[$17], +=[$18], d_date_sk0=[$14], d_week_seq0=[$15], d_date_sk1=[$21], CAST=[$22], p_promo_sk=[$25]) - HiveJoin(condition=[=($9, $25)], joinType=[left], algorithm=[none], cost=[not available]) - HiveJoin(condition=[=($23, $8)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveJoin(condition=[AND(=($5, $21), >($22, $18))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(cs_sold_date_sk=[$4], cs_ship_date_sk=[$5], cs_bill_cdemo_sk=[$6], cs_bill_hdemo_sk=[$7], cs_item_sk=[$8], cs_promo_sk=[$9], cs_order_number=[$10], cs_quantity=[$11], inv_date_sk=[$0], inv_item_sk=[$1], inv_warehouse_sk=[$2], inv_quantity_on_hand=[$3], w_warehouse_sk=[$19], w_warehouse_name=[$20], i_item_sk=[$24], i_item_desc=[$25], cd_demo_sk=[$12], hd_demo_sk=[$13], d_date_sk=[$16], d_week_seq=[$17], +=[$18], d_date_sk0=[$14], d_week_seq0=[$15], d_date_sk1=[$22], CAST=[$23], p_promo_sk=[$21]) + HiveJoin(condition=[=($24, $8)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[AND(=($5, $22), >($23, $18))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[=($9, $21)], joinType=[left], algorithm=[none], cost=[not available]) HiveJoin(condition=[=($19, $2)], joinType=[inner], algorithm=[none], cost=[not available]) HiveJoin(condition=[AND(AND(=($0, $14), =($8, $1)), <($3, $11))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(inv_date_sk=[$0], inv_item_sk=[$1], inv_warehouse_sk=[$2], inv_quantity_on_hand=[$3]) @@ -109,17 +109,17 @@ HiveSortLimit(sort0=[$5], sort1=[$0], sort2=[$1], sort3=[$2], dir0=[DESC-nulls-l HiveProject(d_date_sk=[$0], d_week_seq=[$4]) HiveFilter(condition=[IS NOT NULL($4)]) HiveTableScan(table=[[default, date_dim]], table:alias=[d2]) - HiveProject(d_date_sk=[$0], d_week_seq=[$4], +=[+(CAST($2):DOUBLE, 5)]) + HiveProject(d_date_sk=[$0], d_week_seq=[$4], +=[+(CAST($2):DOUBLE, CAST(5):DOUBLE)]) HiveFilter(condition=[AND(=($6, 2001), IS NOT NULL($4))]) HiveTableScan(table=[[default, date_dim]], table:alias=[d1]) HiveProject(w_warehouse_sk=[$0], w_warehouse_name=[$2]) HiveTableScan(table=[[default, warehouse]], table:alias=[warehouse]) - HiveProject(d_date_sk=[$0], CAST=[CAST($2):DOUBLE]) - HiveTableScan(table=[[default, date_dim]], table:alias=[d3]) - HiveProject(i_item_sk=[$0], i_item_desc=[$4]) - HiveTableScan(table=[[default, item]], table:alias=[item]) - HiveProject(p_promo_sk=[$0]) - HiveTableScan(table=[[default, promotion]], table:alias=[promotion]) + HiveProject(p_promo_sk=[$0]) + HiveTableScan(table=[[default, promotion]], table:alias=[promotion]) + HiveProject(d_date_sk=[$0], CAST=[CAST($2):DOUBLE]) + HiveTableScan(table=[[default, date_dim]], table:alias=[d3]) + HiveProject(i_item_sk=[$0], i_item_desc=[$4]) + HiveTableScan(table=[[default, item]], table:alias=[item]) HiveProject(cr_item_sk=[$2], cr_order_number=[$16]) HiveTableScan(table=[[default, catalog_returns]], table:alias=[catalog_returns]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query73.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query73.q.out index 38af7c0d35..23f4052ed8 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query73.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query73.q.out @@ -71,7 +71,7 @@ HiveSortLimit(sort0=[$5], dir0=[DESC-nulls-last]) HiveProject(c_customer_sk=[$0], c_salutation=[$7], c_first_name=[$8], c_last_name=[$9], c_preferred_cust_flag=[$10]) HiveTableScan(table=[[default, customer]], table:alias=[customer]) HiveProject(ss_ticket_number=[$0], ss_customer_sk=[$1], $f2=[$2]) - HiveFilter(condition=[BETWEEN(false, $2, 1, 5)]) + HiveFilter(condition=[BETWEEN(false, $2, CAST(1):BIGINT, CAST(5):BIGINT)]) HiveProject(ss_ticket_number=[$1], ss_customer_sk=[$0], $f2=[$2]) HiveAggregate(group=[{1, 4}], agg#0=[count()]) HiveJoin(condition=[=($3, $7)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query74.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query74.q.out index 4a8f0b88f0..20197e1850 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query74.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query74.q.out @@ -131,7 +131,7 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$1], sort1=[$0], sort2=[$2], dir0=[ASC], dir1=[ASC], dir2=[ASC], fetch=[100]) HiveProject(customer_id=[$0], customer_first_name=[$1], customer_last_name=[$2]) - HiveJoin(condition=[AND(=($0, $9), CASE(CAST(IS NOT NULL($10)):BOOLEAN, CASE($8, >(/($5, $7), /($3, $10)), >(null, /($3, $10))), CASE($8, >(/($5, $7), null), null)))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[AND(=($0, $9), CASE(CAST(IS NOT NULL($10)):BOOLEAN, CASE($8, >(/($5, $7), /($3, $10)), null), null))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_id=[$0], c_first_name=[$1], c_last_name=[$2], $f3=[$3]) HiveAggregate(group=[{1, 2, 3}], agg#0=[max($6)]) HiveJoin(condition=[=($0, $5)], joinType=[inner], algorithm=[none], cost=[not available]) @@ -145,7 +145,7 @@ HiveSortLimit(sort0=[$1], sort1=[$0], sort2=[$2], dir0=[ASC], dir1=[ASC], dir2=[ HiveFilter(condition=[AND(IN($6, 2001, 2002), =($6, 2002))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveJoin(condition=[=($5, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject($f0=[$0], $f4=[$3]) + HiveProject(customer_id=[$0], year_total=[$3]) HiveAggregate(group=[{1, 2, 3}], agg#0=[max($6)]) HiveJoin(condition=[=($0, $5)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(c_customer_sk=[$0], c_customer_id=[$1], c_first_name=[$8], c_last_name=[$9]) @@ -171,7 +171,7 @@ HiveSortLimit(sort0=[$1], sort1=[$0], sort2=[$2], dir0=[ASC], dir1=[ASC], dir2=[ HiveProject(d_date_sk=[$0]) HiveFilter(condition=[AND(IN($6, 2001, 2002), =($6, 2001))]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject($f0=[$0], $f4=[$3]) + HiveProject(customer_id=[$0], year_total=[$3]) HiveFilter(condition=[>($3, 0)]) HiveAggregate(group=[{1, 2, 3}], agg#0=[max($6)]) HiveJoin(condition=[=($0, $5)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query78.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query78.q.out index de1b133006..3d57cd156d 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query78.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query78.q.out @@ -129,55 +129,54 @@ POSTHOOK: Input: default@web_returns POSTHOOK: Input: default@web_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: -HiveSortLimit(fetch=[100]) - HiveProject(ss_sold_year=[CAST(2000):INTEGER], ss_item_sk=[$0], ss_customer_sk=[$1], ratio=[$2], store_qty=[$3], store_wholesale_cost=[$4], store_sales_price=[$5], other_chan_qty=[$6], other_chan_wholesale_cost=[$7], other_chan_sales_price=[$8]) - HiveSortLimit(sort0=[$0], sort1=[$1], sort2=[$9], sort3=[$10], sort4=[$11], sort5=[$6], sort6=[$7], sort7=[$8], sort8=[$12], dir0=[ASC], dir1=[ASC], dir2=[DESC-nulls-last], dir3=[DESC-nulls-last], dir4=[DESC-nulls-last], dir5=[ASC], dir6=[ASC], dir7=[ASC], dir8=[ASC]) - HiveProject(ss_item_sk=[$0], ss_customer_sk=[$1], ratio=[round(/(CAST($2):DOUBLE, CAST(CASE(AND(IS NOT NULL($7), IS NOT NULL($11)), +($7, $11), 1)):DOUBLE), 2)], store_qty=[$2], store_wholesale_cost=[$3], store_sales_price=[$4], other_chan_qty=[+(CASE(IS NOT NULL($7), $7, 0), CASE(IS NOT NULL($11), $11, 0))], other_chan_wholesale_cost=[+(CASE(IS NOT NULL($8), $8, 0), CASE(IS NOT NULL($12), $12, 0))], other_chan_sales_price=[+(CASE(IS NOT NULL($9), $9, 0), CASE(IS NOT NULL($13), $13, 0))], ss_qty=[$2], ss_wc=[$3], ss_sp=[$4], (tok_function round (/ (tok_table_or_col ss_qty) (tok_function coalesce (+ (tok_table_or_col ws_qty) (tok_table_or_col cs_qty)) 1)) 2)=[round(/(CAST($2):DOUBLE, CAST(CASE(AND(IS NOT NULL($7), IS NOT NULL($11)), +($7, $11), 1)):DOUBLE), 2)]) - HiveFilter(condition=[CASE(IS NOT NULL($11), >($11, 0), false)]) - HiveJoin(condition=[=($10, $1)], joinType=[left], algorithm=[none], cost=[not available]) - HiveProject(ss_item_sk=[$0], ss_customer_sk=[$1], $f2=[$2], $f3=[$3], $f4=[$4], ws_item_sk=[$5], ws_bill_customer_sk=[$6], $f20=[$7], $f30=[$8], $f40=[$9]) - HiveFilter(condition=[CASE(IS NOT NULL($7), >($7, 0), false)]) - HiveJoin(condition=[AND(=($5, $0), =($6, $1))], joinType=[left], algorithm=[none], cost=[not available]) - HiveProject(ss_item_sk=[$0], ss_customer_sk=[$1], $f2=[$2], $f3=[$3], $f4=[$4]) - HiveAggregate(group=[{2, 3}], agg#0=[sum($4)], agg#1=[sum($5)], agg#2=[sum($6)]) - HiveJoin(condition=[=($1, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[=($6, 2000)]) - HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$1], ss_customer_sk=[$2], ss_quantity=[$4], ss_wholesale_cost=[$5], ss_sales_price=[$6]) - HiveFilter(condition=[IS NULL($8)]) - HiveJoin(condition=[AND(=($8, $3), =($1, $7))], joinType=[left], algorithm=[none], cost=[not available]) - HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_customer_sk=[$3], ss_ticket_number=[$9], ss_quantity=[$10], ss_wholesale_cost=[$11], ss_sales_price=[$13]) - HiveFilter(condition=[IS NOT NULL($0)]) - HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject(sr_item_sk=[$2], sr_ticket_number=[$9]) - HiveTableScan(table=[[default, store_returns]], table:alias=[store_returns]) - HiveProject(ws_item_sk=[$0], ws_bill_customer_sk=[$1], $f2=[$2], $f3=[$3], $f4=[$4]) - HiveAggregate(group=[{2, 3}], agg#0=[sum($4)], agg#1=[sum($5)], agg#2=[sum($6)]) - HiveJoin(condition=[=($1, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[=($6, 2000)]) - HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$1], ws_bill_customer_sk=[$2], ws_quantity=[$4], ws_wholesale_cost=[$5], ws_sales_price=[$6]) - HiveFilter(condition=[IS NULL($8)]) - HiveJoin(condition=[AND(=($8, $3), =($1, $7))], joinType=[left], algorithm=[none], cost=[not available]) - HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$3], ws_bill_customer_sk=[$4], ws_order_number=[$17], ws_quantity=[$18], ws_wholesale_cost=[$19], ws_sales_price=[$21]) - HiveFilter(condition=[IS NOT NULL($0)]) - HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales]) - HiveProject(wr_item_sk=[$2], wr_order_number=[$13]) - HiveTableScan(table=[[default, web_returns]], table:alias=[web_returns]) - HiveProject($f2=[$0], $f3=[$2], $f4=[$3], $f5=[$4]) - HiveAggregate(group=[{2, 3}], agg#0=[sum($4)], agg#1=[sum($5)], agg#2=[sum($6)]) - HiveJoin(condition=[=($1, $0)], joinType=[inner], algorithm=[none], cost=[not available]) - HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[=($6, 2000)]) - HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) - HiveProject(cs_sold_date_sk=[$0], cs_bill_customer_sk=[$1], cs_item_sk=[$2], cs_quantity=[$4], cs_wholesale_cost=[$5], cs_sales_price=[$6]) - HiveFilter(condition=[IS NULL($8)]) - HiveJoin(condition=[AND(=($8, $3), =($2, $7))], joinType=[left], algorithm=[none], cost=[not available]) - HiveProject(cs_sold_date_sk=[$0], cs_bill_customer_sk=[$3], cs_item_sk=[$15], cs_order_number=[$17], cs_quantity=[$18], cs_wholesale_cost=[$19], cs_sales_price=[$21]) - HiveFilter(condition=[IS NOT NULL($0)]) - HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales]) - HiveProject(cr_item_sk=[$2], cr_order_number=[$16]) - HiveTableScan(table=[[default, catalog_returns]], table:alias=[catalog_returns]) +HiveProject(ss_sold_year=[CAST(2000):INTEGER], ss_item_sk=[$0], ss_customer_sk=[$1], ratio=[$2], store_qty=[$3], store_wholesale_cost=[$4], store_sales_price=[$5], other_chan_qty=[$6], other_chan_wholesale_cost=[$7], other_chan_sales_price=[$8]) + HiveSortLimit(sort0=[$0], sort1=[$1], sort2=[$9], sort3=[$10], sort4=[$11], sort5=[$6], sort6=[$7], sort7=[$8], sort8=[$12], dir0=[ASC], dir1=[ASC], dir2=[DESC-nulls-last], dir3=[DESC-nulls-last], dir4=[DESC-nulls-last], dir5=[ASC], dir6=[ASC], dir7=[ASC], dir8=[ASC], fetch=[100]) + HiveProject(ss_item_sk=[$0], ss_customer_sk=[$1], ratio=[round(/(CAST($2):DOUBLE, CAST(CASE(IS NOT NULL(+($11, $6)), +($11, $6), 1)):DOUBLE), 2)], store_qty=[$2], store_wholesale_cost=[$3], store_sales_price=[$4], other_chan_qty=[+(CASE(IS NOT NULL($11), $11, 0), CASE(IS NOT NULL($6), $6, 0))], other_chan_wholesale_cost=[+(CASE(IS NOT NULL($12), $12, 0), CASE(IS NOT NULL($7), $7, 0))], other_chan_sales_price=[+(CASE(IS NOT NULL($13), $13, 0), CASE(IS NOT NULL($8), $8, 0))], ss_qty=[$2], ss_wc=[$3], ss_sp=[$4], (tok_function round (/ (tok_table_or_col ss_qty) (tok_function coalesce (+ (tok_table_or_col ws_qty) (tok_table_or_col cs_qty)) 1)) 2)=[round(/(CAST($2):DOUBLE, CAST(CASE(IS NOT NULL(+($11, $6)), +($11, $6), 1)):DOUBLE), 2)]) + HiveJoin(condition=[AND(=($9, $0), =($10, $1))], joinType=[inner], algorithm=[none], cost=[not available]) + HiveJoin(condition=[=($5, $1)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(ss_item_sk=[$0], ss_customer_sk=[$1], $f2=[$2], $f3=[$3], $f4=[$4]) + HiveAggregate(group=[{2, 3}], agg#0=[sum($4)], agg#1=[sum($5)], agg#2=[sum($6)]) + HiveJoin(condition=[=($1, $0)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(d_date_sk=[$0]) + HiveFilter(condition=[=($6, 2000)]) + HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) + HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$1], ss_customer_sk=[$2], ss_quantity=[$4], ss_wholesale_cost=[$5], ss_sales_price=[$6]) + HiveFilter(condition=[IS NULL($8)]) + HiveJoin(condition=[AND(=($8, $3), =($1, $7))], joinType=[left], algorithm=[none], cost=[not available]) + HiveProject(ss_sold_date_sk=[$0], ss_item_sk=[$2], ss_customer_sk=[$3], ss_ticket_number=[$9], ss_quantity=[$10], ss_wholesale_cost=[$11], ss_sales_price=[$13]) + HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($3))]) + HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) + HiveProject(sr_item_sk=[$2], sr_ticket_number=[$9]) + HiveTableScan(table=[[default, store_returns]], table:alias=[store_returns]) + HiveProject($f2=[$1], $f3=[$2], $f4=[$3], $f5=[$4]) + HiveFilter(condition=[>($2, 0)]) + HiveProject(cs_item_sk=[$1], cs_bill_customer_sk=[$0], $f2=[$2], $f3=[$3], $f4=[$4]) + HiveAggregate(group=[{2, 3}], agg#0=[sum($4)], agg#1=[sum($5)], agg#2=[sum($6)]) + HiveJoin(condition=[=($1, $0)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(d_date_sk=[$0]) + HiveFilter(condition=[=($6, 2000)]) + HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) + HiveProject(cs_sold_date_sk=[$0], cs_bill_customer_sk=[$1], cs_item_sk=[$2], cs_quantity=[$4], cs_wholesale_cost=[$5], cs_sales_price=[$6]) + HiveFilter(condition=[IS NULL($8)]) + HiveJoin(condition=[AND(=($8, $3), =($2, $7))], joinType=[left], algorithm=[none], cost=[not available]) + HiveProject(cs_sold_date_sk=[$0], cs_bill_customer_sk=[$3], cs_item_sk=[$15], cs_order_number=[$17], cs_quantity=[$18], cs_wholesale_cost=[$19], cs_sales_price=[$21]) + HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($3))]) + HiveTableScan(table=[[default, catalog_sales]], table:alias=[catalog_sales]) + HiveProject(cr_item_sk=[$2], cr_order_number=[$16]) + HiveTableScan(table=[[default, catalog_returns]], table:alias=[catalog_returns]) + HiveProject(ws_item_sk=[$0], ws_bill_customer_sk=[$1], $f2=[$2], $f3=[$3], $f4=[$4]) + HiveFilter(condition=[>($2, 0)]) + HiveAggregate(group=[{2, 3}], agg#0=[sum($4)], agg#1=[sum($5)], agg#2=[sum($6)]) + HiveJoin(condition=[=($1, $0)], joinType=[inner], algorithm=[none], cost=[not available]) + HiveProject(d_date_sk=[$0]) + HiveFilter(condition=[=($6, 2000)]) + HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) + HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$1], ws_bill_customer_sk=[$2], ws_quantity=[$4], ws_wholesale_cost=[$5], ws_sales_price=[$6]) + HiveFilter(condition=[IS NULL($8)]) + HiveJoin(condition=[AND(=($8, $3), =($1, $7))], joinType=[left], algorithm=[none], cost=[not available]) + HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$3], ws_bill_customer_sk=[$4], ws_order_number=[$17], ws_quantity=[$18], ws_wholesale_cost=[$19], ws_sales_price=[$21]) + HiveFilter(condition=[AND(IS NOT NULL($0), IS NOT NULL($4))]) + HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales]) + HiveProject(wr_item_sk=[$2], wr_order_number=[$13]) + HiveTableScan(table=[[default, web_returns]], table:alias=[web_returns]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query8.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query8.q.out index fe14ea31ac..e804a21ad4 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query8.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query8.q.out @@ -241,16 +241,16 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(substr=[substr($0, 1, 2)]) HiveFilter(condition=[=($1, 2)]) HiveAggregate(group=[{0}], agg#0=[count($1)]) - HiveProject(ca_zip=[$0], $f1=[$1]) + HiveProject($f0=[$0], $f1=[$1]) HiveUnion(all=[true]) - HiveProject(ca_zip=[$0], $f1=[$1]) + HiveProject($f0=[$0], $f1=[$1]) HiveAggregate(group=[{0}], agg#0=[count()]) - HiveProject(ca_zip=[substr($9, 1, 5)]) + HiveProject($f0=[substr($9, 1, 5)]) HiveFilter(condition=[AND(IN(substr($9, 1, 5), _UTF-16LE'89436', _UTF-16LE'30868', _UTF-16LE'65085', _UTF-16LE'22977', _UTF-16LE'83927', _UTF-16LE'77557', _UTF-16LE'58429', _UTF-16LE'40697', _UTF-16LE'80614', _UTF-16LE'10502', _UTF-16LE'32779', _UTF-16LE'91137', _UTF-16LE'61265', _UTF-16LE'98294', _UTF-16LE'17921', _UTF-16LE'18427', _UTF-16LE'21203', _UTF-16LE'59362', _UTF-16LE'87291', _UTF-16LE'84093', _UTF-16LE'21505', _UTF-16LE'17184', _UTF-16LE'10866', _UTF-16LE'67898', _UTF-16LE'25797', _UTF-16LE'28055', _UTF-16LE'18377', _UTF-16LE'80332', _UTF-16LE'74535', _UTF-16LE'21757', _UTF-16LE'29742', _UTF-16LE'90885', _UTF-16LE'29898', _UTF-16LE'17819', _UTF-16LE'40811', _UTF-16LE'25990', _UTF-16LE'47513', _UTF-16LE'89531', _UTF-16LE'91068', _UTF-16LE'10391', _UTF-16LE'18846', _UTF-16LE'99223', _UTF-16LE'82637', _UTF-16LE'41368', _UTF-16LE'83658', _UTF-16LE'86199', _UTF-16LE'81625', _UTF-16LE'26696', _UTF-16LE'89338', _UTF-16LE'88425', _UTF-16LE'32200', _UTF-16LE'81427', _UTF-16LE'19053', _UTF-16LE'77471', _UTF-16LE'36610', _UTF-16LE'99823', _UTF-16LE'43276', _UTF-16LE'41249', _UTF-16LE'48584', _UTF-16LE'83550', _UTF-16LE'82276', _UTF-16LE'18842', _UTF-16LE'78890', _UTF-16LE'14090', _UTF-16LE'38123', _UTF-16LE'40936', _UTF-16LE'34425', _UTF-16LE'19850', _UTF-16LE'43286', _UTF-16LE'80072', _UTF-16LE'79188', _UTF-16LE'54191', _UTF-16LE'11395', _UTF-16LE'50497', _UTF-16LE'84861', _UTF-16LE'90733', _UTF-16LE'21068', _UTF-16LE'57666', _UTF-16LE'37119', _UTF-16LE'25004', _UTF-16LE'57835', _UTF-16LE'70067', _UTF-16LE'62878', _UTF-16LE'95806', _UTF-16LE'19303', _UTF-16LE'18840', _UTF-16LE'19124', _UTF-16LE'29785', _UTF-16LE'16737', _UTF-16LE'16022', _UTF-16LE'49613', _UTF-16LE'89977', _UTF-16LE'68310', _UTF-16LE'60069', _UTF-16LE'98360', _UTF-16LE'48649', _UTF-16LE'39050', _UTF-16LE'41793', _UTF-16LE'25002', _UTF-16LE'27413', _UTF-16LE'39736', _UTF-16LE'47208', _UTF-16LE'16515', _UTF-16LE'94808', _UTF-16LE'57648', _UTF-16LE'15009', _UTF-16LE'80015', _UTF-16LE'42961', _UTF-16LE'63982', _UTF-16LE'21744', _UTF-16LE'71853', _UTF-16LE'81087', _UTF-16LE'67468', _UTF-16LE'34175', _UTF-16LE'64008', _UTF-16LE'20261', _UTF-16LE'11201', _UTF-16LE'51799', _UTF-16LE'48043', _UTF-16LE'45645', _UTF-16LE'61163', _UTF-16LE'48375', _UTF-16LE'36447', _UTF-16LE'57042', _UTF-16LE'21218', _UTF-16LE'41100', _UTF-16LE'89951', _UTF-16LE'22745', _UTF-16LE'35851', _UTF-16LE'83326', _UTF-16LE'61125', _UTF-16LE'78298', _UTF-16LE'80752', _UTF-16LE'49858', _UTF-16LE'52940', _UTF-16LE'96976', _UTF-16LE'63792', _UTF-16LE'11376', _UTF-16LE'53582', _UTF-16LE'18717', _UTF-16LE'90226', _UTF-16LE'50530', _UTF-16LE'94203', _UTF-16LE'99447', _UTF-16LE'27670', _UTF-16LE'96577', _UTF-16LE'57856', _UTF-16LE'56372', _UTF-16LE'16165', _UTF-16LE'23427', _UTF-16LE'54561', _UTF-16LE'28806', _UTF-16LE'44439', _UTF-16LE'22926', _UTF-16LE'30123', _UTF-16LE'61451', _UTF-16LE'92397', _UTF-16LE'56979', _UTF-16LE'92309', _UTF-16LE'70873', _UTF-16LE'13355', _UTF-16LE'21801', _UTF-16LE'46346', _UTF-16LE'37562', _UTF-16LE'56458', _UTF-16LE'28286', _UTF-16LE'47306', _UTF-16LE'99555', _UTF-16LE'69399', _UTF-16LE'26234', _UTF-16LE'47546', _UTF-16LE'49661', _UTF-16LE'88601', _UTF-16LE'35943', _UTF-16LE'39936', _UTF-16LE'25632', _UTF-16LE'24611', _UTF-16LE'44166', _UTF-16LE'56648', _UTF-16LE'30379', _UTF-16LE'59785', _UTF-16LE'11110', _UTF-16LE'14329', _UTF-16LE'93815', _UTF-16LE'52226', _UTF-16LE'71381', _UTF-16LE'13842', _UTF-16LE'25612', _UTF-16LE'63294', _UTF-16LE'14664', _UTF-16LE'21077', _UTF-16LE'82626', _UTF-16LE'18799', _UTF-16LE'60915', _UTF-16LE'81020', _UTF-16LE'56447', _UTF-16LE'76619', _UTF-16LE'11433', _UTF-16LE'13414', _UTF-16LE'42548', _UTF-16LE'92713', _UTF-16LE'70467', _UTF-16LE'30884', _UTF-16LE'47484', _UTF-16LE'16072', _UTF-16LE'38936', _UTF-16LE'13036', _UTF-16LE'88376', _UTF-16LE'45539', _UTF-16LE'35901', _UTF-16LE'19506', _UTF-16LE'65690', _UTF-16LE'73957', _UTF-16LE'71850', _UTF-16LE'49231', _UTF-16LE'14276', _UTF-16LE'20005', _UTF-16LE'18384', _UTF-16LE'76615', _UTF-16LE'11635', _UTF-16LE'38177', _UTF-16LE'55607', _UTF-16LE'41369', _UTF-16LE'95447', _UTF-16LE'58581', _UTF-16LE'58149', _UTF-16LE'91946', _UTF-16LE'33790', _UTF-16LE'76232', _UTF-16LE'75692', _UTF-16LE'95464', _UTF-16LE'22246', _UTF-16LE'51061', _UTF-16LE'56692', _UTF-16LE'53121', _UTF-16LE'77209', _UTF-16LE'15482', _UTF-16LE'10688', _UTF-16LE'14868', _UTF-16LE'45907', _UTF-16LE'73520', _UTF-16LE'72666', _UTF-16LE'25734', _UTF-16LE'17959', _UTF-16LE'24677', _UTF-16LE'66446', _UTF-16LE'94627', _UTF-16LE'53535', _UTF-16LE'15560', _UTF-16LE'41967', _UTF-16LE'69297', _UTF-16LE'11929', _UTF-16LE'59403', _UTF-16LE'33283', _UTF-16LE'52232', _UTF-16LE'57350', _UTF-16LE'43933', _UTF-16LE'40921', _UTF-16LE'36635', _UTF-16LE'10827', _UTF-16LE'71286', _UTF-16LE'19736', _UTF-16LE'80619', _UTF-16LE'25251', _UTF-16LE'95042', _UTF-16LE'15526', _UTF-16LE'36496', _UTF-16LE'55854', _UTF-16LE'49124', _UTF-16LE'81980', _UTF-16LE'35375', _UTF-16LE'49157', _UTF-16LE'63512', _UTF-16LE'28944', _UTF-16LE'14946', _UTF-16LE'36503', _UTF-16LE'54010', _UTF-16LE'18767', _UTF-16LE'23969', _UTF-16LE'43905', _UTF-16LE'66979', _UTF-16LE'33113', _UTF-16LE'21286', _UTF-16LE'58471', _UTF-16LE'59080', _UTF-16LE'13395', _UTF-16LE'79144', _UTF-16LE'70373', _UTF-16LE'67031', _UTF-16LE'38360', _UTF-16LE'26705', _UTF-16LE'50906', _UTF-16LE'52406', _UTF-16LE'26066', _UTF-16LE'73146', _UTF-16LE'15884', _UTF-16LE'31897', _UTF-16LE'30045', _UTF-16LE'61068', _UTF-16LE'45550', _UTF-16LE'92454', _UTF-16LE'13376', _UTF-16LE'14354', _UTF-16LE'19770', _UTF-16LE'22928', _UTF-16LE'97790', _UTF-16LE'50723', _UTF-16LE'46081', _UTF-16LE'30202', _UTF-16LE'14410', _UTF-16LE'20223', _UTF-16LE'88500', _UTF-16LE'67298', _UTF-16LE'13261', _UTF-16LE'14172', _UTF-16LE'81410', _UTF-16LE'93578', _UTF-16LE'83583', _UTF-16LE'46047', _UTF-16LE'94167', _UTF-16LE'82564', _UTF-16LE'21156', _UTF-16LE'15799', _UTF-16LE'86709', _UTF-16LE'37931', _UTF-16LE'74703', _UTF-16LE'83103', _UTF-16LE'23054', _UTF-16LE'70470', _UTF-16LE'72008', _UTF-16LE'49247', _UTF-16LE'91911', _UTF-16LE'69998', _UTF-16LE'20961', _UTF-16LE'70070', _UTF-16LE'63197', _UTF-16LE'54853', _UTF-16LE'88191', _UTF-16LE'91830', _UTF-16LE'49521', _UTF-16LE'19454', _UTF-16LE'81450', _UTF-16LE'89091', _UTF-16LE'62378', _UTF-16LE'25683', _UTF-16LE'61869', _UTF-16LE'51744', _UTF-16LE'36580', _UTF-16LE'85778', _UTF-16LE'36871', _UTF-16LE'48121', _UTF-16LE'28810', _UTF-16LE'83712', _UTF-16LE'45486', _UTF-16LE'67393', _UTF-16LE'26935', _UTF-16LE'42393', _UTF-16LE'20132', _UTF-16LE'55349', _UTF-16LE'86057', _UTF-16LE'21309', _UTF-16LE'80218', _UTF-16LE'10094', _UTF-16LE'11357', _UTF-16LE'48819', _UTF-16LE'39734', _UTF-16LE'40758', _UTF-16LE'30432', _UTF-16LE'21204', _UTF-16LE'29467', _UTF-16LE'30214', _UTF-16LE'61024', _UTF-16LE'55307', _UTF-16LE'74621', _UTF-16LE'11622', _UTF-16LE'68908', _UTF-16LE'33032', _UTF-16LE'52868', _UTF-16LE'99194', _UTF-16LE'99900', _UTF-16LE'84936', _UTF-16LE'69036', _UTF-16LE'99149', _UTF-16LE'45013', _UTF-16LE'32895', _UTF-16LE'59004', _UTF-16LE'32322', _UTF-16LE'14933', _UTF-16LE'32936', _UTF-16LE'33562', _UTF-16LE'72550', _UTF-16LE'27385', _UTF-16LE'58049', _UTF-16LE'58200', _UTF-16LE'16808', _UTF-16LE'21360', _UTF-16LE'32961', _UTF-16LE'18586', _UTF-16LE'79307', _UTF-16LE'15492'), IS NOT NULL(substr(substr($9, 1, 5), 1, 2)))]) HiveTableScan(table=[[default, customer_address]], table:alias=[customer_address]) - HiveProject(ca_zip=[$0], $f1=[$1]) + HiveProject($f0=[$0], $f1=[$1]) HiveAggregate(group=[{0}], agg#0=[count()]) - HiveProject(ca_zip=[substr($0, 1, 5)]) + HiveProject($f0=[substr($0, 1, 5)]) HiveFilter(condition=[>($1, 10)]) HiveAggregate(group=[{1}], agg#0=[count()]) HiveJoin(condition=[=($0, $2)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query82.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query82.q.out index 54c4a99b68..d338dd70a4 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query82.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query82.q.out @@ -49,7 +49,7 @@ HiveSortLimit(sort0=[$0], dir0=[ASC], fetch=[100]) HiveProject(ss_item_sk=[$2]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(i_item_sk=[$0], i_item_id=[$1], i_item_desc=[$4], i_current_price=[$5]) - HiveFilter(condition=[AND(IN($13, 437, 129, 727, 663), BETWEEN(false, $5, 30, 60))]) + HiveFilter(condition=[AND(IN($13, 437, 129, 727, 663), BETWEEN(false, $5, CAST(30):DECIMAL(12, 2), 60))]) HiveTableScan(table=[[default, item]], table:alias=[item]) HiveProject(inv_date_sk=[$0], inv_item_sk=[$1], d_date_sk=[$2]) HiveJoin(condition=[=($2, $0)], joinType=[inner], algorithm=[none], cost=[not available]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query85.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query85.q.out index 6471345141..8f5af1d114 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query85.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query85.q.out @@ -208,7 +208,7 @@ HiveProject(_o__c0=[$0], _o__c1=[$1], _o__c2=[$2], _o__c3=[$3]) HiveProject(wr_item_sk=[$2], wr_refunded_cdemo_sk=[$4], wr_refunded_addr_sk=[$6], wr_returning_cdemo_sk=[$8], wr_reason_sk=[$12], wr_order_number=[$13], wr_fee=[$18], wr_refunded_cash=[$20]) HiveFilter(condition=[AND(IS NOT NULL($4), IS NOT NULL($8), IS NOT NULL($6), IS NOT NULL($12))]) HiveTableScan(table=[[default, web_returns]], table:alias=[web_returns]) - HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$3], ws_order_number=[$17], ws_quantity=[$18], BETWEEN=[BETWEEN(false, $33, 100, 200)], BETWEEN6=[BETWEEN(false, $33, 150, 300)], BETWEEN7=[BETWEEN(false, $33, 50, 250)], BETWEEN8=[BETWEEN(false, $21, 100, 150)], BETWEEN9=[BETWEEN(false, $21, 50, 100)], BETWEEN10=[BETWEEN(false, $21, 150, 200)]) - HiveFilter(condition=[AND(OR(BETWEEN(false, $21, 100, 150), BETWEEN(false, $21, 50, 100), BETWEEN(false, $21, 150, 200)), OR(BETWEEN(false, $33, 100, 200), BETWEEN(false, $33, 150, 300), BETWEEN(false, $33, 50, 250)), IS NOT NULL($12), IS NOT NULL($0))]) + HiveProject(ws_sold_date_sk=[$0], ws_item_sk=[$3], ws_order_number=[$17], ws_quantity=[$18], BETWEEN=[BETWEEN(false, $33, CAST(100):DECIMAL(12, 2), CAST(200):DECIMAL(12, 2))], BETWEEN6=[BETWEEN(false, $33, CAST(150):DECIMAL(12, 2), CAST(300):DECIMAL(12, 2))], BETWEEN7=[BETWEEN(false, $33, CAST(50):DECIMAL(12, 2), CAST(250):DECIMAL(12, 2))], BETWEEN8=[BETWEEN(false, $21, 100, 150)], BETWEEN9=[BETWEEN(false, $21, 50, 100)], BETWEEN10=[BETWEEN(false, $21, 150, 200)]) + HiveFilter(condition=[AND(OR(BETWEEN(false, $21, 100, 150), BETWEEN(false, $21, 50, 100), BETWEEN(false, $21, 150, 200)), OR(BETWEEN(false, $33, CAST(100):DECIMAL(12, 2), CAST(200):DECIMAL(12, 2)), BETWEEN(false, $33, CAST(150):DECIMAL(12, 2), CAST(300):DECIMAL(12, 2)), BETWEEN(false, $33, CAST(50):DECIMAL(12, 2), CAST(250):DECIMAL(12, 2))), IS NOT NULL($12), IS NOT NULL($0))]) HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query88.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query88.q.out index 1ac8fe2dcd..421d3c2d0f 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query88.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query88.q.out @@ -217,7 +217,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 8), >=($4, 30))]) @@ -234,7 +234,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 12), <($4, 30))]) @@ -251,7 +251,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 11), >=($4, 30))]) @@ -268,7 +268,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 11), <($4, 30))]) @@ -285,7 +285,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 10), >=($4, 30))]) @@ -302,7 +302,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 10), <($4, 30))]) @@ -319,7 +319,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 9), >=($4, 30))]) @@ -336,7 +336,7 @@ HiveProject($f0=[$0], $f00=[$7], $f01=[$6], $f02=[$5], $f03=[$4], $f04=[$3], $f0 HiveFilter(condition=[AND(IS NOT NULL($5), IS NOT NULL($1), IS NOT NULL($7))]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) HiveProject(hd_demo_sk=[$0]) - HiveFilter(condition=[AND(IN($3, 3, 0, 1), <=($4, 5), OR(AND(=($3, 3), IS NOT NULL($4)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) + HiveFilter(condition=[AND(IN($3, 3, 0, 1), OR(<=($4, 5), <=($4, 2), <=($4, 3)), OR(AND(=($3, 3), <=($4, 5)), AND(=($3, 0), <=($4, 2)), AND(=($3, 1), <=($4, 3))))]) HiveTableScan(table=[[default, household_demographics]], table:alias=[household_demographics]) HiveProject(t_time_sk=[$0]) HiveFilter(condition=[AND(=($3, 9), <($4, 30))]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query89.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query89.q.out index d9c7d42b9f..68de432130 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query89.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query89.q.out @@ -66,7 +66,7 @@ CBO PLAN: HiveProject(i_category=[$0], i_class=[$1], i_brand=[$2], s_store_name=[$3], s_company_name=[$4], d_moy=[$5], sum_sales=[$6], avg_monthly_sales=[$7]) HiveSortLimit(sort0=[$8], sort1=[$3], dir0=[ASC], dir1=[ASC], fetch=[100]) HiveProject(i_category=[$0], i_class=[$1], i_brand=[$2], s_store_name=[$3], s_company_name=[$4], d_moy=[$5], sum_sales=[$6], avg_monthly_sales=[$7], (- (tok_table_or_col sum_sales) (tok_table_or_col avg_monthly_sales))=[-($6, $7)]) - HiveFilter(condition=[CASE(<>($7, 0), >(/(ABS(-($6, $7)), $7), 0.1), null)]) + HiveFilter(condition=[CASE(<>($7, 0), >(/(ABS(-($6, $7)), $7), 0.1), false)]) HiveProject((tok_table_or_col i_category)=[$2], (tok_table_or_col i_class)=[$1], (tok_table_or_col i_brand)=[$0], (tok_table_or_col s_store_name)=[$4], (tok_table_or_col s_company_name)=[$5], (tok_table_or_col d_moy)=[$3], (tok_function sum (tok_table_or_col ss_sales_price))=[$6], avg_window_0=[avg($6) OVER (PARTITION BY $2, $0, $4, $5 ORDER BY $2 NULLS FIRST, $0 NULLS FIRST, $4 NULLS FIRST, $5 NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)]) HiveProject(i_brand=[$0], i_class=[$1], i_category=[$2], d_moy=[$3], s_store_name=[$4], s_company_name=[$5], $f6=[$6]) HiveAggregate(group=[{5, 6, 7, 9, 11, 12}], agg#0=[sum($3)]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query9.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query9.q.out index 4a92def905..a1277470ba 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query9.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query9.q.out @@ -141,11 +141,11 @@ HiveProject(bucket1=[CASE($1, $2, $3)], bucket2=[CASE($4, $5, $6)], bucket3=[CAS HiveAggregate(group=[{}], agg#0=[count()]) HiveFilter(condition=[BETWEEN(false, $10, 1, 20)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($17)], agg#1=[count($17)]) HiveFilter(condition=[BETWEEN(false, $10, 1, 20)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)]) HiveFilter(condition=[BETWEEN(false, $10, 1, 20)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) @@ -153,11 +153,11 @@ HiveProject(bucket1=[CASE($1, $2, $3)], bucket2=[CASE($4, $5, $6)], bucket3=[CAS HiveAggregate(group=[{}], agg#0=[count()]) HiveFilter(condition=[BETWEEN(false, $10, 21, 40)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($17)], agg#1=[count($17)]) HiveFilter(condition=[BETWEEN(false, $10, 21, 40)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)]) HiveFilter(condition=[BETWEEN(false, $10, 21, 40)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) @@ -165,11 +165,11 @@ HiveProject(bucket1=[CASE($1, $2, $3)], bucket2=[CASE($4, $5, $6)], bucket3=[CAS HiveAggregate(group=[{}], agg#0=[count()]) HiveFilter(condition=[BETWEEN(false, $10, 41, 60)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($17)], agg#1=[count($17)]) HiveFilter(condition=[BETWEEN(false, $10, 41, 60)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)]) HiveFilter(condition=[BETWEEN(false, $10, 41, 60)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) @@ -177,11 +177,11 @@ HiveProject(bucket1=[CASE($1, $2, $3)], bucket2=[CASE($4, $5, $6)], bucket3=[CAS HiveAggregate(group=[{}], agg#0=[count()]) HiveFilter(condition=[BETWEEN(false, $10, 61, 80)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($17)], agg#1=[count($17)]) HiveFilter(condition=[BETWEEN(false, $10, 61, 80)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)]) HiveFilter(condition=[BETWEEN(false, $10, 61, 80)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) @@ -189,11 +189,11 @@ HiveProject(bucket1=[CASE($1, $2, $3)], bucket2=[CASE($4, $5, $6)], bucket3=[CAS HiveAggregate(group=[{}], agg#0=[count()]) HiveFilter(condition=[BETWEEN(false, $10, 81, 100)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($17)], agg#1=[count($17)]) HiveFilter(condition=[BETWEEN(false, $10, 81, 100)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(_o__c0=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($21)], agg#1=[count($21)]) HiveFilter(condition=[BETWEEN(false, $10, 81, 100)]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query92.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query92.q.out index 16098d7243..5d0a89eed9 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query92.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query92.q.out @@ -75,7 +75,7 @@ HiveProject(excess discount amount=[$0]) HiveFilter(condition=[IS NOT NULL($0)]) HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales]) HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[BETWEEN(false, CAST($2):TIMESTAMP(9), 1998-03-18 00:00:00, 1998-06-16 00:00:00)]) + HiveFilter(condition=[BETWEEN(false, CAST($2):TIMESTAMP(9), CAST(_UTF-16LE'1998-03-18'):TIMESTAMP(9), 1998-06-16 00:00:00)]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(ws_item_sk=[$0], CAST3=[$1], i_item_sk=[$2]) HiveJoin(condition=[=($0, $2)], joinType=[inner], algorithm=[none], cost=[not available]) @@ -86,7 +86,7 @@ HiveProject(excess discount amount=[$0]) HiveFilter(condition=[IS NOT NULL($0)]) HiveTableScan(table=[[default, web_sales]], table:alias=[web_sales]) HiveProject(d_date_sk=[$0]) - HiveFilter(condition=[BETWEEN(false, CAST($2):TIMESTAMP(9), 1998-03-18 00:00:00, 1998-06-16 00:00:00)]) + HiveFilter(condition=[BETWEEN(false, CAST($2):TIMESTAMP(9), CAST(_UTF-16LE'1998-03-18'):TIMESTAMP(9), 1998-06-16 00:00:00)]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(i_item_sk=[$0]) HiveFilter(condition=[=($13, 269)]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query93.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query93.q.out index 49023208dc..d35ddcf45e 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query93.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query93.q.out @@ -42,9 +42,9 @@ POSTHOOK: Input: default@store_sales POSTHOOK: Output: hdfs://### HDFS PATH ### CBO PLAN: HiveSortLimit(sort0=[$1], sort1=[$0], dir0=[ASC], dir1=[ASC], fetch=[100]) - HiveProject(ss_customer_sk=[$0], $f1=[$1]) + HiveProject($f0=[$0], $f1=[$1]) HiveAggregate(group=[{0}], agg#0=[sum($1)]) - HiveProject(ss_customer_sk=[$1], act_sales=[CASE(IS NOT NULL($8), *(CAST(-($3, $8)):DECIMAL(10, 0), $4), *(CAST($3):DECIMAL(10, 0), $4))]) + HiveProject($f0=[$1], $f1=[CASE(IS NOT NULL($8), *(CAST(-($3, $8)):DECIMAL(10, 0), $4), *(CAST($3):DECIMAL(10, 0), $4))]) HiveJoin(condition=[AND(=($5, $0), =($7, $2))], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(ss_item_sk=[$2], ss_customer_sk=[$3], ss_ticket_number=[$9], ss_quantity=[$10], ss_sales_price=[$13]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query94.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query94.q.out index 19c531273b..769556d317 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query94.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query94.q.out @@ -85,7 +85,7 @@ HiveProject(order count=[$0], total shipping cost=[$1], total net profit=[$2]) HiveFilter(condition=[AND(IS NOT NULL($2), IS NOT NULL($11), IS NOT NULL($13))]) HiveTableScan(table=[[default, web_sales]], table:alias=[ws1]) HiveProject(d_date_sk=[$0], d_date=[$2]) - HiveFilter(condition=[BETWEEN(false, CAST($2):TIMESTAMP(9), 1999-05-01 00:00:00, 1999-06-30 00:00:00)]) + HiveFilter(condition=[BETWEEN(false, CAST($2):TIMESTAMP(9), CAST(_UTF-16LE'1999-5-01'):TIMESTAMP(9), 1999-06-30 00:00:00)]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(web_site_sk=[$0], web_company_name=[CAST(_UTF-16LE'pri'):VARCHAR(2147483647) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary"]) HiveFilter(condition=[=($14, _UTF-16LE'pri')]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query95.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query95.q.out index 526dafb1f3..d579077d5b 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query95.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query95.q.out @@ -106,7 +106,7 @@ HiveProject(order count=[$0], total shipping cost=[$1], total net profit=[$2]) HiveFilter(condition=[AND(IS NOT NULL($2), IS NOT NULL($11), IS NOT NULL($13))]) HiveTableScan(table=[[default, web_sales]], table:alias=[ws1]) HiveProject(d_date_sk=[$0], d_date=[$2]) - HiveFilter(condition=[BETWEEN(false, CAST($2):TIMESTAMP(9), 1999-05-01 00:00:00, 1999-06-30 00:00:00)]) + HiveFilter(condition=[BETWEEN(false, CAST($2):TIMESTAMP(9), CAST(_UTF-16LE'1999-5-01'):TIMESTAMP(9), 1999-06-30 00:00:00)]) HiveTableScan(table=[[default, date_dim]], table:alias=[date_dim]) HiveProject(web_site_sk=[$0]) HiveFilter(condition=[=($14, _UTF-16LE'pri')]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query97.q.out ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query97.q.out index 6151627c83..f5e24c58ae 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query97.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/cbo_query97.q.out @@ -58,7 +58,7 @@ CBO PLAN: HiveSortLimit(fetch=[100]) HiveProject($f0=[$0], $f1=[$1], $f2=[$2]) HiveAggregate(group=[{}], agg#0=[sum($0)], agg#1=[sum($1)], agg#2=[sum($2)]) - HiveProject($f0=[CASE(AND(IS NOT NULL($0), IS NULL($2)), 1, 0)], $f1=[CASE(AND(IS NULL($0), IS NOT NULL($2)), 1, 0)], $f2=[CASE(AND(IS NOT NULL($0), IS NOT NULL($2)), 1, 0)]) + HiveProject($f0=[CAST(CASE(AND(IS NULL($2), IS NOT NULL($0)), 1, 0)):INTEGER], $f1=[CASE(AND(IS NULL($0), IS NOT NULL($2)), 1, 0)], $f2=[CASE(AND(IS NOT NULL($0), IS NOT NULL($2)), 1, 0)]) HiveJoin(condition=[AND(=($0, $2), =($1, $3))], joinType=[full], algorithm=[none], cost=[not available]) HiveProject(ss_customer_sk=[$1], ss_item_sk=[$0]) HiveAggregate(group=[{1, 2}]) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/mv_query44.q.out ql/src/test/results/clientpositive/perf/tez/constraints/mv_query44.q.out index db9acc93cb..7ba03a1644 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/mv_query44.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/mv_query44.q.out @@ -19,7 +19,7 @@ POSTHOOK: type: CREATE_MATERIALIZED_VIEW POSTHOOK: Input: default@store_sales POSTHOOK: Output: database:default POSTHOOK: Output: default@mv_store_sales_item_customer -Warning: Shuffle Join MERGEJOIN[101][tables = [$hdt$_1, $hdt$_2]] in Stage 'Reducer 8' is a cross product +Warning: Shuffle Join MERGEJOIN[103][tables = [$hdt$_1, $hdt$_2]] in Stage 'Reducer 3' is a cross product PREHOOK: query: explain select asceding.rnk, i1.i_product_name best_performing, i2.i_product_name worst_performing from(select * @@ -97,118 +97,118 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### Plan optimized by CBO. Vertex dependency in root stage -Reducer 10 <- Reducer 8 (SIMPLE_EDGE) -Reducer 12 <- Map 11 (SIMPLE_EDGE) -Reducer 2 <- Map 1 (SIMPLE_EDGE), Reducer 9 (SIMPLE_EDGE) -Reducer 3 <- Reducer 2 (SIMPLE_EDGE), Reducer 5 (SIMPLE_EDGE) +Reducer 11 <- Map 10 (SIMPLE_EDGE) +Reducer 2 <- Map 1 (SIMPLE_EDGE) +Reducer 3 <- Reducer 11 (CUSTOM_SIMPLE_EDGE), Reducer 2 (CUSTOM_SIMPLE_EDGE) Reducer 4 <- Reducer 3 (SIMPLE_EDGE) -Reducer 5 <- Map 1 (SIMPLE_EDGE), Reducer 10 (SIMPLE_EDGE) -Reducer 7 <- Map 6 (SIMPLE_EDGE) -Reducer 8 <- Reducer 12 (CUSTOM_SIMPLE_EDGE), Reducer 7 (CUSTOM_SIMPLE_EDGE) -Reducer 9 <- Reducer 8 (SIMPLE_EDGE) +Reducer 5 <- Reducer 4 (SIMPLE_EDGE), Reducer 9 (SIMPLE_EDGE) +Reducer 6 <- Map 12 (SIMPLE_EDGE), Reducer 5 (SIMPLE_EDGE) +Reducer 7 <- Map 12 (SIMPLE_EDGE), Reducer 6 (SIMPLE_EDGE) +Reducer 8 <- Reducer 7 (SIMPLE_EDGE) +Reducer 9 <- Reducer 3 (SIMPLE_EDGE) Stage-0 Fetch Operator limit:100 Stage-1 - Reducer 4 vectorized - File Output Operator [FS_135] - Limit [LIM_134] (rows=100 width=218) + Reducer 8 vectorized + File Output Operator [FS_137] + Limit [LIM_136] (rows=100 width=218) Number of rows:100 - Select Operator [SEL_133] (rows=6951 width=218) + Select Operator [SEL_135] (rows=6951 width=218) Output:["_col0","_col1","_col2"] - <-Reducer 3 [SIMPLE_EDGE] - SHUFFLE [RS_67] - Select Operator [SEL_66] (rows=6951 width=218) + <-Reducer 7 [SIMPLE_EDGE] + SHUFFLE [RS_66] + Select Operator [SEL_65] (rows=6951 width=218) Output:["_col0","_col1","_col2"] - Merge Join Operator [MERGEJOIN_105] (rows=6951 width=218) - Conds:RS_63._col3=RS_64._col3(Inner),Output:["_col1","_col3","_col5"] - <-Reducer 2 [SIMPLE_EDGE] - SHUFFLE [RS_63] - PartitionCols:_col3 - Merge Join Operator [MERGEJOIN_102] (rows=6951 width=111) - Conds:RS_107._col0=RS_127._col0(Inner),Output:["_col1","_col3"] - <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_107] + Merge Join Operator [MERGEJOIN_107] (rows=6951 width=218) + Conds:RS_62._col2=RS_134._col0(Inner),Output:["_col1","_col5","_col7"] + <-Map 12 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_134] + PartitionCols:_col0 + Select Operator [SEL_132] (rows=462000 width=111) + Output:["_col0","_col1"] + TableScan [TS_52] (rows=462000 width=111) + default@item,i1,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_product_name"] + <-Reducer 6 [SIMPLE_EDGE] + SHUFFLE [RS_62] + PartitionCols:_col2 + Merge Join Operator [MERGEJOIN_106] (rows=6951 width=115) + Conds:RS_59._col0=RS_133._col0(Inner),Output:["_col1","_col2","_col5"] + <-Map 12 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_133] PartitionCols:_col0 - Select Operator [SEL_106] (rows=462000 width=111) - Output:["_col0","_col1"] - TableScan [TS_0] (rows=462000 width=111) - default@item,i1,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_product_name"] - <-Reducer 9 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_127] + Please refer to the previous Select Operator [SEL_132] + <-Reducer 5 [SIMPLE_EDGE] + SHUFFLE [RS_59] PartitionCols:_col0 - Select Operator [SEL_126] (rows=6951 width=8) - Output:["_col0","_col1"] - Filter Operator [FIL_125] (rows=6951 width=116) - predicate:(rank_window_0 < 11) - PTF Operator [PTF_124] (rows=20854 width=116) - Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col1 ASC NULLS FIRST","partition by:":"0"}] - Select Operator [SEL_123] (rows=20854 width=116) - Output:["_col0","_col1"] - <-Reducer 8 [SIMPLE_EDGE] - SHUFFLE [RS_21] - PartitionCols:0 - Filter Operator [FIL_20] (rows=20854 width=228) - predicate:(_col1 > (0.9 * _col2)) - Merge Join Operator [MERGEJOIN_101] (rows=62562 width=228) - Conds:(Inner),Output:["_col0","_col1","_col2"] - <-Reducer 12 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_122] - Select Operator [SEL_121] (rows=1 width=112) - Output:["_col0"] - Group By Operator [GBY_120] (rows=1 width=124) - Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)","count(VALUE._col1)"],keys:KEY._col0 - <-Map 11 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_119] - PartitionCols:_col0 - Group By Operator [GBY_118] (rows=258 width=124) - Output:["_col0","_col1","_col2"],aggregations:["sum(_col1)","count(_col1)"],keys:true - Select Operator [SEL_117] (rows=287946 width=114) - Output:["_col1"] - Filter Operator [FIL_116] (rows=287946 width=114) - predicate:((ss_store_sk = 410) and ss_hdemo_sk is null) - TableScan [TS_9] (rows=575995635 width=114) - default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_hdemo_sk","ss_store_sk","ss_net_profit"] - <-Reducer 7 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_115] - Select Operator [SEL_114] (rows=62562 width=116) - Output:["_col0","_col1"] - Group By Operator [GBY_113] (rows=62562 width=124) - Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)","count(VALUE._col1)"],keys:KEY._col0 - <-Map 6 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_112] - PartitionCols:_col0 - Group By Operator [GBY_111] (rows=3199976 width=124) - Output:["_col0","_col1","_col2"],aggregations:["sum(ss_net_profit)","count(ss_net_profit)"],keys:ss_item_sk - Select Operator [SEL_110] (rows=6399952 width=114) - Output:["ss_item_sk","ss_net_profit"] - Filter Operator [FIL_109] (rows=6399952 width=114) - predicate:(ss_store_sk = 410) - TableScan [TS_2] (rows=575995635 width=114) - default@store_sales,ss1,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_item_sk","ss_store_sk","ss_net_profit"] - <-Reducer 5 [SIMPLE_EDGE] - SHUFFLE [RS_64] - PartitionCols:_col3 - Merge Join Operator [MERGEJOIN_104] (rows=6951 width=111) - Conds:RS_108._col0=RS_132._col0(Inner),Output:["_col1","_col3"] - <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_108] - PartitionCols:_col0 - Please refer to the previous Select Operator [SEL_106] - <-Reducer 10 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_132] - PartitionCols:_col0 - Select Operator [SEL_131] (rows=6951 width=8) - Output:["_col0","_col1"] - Filter Operator [FIL_130] (rows=6951 width=116) - predicate:(rank_window_0 < 11) - PTF Operator [PTF_129] (rows=20854 width=116) - Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col1 DESC NULLS LAST","partition by:":"0"}] - Select Operator [SEL_128] (rows=20854 width=116) - Output:["_col0","_col1"] - <-Reducer 8 [SIMPLE_EDGE] - SHUFFLE [RS_49] - PartitionCols:0 - Please refer to the previous Filter Operator [FIL_20] + Merge Join Operator [MERGEJOIN_105] (rows=6951 width=12) + Conds:RS_126._col1=RS_131._col1(Inner),Output:["_col0","_col1","_col2"] + <-Reducer 4 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_126] + PartitionCols:_col1 + Select Operator [SEL_125] (rows=6951 width=8) + Output:["_col0","_col1"] + Filter Operator [FIL_124] (rows=6951 width=116) + predicate:(rank_window_0 < 11) + PTF Operator [PTF_123] (rows=20854 width=116) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col1 ASC NULLS FIRST","partition by:":"0"}] + Select Operator [SEL_122] (rows=20854 width=116) + Output:["_col0","_col1"] + <-Reducer 3 [SIMPLE_EDGE] + SHUFFLE [RS_19] + PartitionCols:0 + Filter Operator [FIL_18] (rows=20854 width=228) + predicate:(_col1 > (0.9 * _col2)) + Merge Join Operator [MERGEJOIN_103] (rows=62562 width=228) + Conds:(Inner),Output:["_col0","_col1","_col2"] + <-Reducer 11 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_121] + Select Operator [SEL_120] (rows=1 width=112) + Output:["_col0"] + Group By Operator [GBY_119] (rows=1 width=124) + Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)","count(VALUE._col1)"],keys:KEY._col0 + <-Map 10 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_118] + PartitionCols:_col0 + Group By Operator [GBY_117] (rows=258 width=124) + Output:["_col0","_col1","_col2"],aggregations:["sum(_col1)","count(_col1)"],keys:true + Select Operator [SEL_116] (rows=287946 width=114) + Output:["_col1"] + Filter Operator [FIL_115] (rows=287946 width=114) + predicate:((ss_store_sk = 410) and ss_hdemo_sk is null) + TableScan [TS_7] (rows=575995635 width=114) + default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_hdemo_sk","ss_store_sk","ss_net_profit"] + <-Reducer 2 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_114] + Select Operator [SEL_113] (rows=62562 width=116) + Output:["_col0","_col1"] + Group By Operator [GBY_112] (rows=62562 width=124) + Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)","count(VALUE._col1)"],keys:KEY._col0 + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_111] + PartitionCols:_col0 + Group By Operator [GBY_110] (rows=3199976 width=124) + Output:["_col0","_col1","_col2"],aggregations:["sum(ss_net_profit)","count(ss_net_profit)"],keys:ss_item_sk + Select Operator [SEL_109] (rows=6399952 width=114) + Output:["ss_item_sk","ss_net_profit"] + Filter Operator [FIL_108] (rows=6399952 width=114) + predicate:(ss_store_sk = 410) + TableScan [TS_0] (rows=575995635 width=114) + default@store_sales,ss1,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_item_sk","ss_store_sk","ss_net_profit"] + <-Reducer 9 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_131] + PartitionCols:_col1 + Select Operator [SEL_130] (rows=6951 width=8) + Output:["_col0","_col1"] + Filter Operator [FIL_129] (rows=6951 width=116) + predicate:(rank_window_0 < 11) + PTF Operator [PTF_128] (rows=20854 width=116) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col1 DESC NULLS LAST","partition by:":"0"}] + Select Operator [SEL_127] (rows=20854 width=116) + Output:["_col0","_col1"] + <-Reducer 3 [SIMPLE_EDGE] + SHUFFLE [RS_45] + PartitionCols:0 + Please refer to the previous Filter Operator [FIL_18] diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query1.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query1.q.out index 69f93290d9..d1fd7a5eb8 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query1.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query1.q.out @@ -62,8 +62,8 @@ Vertex dependency in root stage Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 10 (SIMPLE_EDGE) Reducer 3 <- Reducer 2 (SIMPLE_EDGE) Reducer 4 <- Map 11 (SIMPLE_EDGE), Reducer 3 (SIMPLE_EDGE) -Reducer 5 <- Map 12 (SIMPLE_EDGE), Reducer 4 (SIMPLE_EDGE) -Reducer 6 <- Reducer 5 (SIMPLE_EDGE), Reducer 9 (SIMPLE_EDGE) +Reducer 5 <- Reducer 4 (ONE_TO_ONE_EDGE), Reducer 9 (SIMPLE_EDGE) +Reducer 6 <- Map 12 (SIMPLE_EDGE), Reducer 5 (SIMPLE_EDGE) Reducer 7 <- Reducer 6 (SIMPLE_EDGE) Reducer 8 <- Map 1 (SIMPLE_EDGE), Map 10 (SIMPLE_EDGE) Reducer 9 <- Reducer 8 (SIMPLE_EDGE) @@ -73,105 +73,105 @@ Stage-0 limit:100 Stage-1 Reducer 7 vectorized - File Output Operator [FS_159] - Limit [LIM_158] (rows=100 width=100) + File Output Operator [FS_160] + Limit [LIM_159] (rows=100 width=100) Number of rows:100 - Select Operator [SEL_157] (rows=816091 width=100) + Select Operator [SEL_158] (rows=816091 width=100) Output:["_col0"] <-Reducer 6 [SIMPLE_EDGE] SHUFFLE [RS_49] Select Operator [SEL_48] (rows=816091 width=100) Output:["_col0"] - Filter Operator [FIL_47] (rows=816091 width=324) - predicate:(_col2 > _col6) - Merge Join Operator [MERGEJOIN_133] (rows=2448274 width=324) - Conds:RS_44._col1=RS_156._col1(Inner),Output:["_col2","_col5","_col6"] - <-Reducer 5 [SIMPLE_EDGE] - SHUFFLE [RS_44] - PartitionCols:_col1 - Merge Join Operator [MERGEJOIN_131] (rows=2369298 width=213) - Conds:RS_41._col0=RS_151._col0(Inner),Output:["_col1","_col2","_col5"] - <-Map 12 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_151] - PartitionCols:_col0 - Select Operator [SEL_150] (rows=80000000 width=104) - Output:["_col0","_col1"] - TableScan [TS_17] (rows=80000000 width=104) - default@customer,customer,Tbl:COMPLETE,Col:COMPLETE,Output:["c_customer_sk","c_customer_id"] - <-Reducer 4 [SIMPLE_EDGE] - SHUFFLE [RS_41] - PartitionCols:_col0 - Merge Join Operator [MERGEJOIN_130] (rows=2369298 width=114) - Conds:RS_146._col1=RS_149._col0(Inner),Output:["_col0","_col1","_col2"] + Merge Join Operator [MERGEJOIN_134] (rows=816091 width=100) + Conds:RS_45._col0=RS_157._col0(Inner),Output:["_col7"] + <-Map 12 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_157] + PartitionCols:_col0 + Select Operator [SEL_156] (rows=80000000 width=104) + Output:["_col0","_col1"] + TableScan [TS_36] (rows=80000000 width=104) + default@customer,customer,Tbl:COMPLETE,Col:COMPLETE,Output:["c_customer_sk","c_customer_id"] + <-Reducer 5 [SIMPLE_EDGE] + SHUFFLE [RS_45] + PartitionCols:_col0 + Filter Operator [FIL_44] (rows=816091 width=225) + predicate:(_col2 > _col4) + Merge Join Operator [MERGEJOIN_133] (rows=2448274 width=225) + Conds:RS_41._col1=RS_155._col1(Inner),Output:["_col0","_col2","_col4"] + <-Reducer 4 [ONE_TO_ONE_EDGE] + FORWARD [RS_41] + PartitionCols:_col1 + Merge Join Operator [MERGEJOIN_131] (rows=2369298 width=114) + Conds:RS_147._col1=RS_150._col0(Inner),Output:["_col0","_col1","_col2"] <-Map 11 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_149] + SHUFFLE [RS_150] PartitionCols:_col0 - Select Operator [SEL_148] (rows=35 width=4) + Select Operator [SEL_149] (rows=35 width=4) Output:["_col0"] - Filter Operator [FIL_147] (rows=35 width=90) + Filter Operator [FIL_148] (rows=35 width=90) predicate:(s_state = 'NM') TableScan [TS_14] (rows=1704 width=90) default@store,store,Tbl:COMPLETE,Col:COMPLETE,Output:["s_store_sk","s_state"] <-Reducer 3 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_146] + SHUFFLE [RS_147] PartitionCols:_col1 - Select Operator [SEL_145] (rows=14291868 width=119) + Select Operator [SEL_146] (rows=14291868 width=119) Output:["_col0","_col1","_col2"] - Group By Operator [GBY_144] (rows=14291868 width=119) + Group By Operator [GBY_145] (rows=14291868 width=119) Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1 <-Reducer 2 [SIMPLE_EDGE] SHUFFLE [RS_11] PartitionCols:_col0, _col1 Group By Operator [GBY_10] (rows=16855704 width=119) Output:["_col0","_col1","_col2"],aggregations:["sum(_col3)"],keys:_col2, _col1 - Merge Join Operator [MERGEJOIN_129] (rows=16855704 width=107) - Conds:RS_138._col0=RS_142._col0(Inner),Output:["_col1","_col2","_col3"] + Merge Join Operator [MERGEJOIN_130] (rows=16855704 width=107) + Conds:RS_139._col0=RS_143._col0(Inner),Output:["_col1","_col2","_col3"] <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_138] + SHUFFLE [RS_139] PartitionCols:_col0 - Select Operator [SEL_136] (rows=51757026 width=119) + Select Operator [SEL_137] (rows=51757026 width=119) Output:["_col0","_col1","_col2","_col3"] - Filter Operator [FIL_134] (rows=51757026 width=119) + Filter Operator [FIL_135] (rows=51757026 width=119) predicate:(sr_customer_sk is not null and sr_returned_date_sk is not null and sr_store_sk is not null) TableScan [TS_0] (rows=57591150 width=119) default@store_returns,store_returns,Tbl:COMPLETE,Col:COMPLETE,Output:["sr_returned_date_sk","sr_customer_sk","sr_store_sk","sr_fee"] <-Map 10 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_142] + SHUFFLE [RS_143] PartitionCols:_col0 - Select Operator [SEL_141] (rows=652 width=4) + Select Operator [SEL_142] (rows=652 width=4) Output:["_col0"] - Filter Operator [FIL_140] (rows=652 width=8) + Filter Operator [FIL_141] (rows=652 width=8) predicate:(d_year = 2000) TableScan [TS_3] (rows=73049 width=8) default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year"] - <-Reducer 9 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_156] - PartitionCols:_col1 - Select Operator [SEL_155] (rows=31 width=115) - Output:["_col0","_col1"] - Group By Operator [GBY_154] (rows=31 width=123) - Output:["_col0","_col1","_col2"],aggregations:["sum(_col2)","count(_col2)"],keys:_col1 - Select Operator [SEL_153] (rows=14291868 width=119) - Output:["_col1","_col2"] - Group By Operator [GBY_152] (rows=14291868 width=119) - Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1 - <-Reducer 8 [SIMPLE_EDGE] - SHUFFLE [RS_30] - PartitionCols:_col0 - Group By Operator [GBY_29] (rows=17467258 width=119) - Output:["_col0","_col1","_col2"],aggregations:["sum(_col3)"],keys:_col2, _col1 - Merge Join Operator [MERGEJOIN_132] (rows=17467258 width=107) - Conds:RS_139._col0=RS_143._col0(Inner),Output:["_col1","_col2","_col3"] - <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_139] - PartitionCols:_col0 - Select Operator [SEL_137] (rows=53634860 width=119) - Output:["_col0","_col1","_col2","_col3"] - Filter Operator [FIL_135] (rows=53634860 width=119) - predicate:(sr_returned_date_sk is not null and sr_store_sk is not null) - Please refer to the previous TableScan [TS_0] - <-Map 10 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_143] - PartitionCols:_col0 - Please refer to the previous Select Operator [SEL_141] + <-Reducer 9 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_155] + PartitionCols:_col1 + Select Operator [SEL_154] (rows=31 width=115) + Output:["_col0","_col1"] + Group By Operator [GBY_153] (rows=31 width=123) + Output:["_col0","_col1","_col2"],aggregations:["sum(_col2)","count(_col2)"],keys:_col1 + Select Operator [SEL_152] (rows=14291868 width=119) + Output:["_col1","_col2"] + Group By Operator [GBY_151] (rows=14291868 width=119) + Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1 + <-Reducer 8 [SIMPLE_EDGE] + SHUFFLE [RS_28] + PartitionCols:_col0 + Group By Operator [GBY_27] (rows=17467258 width=119) + Output:["_col0","_col1","_col2"],aggregations:["sum(_col3)"],keys:_col2, _col1 + Merge Join Operator [MERGEJOIN_132] (rows=17467258 width=107) + Conds:RS_140._col0=RS_144._col0(Inner),Output:["_col1","_col2","_col3"] + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_140] + PartitionCols:_col0 + Select Operator [SEL_138] (rows=53634860 width=119) + Output:["_col0","_col1","_col2","_col3"] + Filter Operator [FIL_136] (rows=53634860 width=119) + predicate:(sr_returned_date_sk is not null and sr_store_sk is not null) + Please refer to the previous TableScan [TS_0] + <-Map 10 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_144] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_142] diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query11.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query11.q.out index 7e0582e164..18ccbeb9dd 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query11.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query11.q.out @@ -199,7 +199,7 @@ Stage-0 Select Operator [SEL_88] (rows=12248094 width=85) Output:["_col0"] Filter Operator [FIL_87] (rows=12248094 width=537) - predicate:CASE WHEN (_col4 is not null) THEN (CASE WHEN (_col2) THEN (((_col6 / _col1) > (_col9 / _col4))) ELSE ((null > (_col9 / _col4))) END) ELSE (CASE WHEN (_col2) THEN (((_col6 / _col1) > null)) ELSE (null) END) END + predicate:CASE WHEN (_col4 is not null) THEN (CASE WHEN (_col2) THEN (((_col6 / _col1) > (_col9 / _col4))) ELSE (null) END) ELSE (null) END Merge Join Operator [MERGEJOIN_283] (rows=24496188 width=537) Conds:RS_84._col3=RS_346._col0(Inner),Output:["_col1","_col2","_col4","_col6","_col8","_col9"] <-Reducer 20 [SIMPLE_EDGE] vectorized diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query21.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query21.q.out index 67fdc85be3..89f8369ee8 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query21.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query21.q.out @@ -88,7 +88,7 @@ Stage-0 <-Reducer 5 [SIMPLE_EDGE] vectorized SHUFFLE [RS_88] Filter Operator [FIL_87] (rows=231983 width=216) - predicate:CASE WHEN ((_col2 > 0L)) THEN ((UDFToDouble(_col3) / UDFToDouble(_col2)) BETWEEN 0.666667D AND 1.5D) ELSE (null) END + predicate:CASE WHEN ((_col2 > 0L)) THEN ((UDFToDouble(_col3) / UDFToDouble(_col2)) BETWEEN 0.666667D AND 1.5D) ELSE (false) END Group By Operator [GBY_86] (rows=463966 width=216) Output:["_col0","_col1","_col2","_col3"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)"],keys:KEY._col0, KEY._col1 <-Reducer 4 [SIMPLE_EDGE] diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query31.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query31.q.out index 8e0de0ffe2..4fc0c77352 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query31.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query31.q.out @@ -158,7 +158,7 @@ Stage-0 Select Operator [SEL_138] (rows=110 width=550) Output:["_col0","_col1","_col2","_col3","_col4","_col5"] Filter Operator [FIL_136] (rows=110 width=778) - predicate:(CASE WHEN ((_col11 > 0)) THEN (CASE WHEN (_col2) THEN (((_col6 / _col1) > (_col9 / _col11))) ELSE ((null > (_col9 / _col11))) END) ELSE (CASE WHEN (_col2) THEN (((_col6 / _col1) > null)) ELSE (null) END) END and CASE WHEN ((_col9 > 0)) THEN (CASE WHEN (_col7) THEN (((_col4 / _col6) > (_col13 / _col9))) ELSE ((null > (_col13 / _col9))) END) ELSE (CASE WHEN (_col7) THEN (((_col4 / _col6) > null)) ELSE (null) END) END) + predicate:(CASE WHEN ((_col11 > 0)) THEN (CASE WHEN (_col2) THEN (((_col6 / _col1) > (_col9 / _col11))) ELSE (null) END) ELSE (null) END and CASE WHEN ((_col9 > 0)) THEN (CASE WHEN (_col7) THEN (((_col4 / _col6) > (_col13 / _col9))) ELSE (null) END) ELSE (null) END) Merge Join Operator [MERGEJOIN_450] (rows=440 width=778) Conds:RS_133._col0=RS_134._col0(Inner),Output:["_col1","_col2","_col4","_col6","_col7","_col8","_col9","_col11","_col13"] <-Reducer 22 [ONE_TO_ONE_EDGE] diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query34.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query34.q.out index 5b0ded736f..d4aebd36a5 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query34.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query34.q.out @@ -107,7 +107,7 @@ Stage-0 SHUFFLE [RS_122] PartitionCols:_col1 Filter Operator [FIL_121] (rows=6 width=12) - predicate:_col2 BETWEEN 15 AND 20 + predicate:_col2 BETWEEN 15L AND 20L Select Operator [SEL_120] (rows=5521356 width=12) Output:["_col0","_col1","_col2"] Group By Operator [GBY_119] (rows=5521356 width=12) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query36.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query36.q.out index 8158608354..90466fe0e5 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query36.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query36.q.out @@ -93,12 +93,12 @@ Stage-0 Select Operator [SEL_103] (rows=3060 width=490) Output:["_col0","_col1","_col2","_col3","_col4","_col5"] PTF Operator [PTF_102] (rows=3060 width=414) - Function definitions:[{},{"name:":"windowingtablefunction","order by:":"(_col2 / _col3) ASC NULLS FIRST","partition by:":"(grouping(_col4, 1) + grouping(_col4, 0)), CASE WHEN ((grouping(_col4, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END"}] + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"(_col2 / _col3) ASC NULLS FIRST","partition by:":"(grouping(_col4, 1) + grouping(_col4, 0)), CASE WHEN ((grouping(_col4, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END"}] Select Operator [SEL_101] (rows=3060 width=414) Output:["_col0","_col1","_col2","_col3","_col4"] <-Reducer 5 [SIMPLE_EDGE] vectorized SHUFFLE [RS_100] - PartitionCols:(grouping(_col4, 1) + grouping(_col4, 0)), CASE WHEN ((grouping(_col4, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END + PartitionCols:(grouping(_col4, 1) + grouping(_col4, 0)), CASE WHEN ((grouping(_col4, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END Select Operator [SEL_99] (rows=3060 width=414) Output:["_col0","_col1","_col2","_col3","_col4"] Group By Operator [GBY_98] (rows=3060 width=414) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query4.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query4.q.out index e6558e99a9..f52ac789df 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query4.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query4.q.out @@ -281,7 +281,7 @@ Stage-0 Select Operator [SEL_134] (rows=7323197 width=85) Output:["_col0"] Filter Operator [FIL_133] (rows=7323197 width=537) - predicate:CASE WHEN (_col4 is not null) THEN (CASE WHEN (_col7) THEN (((_col9 / _col6) > (_col14 / _col4))) ELSE ((null > (_col14 / _col4))) END) ELSE (CASE WHEN (_col7) THEN (((_col9 / _col6) > null)) ELSE (null) END) END + predicate:CASE WHEN (_col4 is not null) THEN (CASE WHEN (_col7) THEN (((_col9 / _col6) > (_col14 / _col4))) ELSE (null) END) ELSE (null) END Merge Join Operator [MERGEJOIN_466] (rows=14646395 width=537) Conds:RS_130._col3=RS_547._col0(Inner),Output:["_col4","_col6","_col7","_col9","_col13","_col14"] <-Reducer 30 [SIMPLE_EDGE] vectorized @@ -343,7 +343,7 @@ Stage-0 FORWARD [RS_130] PartitionCols:_col3 Filter Operator [FIL_129] (rows=12248093 width=668) - predicate:CASE WHEN (_col2) THEN (CASE WHEN (_col7) THEN (((_col9 / _col6) > (_col11 / _col1))) ELSE ((null > (_col11 / _col1))) END) ELSE (CASE WHEN (_col7) THEN (((_col9 / _col6) > null)) ELSE (null) END) END + predicate:CASE WHEN (_col2) THEN (CASE WHEN (_col7) THEN (((_col9 / _col6) > (_col11 / _col1))) ELSE (null) END) ELSE (null) END Merge Join Operator [MERGEJOIN_465] (rows=24496187 width=668) Conds:RS_126._col3=RS_541._col0(Inner),Output:["_col1","_col2","_col3","_col4","_col6","_col7","_col9","_col11"] <-Reducer 26 [SIMPLE_EDGE] vectorized diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query42.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query42.q.out index 66fe357562..632fec59dc 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query42.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query42.q.out @@ -60,68 +60,70 @@ Reducer 7 <- Map 6 (CUSTOM_SIMPLE_EDGE) Stage-0 Fetch Operator - limit:100 + limit:-1 Stage-1 Reducer 5 vectorized - File Output Operator [FS_74] - Limit [LIM_73] (rows=100 width=210) - Number of rows:100 - Select Operator [SEL_72] (rows=110 width=210) - Output:["_col0","_col1","_col2","_col3"] - <-Reducer 4 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_71] - Select Operator [SEL_70] (rows=110 width=318) - Output:["_col0","_col1","_col3"] - Group By Operator [GBY_69] (rows=110 width=206) - Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1 - <-Reducer 3 [SIMPLE_EDGE] - SHUFFLE [RS_17] - PartitionCols:_col0, _col1 - Group By Operator [GBY_16] (rows=120 width=206) - Output:["_col0","_col1","_col2"],aggregations:["sum(_col2)"],keys:_col5, _col6 - Merge Join Operator [MERGEJOIN_54] (rows=2301098 width=94) - Conds:RS_12._col1=RS_68._col0(Inner),Output:["_col2","_col5","_col6"] - <-Map 8 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_68] - PartitionCols:_col0 - Select Operator [SEL_67] (rows=7333 width=97) - Output:["_col0","_col1","_col2"] - Filter Operator [FIL_66] (rows=7333 width=101) - predicate:(i_manager_id = 1) - TableScan [TS_6] (rows=462000 width=101) - default@item,item,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_category_id","i_category","i_manager_id"] - <-Reducer 2 [SIMPLE_EDGE] - SHUFFLE [RS_12] - PartitionCols:_col1 - Merge Join Operator [MERGEJOIN_53] (rows=15062131 width=4) - Conds:RS_65._col0=RS_57._col0(Inner),Output:["_col1","_col2"] - <-Map 6 [SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_57] - PartitionCols:_col0 - Select Operator [SEL_56] (rows=50 width=4) - Output:["_col0"] - Filter Operator [FIL_55] (rows=50 width=12) - predicate:((d_moy = 12) and (d_year = 1998)) - TableScan [TS_3] (rows=73049 width=12) - default@date_dim,dt,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year","d_moy"] - <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_65] - PartitionCols:_col0 - Select Operator [SEL_64] (rows=550076554 width=114) - Output:["_col0","_col1","_col2"] - Filter Operator [FIL_63] (rows=550076554 width=114) - predicate:((ss_sold_date_sk BETWEEN DynamicValue(RS_10_dt_d_date_sk_min) AND DynamicValue(RS_10_dt_d_date_sk_max) and in_bloom_filter(ss_sold_date_sk, DynamicValue(RS_10_dt_d_date_sk_bloom_filter))) and ss_sold_date_sk is not null) - TableScan [TS_0] (rows=575995635 width=114) - default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_item_sk","ss_ext_sales_price"] - <-Reducer 7 [BROADCAST_EDGE] vectorized - BROADCAST [RS_62] - Group By Operator [GBY_61] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] - <-Map 6 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_60] - Group By Operator [GBY_59] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] - Select Operator [SEL_58] (rows=50 width=4) - Output:["_col0"] - Please refer to the previous Select Operator [SEL_56] + File Output Operator [FS_75] + Select Operator [SEL_74] (rows=100 width=210) + Output:["_col0","_col1","_col2","_col3"] + Limit [LIM_73] (rows=100 width=318) + Number of rows:100 + Select Operator [SEL_72] (rows=110 width=318) + Output:["_col0","_col1","_col2"] + <-Reducer 4 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_71] + Select Operator [SEL_70] (rows=110 width=318) + Output:["_col0","_col1","_col3"] + Group By Operator [GBY_69] (rows=110 width=206) + Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1 + <-Reducer 3 [SIMPLE_EDGE] + SHUFFLE [RS_17] + PartitionCols:_col0, _col1 + Group By Operator [GBY_16] (rows=120 width=206) + Output:["_col0","_col1","_col2"],aggregations:["sum(_col2)"],keys:_col5, _col6 + Merge Join Operator [MERGEJOIN_54] (rows=2301098 width=94) + Conds:RS_12._col1=RS_68._col0(Inner),Output:["_col2","_col5","_col6"] + <-Map 8 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_68] + PartitionCols:_col0 + Select Operator [SEL_67] (rows=7333 width=97) + Output:["_col0","_col1","_col2"] + Filter Operator [FIL_66] (rows=7333 width=101) + predicate:(i_manager_id = 1) + TableScan [TS_6] (rows=462000 width=101) + default@item,item,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_category_id","i_category","i_manager_id"] + <-Reducer 2 [SIMPLE_EDGE] + SHUFFLE [RS_12] + PartitionCols:_col1 + Merge Join Operator [MERGEJOIN_53] (rows=15062131 width=4) + Conds:RS_65._col0=RS_57._col0(Inner),Output:["_col1","_col2"] + <-Map 6 [SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_57] + PartitionCols:_col0 + Select Operator [SEL_56] (rows=50 width=4) + Output:["_col0"] + Filter Operator [FIL_55] (rows=50 width=12) + predicate:((d_moy = 12) and (d_year = 1998)) + TableScan [TS_3] (rows=73049 width=12) + default@date_dim,dt,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year","d_moy"] + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_65] + PartitionCols:_col0 + Select Operator [SEL_64] (rows=550076554 width=114) + Output:["_col0","_col1","_col2"] + Filter Operator [FIL_63] (rows=550076554 width=114) + predicate:((ss_sold_date_sk BETWEEN DynamicValue(RS_10_dt_d_date_sk_min) AND DynamicValue(RS_10_dt_d_date_sk_max) and in_bloom_filter(ss_sold_date_sk, DynamicValue(RS_10_dt_d_date_sk_bloom_filter))) and ss_sold_date_sk is not null) + TableScan [TS_0] (rows=575995635 width=114) + default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_item_sk","ss_ext_sales_price"] + <-Reducer 7 [BROADCAST_EDGE] vectorized + BROADCAST [RS_62] + Group By Operator [GBY_61] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] + <-Map 6 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_60] + Group By Operator [GBY_59] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] + Select Operator [SEL_58] (rows=50 width=4) + Output:["_col0"] + Please refer to the previous Select Operator [SEL_56] diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query44.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query44.q.out index 3fd361a9f9..4e6c083f5b 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query44.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query44.q.out @@ -1,4 +1,4 @@ -Warning: Shuffle Join MERGEJOIN[101][tables = [$hdt$_1, $hdt$_2]] in Stage 'Reducer 8' is a cross product +Warning: Shuffle Join MERGEJOIN[103][tables = [$hdt$_1, $hdt$_2]] in Stage 'Reducer 3' is a cross product PREHOOK: query: explain select asceding.rnk, i1.i_product_name best_performing, i2.i_product_name worst_performing from(select * @@ -76,118 +76,118 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### Plan optimized by CBO. Vertex dependency in root stage -Reducer 10 <- Reducer 8 (SIMPLE_EDGE) -Reducer 12 <- Map 11 (SIMPLE_EDGE) -Reducer 2 <- Map 1 (SIMPLE_EDGE), Reducer 9 (SIMPLE_EDGE) -Reducer 3 <- Reducer 2 (SIMPLE_EDGE), Reducer 5 (SIMPLE_EDGE) +Reducer 11 <- Map 10 (SIMPLE_EDGE) +Reducer 2 <- Map 1 (SIMPLE_EDGE) +Reducer 3 <- Reducer 11 (CUSTOM_SIMPLE_EDGE), Reducer 2 (CUSTOM_SIMPLE_EDGE) Reducer 4 <- Reducer 3 (SIMPLE_EDGE) -Reducer 5 <- Map 1 (SIMPLE_EDGE), Reducer 10 (SIMPLE_EDGE) -Reducer 7 <- Map 6 (SIMPLE_EDGE) -Reducer 8 <- Reducer 12 (CUSTOM_SIMPLE_EDGE), Reducer 7 (CUSTOM_SIMPLE_EDGE) -Reducer 9 <- Reducer 8 (SIMPLE_EDGE) +Reducer 5 <- Reducer 4 (SIMPLE_EDGE), Reducer 9 (SIMPLE_EDGE) +Reducer 6 <- Map 12 (SIMPLE_EDGE), Reducer 5 (SIMPLE_EDGE) +Reducer 7 <- Map 12 (SIMPLE_EDGE), Reducer 6 (SIMPLE_EDGE) +Reducer 8 <- Reducer 7 (SIMPLE_EDGE) +Reducer 9 <- Reducer 3 (SIMPLE_EDGE) Stage-0 Fetch Operator limit:100 Stage-1 - Reducer 4 vectorized - File Output Operator [FS_135] - Limit [LIM_134] (rows=100 width=218) + Reducer 8 vectorized + File Output Operator [FS_137] + Limit [LIM_136] (rows=100 width=218) Number of rows:100 - Select Operator [SEL_133] (rows=6951 width=218) + Select Operator [SEL_135] (rows=6951 width=218) Output:["_col0","_col1","_col2"] - <-Reducer 3 [SIMPLE_EDGE] - SHUFFLE [RS_67] - Select Operator [SEL_66] (rows=6951 width=218) + <-Reducer 7 [SIMPLE_EDGE] + SHUFFLE [RS_66] + Select Operator [SEL_65] (rows=6951 width=218) Output:["_col0","_col1","_col2"] - Merge Join Operator [MERGEJOIN_105] (rows=6951 width=218) - Conds:RS_63._col3=RS_64._col3(Inner),Output:["_col1","_col3","_col5"] - <-Reducer 2 [SIMPLE_EDGE] - SHUFFLE [RS_63] - PartitionCols:_col3 - Merge Join Operator [MERGEJOIN_102] (rows=6951 width=111) - Conds:RS_107._col0=RS_127._col0(Inner),Output:["_col1","_col3"] - <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_107] + Merge Join Operator [MERGEJOIN_107] (rows=6951 width=218) + Conds:RS_62._col2=RS_134._col0(Inner),Output:["_col1","_col5","_col7"] + <-Map 12 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_134] + PartitionCols:_col0 + Select Operator [SEL_132] (rows=462000 width=111) + Output:["_col0","_col1"] + TableScan [TS_52] (rows=462000 width=111) + default@item,i1,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_product_name"] + <-Reducer 6 [SIMPLE_EDGE] + SHUFFLE [RS_62] + PartitionCols:_col2 + Merge Join Operator [MERGEJOIN_106] (rows=6951 width=115) + Conds:RS_59._col0=RS_133._col0(Inner),Output:["_col1","_col2","_col5"] + <-Map 12 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_133] PartitionCols:_col0 - Select Operator [SEL_106] (rows=462000 width=111) - Output:["_col0","_col1"] - TableScan [TS_0] (rows=462000 width=111) - default@item,i1,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_product_name"] - <-Reducer 9 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_127] + Please refer to the previous Select Operator [SEL_132] + <-Reducer 5 [SIMPLE_EDGE] + SHUFFLE [RS_59] PartitionCols:_col0 - Select Operator [SEL_126] (rows=6951 width=8) - Output:["_col0","_col1"] - Filter Operator [FIL_125] (rows=6951 width=116) - predicate:(rank_window_0 < 11) - PTF Operator [PTF_124] (rows=20854 width=116) - Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col1 ASC NULLS FIRST","partition by:":"0"}] - Select Operator [SEL_123] (rows=20854 width=116) - Output:["_col0","_col1"] - <-Reducer 8 [SIMPLE_EDGE] - SHUFFLE [RS_21] - PartitionCols:0 - Filter Operator [FIL_20] (rows=20854 width=228) - predicate:(_col1 > (0.9 * _col2)) - Merge Join Operator [MERGEJOIN_101] (rows=62562 width=228) - Conds:(Inner),Output:["_col0","_col1","_col2"] - <-Reducer 12 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_122] - Select Operator [SEL_121] (rows=1 width=112) - Output:["_col0"] - Group By Operator [GBY_120] (rows=1 width=124) - Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)","count(VALUE._col1)"],keys:KEY._col0 - <-Map 11 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_119] - PartitionCols:_col0 - Group By Operator [GBY_118] (rows=258 width=124) - Output:["_col0","_col1","_col2"],aggregations:["sum(_col1)","count(_col1)"],keys:true - Select Operator [SEL_117] (rows=287946 width=114) - Output:["_col1"] - Filter Operator [FIL_116] (rows=287946 width=114) - predicate:((ss_store_sk = 410) and ss_hdemo_sk is null) - TableScan [TS_9] (rows=575995635 width=114) - default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_hdemo_sk","ss_store_sk","ss_net_profit"] - <-Reducer 7 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_115] - Select Operator [SEL_114] (rows=62562 width=116) - Output:["_col0","_col1"] - Group By Operator [GBY_113] (rows=62562 width=124) - Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)","count(VALUE._col1)"],keys:KEY._col0 - <-Map 6 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_112] - PartitionCols:_col0 - Group By Operator [GBY_111] (rows=3199976 width=124) - Output:["_col0","_col1","_col2"],aggregations:["sum(ss_net_profit)","count(ss_net_profit)"],keys:ss_item_sk - Select Operator [SEL_110] (rows=6399952 width=114) - Output:["ss_item_sk","ss_net_profit"] - Filter Operator [FIL_109] (rows=6399952 width=114) - predicate:(ss_store_sk = 410) - TableScan [TS_2] (rows=575995635 width=114) - default@store_sales,ss1,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_item_sk","ss_store_sk","ss_net_profit"] - <-Reducer 5 [SIMPLE_EDGE] - SHUFFLE [RS_64] - PartitionCols:_col3 - Merge Join Operator [MERGEJOIN_104] (rows=6951 width=111) - Conds:RS_108._col0=RS_132._col0(Inner),Output:["_col1","_col3"] - <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_108] - PartitionCols:_col0 - Please refer to the previous Select Operator [SEL_106] - <-Reducer 10 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_132] - PartitionCols:_col0 - Select Operator [SEL_131] (rows=6951 width=8) - Output:["_col0","_col1"] - Filter Operator [FIL_130] (rows=6951 width=116) - predicate:(rank_window_0 < 11) - PTF Operator [PTF_129] (rows=20854 width=116) - Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col1 DESC NULLS LAST","partition by:":"0"}] - Select Operator [SEL_128] (rows=20854 width=116) - Output:["_col0","_col1"] - <-Reducer 8 [SIMPLE_EDGE] - SHUFFLE [RS_49] - PartitionCols:0 - Please refer to the previous Filter Operator [FIL_20] + Merge Join Operator [MERGEJOIN_105] (rows=6951 width=12) + Conds:RS_126._col1=RS_131._col1(Inner),Output:["_col0","_col1","_col2"] + <-Reducer 4 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_126] + PartitionCols:_col1 + Select Operator [SEL_125] (rows=6951 width=8) + Output:["_col0","_col1"] + Filter Operator [FIL_124] (rows=6951 width=116) + predicate:(rank_window_0 < 11) + PTF Operator [PTF_123] (rows=20854 width=116) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col1 ASC NULLS FIRST","partition by:":"0"}] + Select Operator [SEL_122] (rows=20854 width=116) + Output:["_col0","_col1"] + <-Reducer 3 [SIMPLE_EDGE] + SHUFFLE [RS_19] + PartitionCols:0 + Filter Operator [FIL_18] (rows=20854 width=228) + predicate:(_col1 > (0.9 * _col2)) + Merge Join Operator [MERGEJOIN_103] (rows=62562 width=228) + Conds:(Inner),Output:["_col0","_col1","_col2"] + <-Reducer 11 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_121] + Select Operator [SEL_120] (rows=1 width=112) + Output:["_col0"] + Group By Operator [GBY_119] (rows=1 width=124) + Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)","count(VALUE._col1)"],keys:KEY._col0 + <-Map 10 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_118] + PartitionCols:_col0 + Group By Operator [GBY_117] (rows=258 width=124) + Output:["_col0","_col1","_col2"],aggregations:["sum(_col1)","count(_col1)"],keys:true + Select Operator [SEL_116] (rows=287946 width=114) + Output:["_col1"] + Filter Operator [FIL_115] (rows=287946 width=114) + predicate:((ss_store_sk = 410) and ss_hdemo_sk is null) + TableScan [TS_7] (rows=575995635 width=114) + default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_hdemo_sk","ss_store_sk","ss_net_profit"] + <-Reducer 2 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_114] + Select Operator [SEL_113] (rows=62562 width=116) + Output:["_col0","_col1"] + Group By Operator [GBY_112] (rows=62562 width=124) + Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)","count(VALUE._col1)"],keys:KEY._col0 + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_111] + PartitionCols:_col0 + Group By Operator [GBY_110] (rows=3199976 width=124) + Output:["_col0","_col1","_col2"],aggregations:["sum(ss_net_profit)","count(ss_net_profit)"],keys:ss_item_sk + Select Operator [SEL_109] (rows=6399952 width=114) + Output:["ss_item_sk","ss_net_profit"] + Filter Operator [FIL_108] (rows=6399952 width=114) + predicate:(ss_store_sk = 410) + TableScan [TS_0] (rows=575995635 width=114) + default@store_sales,ss1,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_item_sk","ss_store_sk","ss_net_profit"] + <-Reducer 9 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_131] + PartitionCols:_col1 + Select Operator [SEL_130] (rows=6951 width=8) + Output:["_col0","_col1"] + Filter Operator [FIL_129] (rows=6951 width=116) + predicate:(rank_window_0 < 11) + PTF Operator [PTF_128] (rows=20854 width=116) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col1 DESC NULLS LAST","partition by:":"0"}] + Select Operator [SEL_127] (rows=20854 width=116) + Output:["_col0","_col1"] + <-Reducer 3 [SIMPLE_EDGE] + SHUFFLE [RS_45] + PartitionCols:0 + Please refer to the previous Filter Operator [FIL_18] diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query45.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query45.q.out index 64d9c98395..419a8a10ae 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query45.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query45.q.out @@ -51,133 +51,133 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### Plan optimized by CBO. Vertex dependency in root stage -Map 9 <- Reducer 12 (BROADCAST_EDGE) -Reducer 10 <- Map 11 (SIMPLE_EDGE), Map 9 (SIMPLE_EDGE) -Reducer 12 <- Map 11 (CUSTOM_SIMPLE_EDGE) -Reducer 2 <- Map 1 (SIMPLE_EDGE), Reducer 8 (ONE_TO_ONE_EDGE) -Reducer 3 <- Reducer 10 (SIMPLE_EDGE), Reducer 2 (SIMPLE_EDGE) -Reducer 4 <- Map 13 (SIMPLE_EDGE), Reducer 3 (SIMPLE_EDGE) -Reducer 5 <- Map 14 (SIMPLE_EDGE), Reducer 4 (SIMPLE_EDGE) -Reducer 6 <- Reducer 5 (SIMPLE_EDGE) -Reducer 7 <- Reducer 6 (SIMPLE_EDGE) -Reducer 8 <- Map 1 (SIMPLE_EDGE) +Map 11 <- Reducer 14 (BROADCAST_EDGE) +Reducer 12 <- Map 11 (SIMPLE_EDGE), Map 13 (SIMPLE_EDGE) +Reducer 14 <- Map 13 (CUSTOM_SIMPLE_EDGE) +Reducer 2 <- Map 1 (SIMPLE_EDGE), Reducer 6 (ONE_TO_ONE_EDGE) +Reducer 3 <- Reducer 2 (SIMPLE_EDGE), Reducer 9 (SIMPLE_EDGE) +Reducer 4 <- Reducer 3 (SIMPLE_EDGE) +Reducer 5 <- Reducer 4 (SIMPLE_EDGE) +Reducer 6 <- Map 1 (SIMPLE_EDGE) +Reducer 8 <- Map 10 (SIMPLE_EDGE), Map 7 (SIMPLE_EDGE) +Reducer 9 <- Reducer 12 (SIMPLE_EDGE), Reducer 8 (SIMPLE_EDGE) Stage-0 Fetch Operator limit:100 Stage-1 - Reducer 7 vectorized - File Output Operator [FS_151] - Limit [LIM_150] (rows=100 width=299) + Reducer 5 vectorized + File Output Operator [FS_149] + Limit [LIM_148] (rows=100 width=299) Number of rows:100 - Select Operator [SEL_149] (rows=1143120 width=299) + Select Operator [SEL_147] (rows=285780 width=299) Output:["_col0","_col1","_col2"] - <-Reducer 6 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_148] - Group By Operator [GBY_147] (rows=1143120 width=299) + <-Reducer 4 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_146] + Group By Operator [GBY_145] (rows=285780 width=299) Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1 - <-Reducer 5 [SIMPLE_EDGE] - SHUFFLE [RS_40] + <-Reducer 3 [SIMPLE_EDGE] + SHUFFLE [RS_41] PartitionCols:_col0, _col1 - Group By Operator [GBY_39] (rows=10246864 width=299) + Group By Operator [GBY_40] (rows=3715140 width=299) Output:["_col0","_col1","_col2"],aggregations:["sum(_col3)"],keys:_col8, _col7 - Top N Key Operator [TNK_71] (rows=10246864 width=302) + Top N Key Operator [TNK_69] (rows=10246864 width=302) keys:_col8, _col7,sort order:++,top n:100 - Select Operator [SEL_38] (rows=10246864 width=302) + Select Operator [SEL_39] (rows=10246864 width=302) Output:["_col3","_col7","_col8"] - Filter Operator [FIL_37] (rows=10246864 width=302) + Filter Operator [FIL_38] (rows=10246864 width=302) predicate:((substr(_col8, 1, 5)) IN ('85669', '86197', '88274', '83405', '86475', '85392', '85460', '80348', '81792') or _col15 is not null) - Select Operator [SEL_36] (rows=10246864 width=302) + Select Operator [SEL_37] (rows=10246864 width=302) Output:["_col3","_col7","_col8","_col15"] - Merge Join Operator [MERGEJOIN_121] (rows=10246864 width=302) - Conds:RS_33._col12=RS_146._col0(Inner),Output:["_col3","_col7","_col14","_col15"] - <-Map 14 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_146] + Merge Join Operator [MERGEJOIN_119] (rows=10246864 width=302) + Conds:RS_34._col0=RS_35._col6(Inner),Output:["_col3","_col7","_col8","_col12"] + <-Reducer 2 [SIMPLE_EDGE] + SHUFFLE [RS_34] PartitionCols:_col0 - Select Operator [SEL_145] (rows=40000000 width=191) - Output:["_col0","_col1","_col2"] - TableScan [TS_22] (rows=40000000 width=191) - default@customer_address,customer_address,Tbl:COMPLETE,Col:COMPLETE,Output:["ca_address_sk","ca_county","ca_zip"] - <-Reducer 4 [SIMPLE_EDGE] - SHUFFLE [RS_33] - PartitionCols:_col12 - Merge Join Operator [MERGEJOIN_120] (rows=10246864 width=119) - Conds:RS_30._col6=RS_144._col0(Inner),Output:["_col3","_col7","_col12"] - <-Map 13 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_144] + Merge Join Operator [MERGEJOIN_115] (rows=462007 width=4) + Conds:RS_122._col1=RS_128._col0(Left Outer),Output:["_col0","_col3"] + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_122] + PartitionCols:_col1 + Select Operator [SEL_120] (rows=462000 width=104) + Output:["_col0","_col1"] + TableScan [TS_0] (rows=462000 width=104) + default@item,item,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_item_id"] + <-Reducer 6 [ONE_TO_ONE_EDGE] vectorized + FORWARD [RS_128] PartitionCols:_col0 - Select Operator [SEL_143] (rows=80000000 width=8) + Select Operator [SEL_127] (rows=5 width=104) Output:["_col0","_col1"] - Filter Operator [FIL_142] (rows=80000000 width=8) - predicate:c_current_addr_sk is not null - TableScan [TS_19] (rows=80000000 width=8) - default@customer,customer,Tbl:COMPLETE,Col:COMPLETE,Output:["c_customer_sk","c_current_addr_sk"] - <-Reducer 3 [SIMPLE_EDGE] - SHUFFLE [RS_30] - PartitionCols:_col6 - Merge Join Operator [MERGEJOIN_119] (rows=10246864 width=119) - Conds:RS_27._col0=RS_28._col1(Inner),Output:["_col3","_col6","_col7"] - <-Reducer 10 [SIMPLE_EDGE] - SHUFFLE [RS_28] - PartitionCols:_col1 - Merge Join Operator [MERGEJOIN_118] (rows=10246864 width=119) - Conds:RS_141._col0=RS_133._col0(Inner),Output:["_col1","_col2","_col3"] - <-Map 11 [SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_133] - PartitionCols:_col0 - Select Operator [SEL_132] (rows=130 width=12) - Output:["_col0"] - Filter Operator [FIL_131] (rows=130 width=12) - predicate:((d_qoy = 2) and (d_year = 2000)) - TableScan [TS_12] (rows=73049 width=12) - default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year","d_qoy"] - <-Map 9 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_141] - PartitionCols:_col0 - Select Operator [SEL_140] (rows=143930993 width=123) - Output:["_col0","_col1","_col2","_col3"] - Filter Operator [FIL_139] (rows=143930993 width=123) - predicate:((ws_sold_date_sk BETWEEN DynamicValue(RS_16_date_dim_d_date_sk_min) AND DynamicValue(RS_16_date_dim_d_date_sk_max) and in_bloom_filter(ws_sold_date_sk, DynamicValue(RS_16_date_dim_d_date_sk_bloom_filter))) and ws_bill_customer_sk is not null and ws_sold_date_sk is not null) - TableScan [TS_9] (rows=144002668 width=123) - default@web_sales,web_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ws_sold_date_sk","ws_item_sk","ws_bill_customer_sk","ws_sales_price"] - <-Reducer 12 [BROADCAST_EDGE] vectorized - BROADCAST [RS_138] - Group By Operator [GBY_137] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] - <-Map 11 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_136] - Group By Operator [GBY_135] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] - Select Operator [SEL_134] (rows=130 width=4) - Output:["_col0"] - Please refer to the previous Select Operator [SEL_132] - <-Reducer 2 [SIMPLE_EDGE] - SHUFFLE [RS_27] + Group By Operator [GBY_126] (rows=5 width=100) + Output:["_col0"],keys:KEY._col0 + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_125] + PartitionCols:_col0 + Group By Operator [GBY_124] (rows=5 width=100) + Output:["_col0"],keys:i_item_id + Select Operator [SEL_123] (rows=11 width=104) + Output:["i_item_id"] + Filter Operator [FIL_121] (rows=11 width=104) + predicate:(i_item_sk) IN (2, 3, 5, 7, 11, 13, 17, 19, 23, 29) + Please refer to the previous TableScan [TS_0] + <-Reducer 9 [SIMPLE_EDGE] + SHUFFLE [RS_35] + PartitionCols:_col6 + Merge Join Operator [MERGEJOIN_118] (rows=10246864 width=302) + Conds:RS_27._col0=RS_28._col2(Inner),Output:["_col3","_col4","_col6","_col8"] + <-Reducer 12 [SIMPLE_EDGE] + SHUFFLE [RS_28] + PartitionCols:_col2 + Merge Join Operator [MERGEJOIN_117] (rows=10246864 width=119) + Conds:RS_144._col0=RS_136._col0(Inner),Output:["_col1","_col2","_col3"] + <-Map 13 [SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_136] + PartitionCols:_col0 + Select Operator [SEL_135] (rows=130 width=12) + Output:["_col0"] + Filter Operator [FIL_134] (rows=130 width=12) + predicate:((d_qoy = 2) and (d_year = 2000)) + TableScan [TS_17] (rows=73049 width=12) + default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year","d_qoy"] + <-Map 11 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_144] PartitionCols:_col0 - Merge Join Operator [MERGEJOIN_117] (rows=462007 width=4) - Conds:RS_124._col1=RS_130._col0(Left Outer),Output:["_col0","_col3"] - <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_124] - PartitionCols:_col1 - Select Operator [SEL_122] (rows=462000 width=104) - Output:["_col0","_col1"] - TableScan [TS_0] (rows=462000 width=104) - default@item,item,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_item_id"] - <-Reducer 8 [ONE_TO_ONE_EDGE] vectorized - FORWARD [RS_130] - PartitionCols:_col0 - Select Operator [SEL_129] (rows=5 width=104) - Output:["_col0","_col1"] - Group By Operator [GBY_128] (rows=5 width=100) - Output:["_col0"],keys:KEY._col0 - <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_127] - PartitionCols:_col0 - Group By Operator [GBY_126] (rows=5 width=100) - Output:["_col0"],keys:i_item_id - Select Operator [SEL_125] (rows=11 width=104) - Output:["i_item_id"] - Filter Operator [FIL_123] (rows=11 width=104) - predicate:(i_item_sk) IN (2, 3, 5, 7, 11, 13, 17, 19, 23, 29) - Please refer to the previous TableScan [TS_0] + Select Operator [SEL_143] (rows=143930993 width=123) + Output:["_col0","_col1","_col2","_col3"] + Filter Operator [FIL_142] (rows=143930993 width=123) + predicate:((ws_sold_date_sk BETWEEN DynamicValue(RS_21_date_dim_d_date_sk_min) AND DynamicValue(RS_21_date_dim_d_date_sk_max) and in_bloom_filter(ws_sold_date_sk, DynamicValue(RS_21_date_dim_d_date_sk_bloom_filter))) and ws_bill_customer_sk is not null and ws_sold_date_sk is not null) + TableScan [TS_14] (rows=144002668 width=123) + default@web_sales,web_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ws_sold_date_sk","ws_item_sk","ws_bill_customer_sk","ws_sales_price"] + <-Reducer 14 [BROADCAST_EDGE] vectorized + BROADCAST [RS_141] + Group By Operator [GBY_140] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] + <-Map 13 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_139] + Group By Operator [GBY_138] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] + Select Operator [SEL_137] (rows=130 width=4) + Output:["_col0"] + Please refer to the previous Select Operator [SEL_135] + <-Reducer 8 [SIMPLE_EDGE] + SHUFFLE [RS_27] + PartitionCols:_col0 + Merge Join Operator [MERGEJOIN_116] (rows=80000000 width=191) + Conds:RS_131._col1=RS_133._col0(Inner),Output:["_col0","_col3","_col4"] + <-Map 10 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_133] + PartitionCols:_col0 + Select Operator [SEL_132] (rows=40000000 width=191) + Output:["_col0","_col1","_col2"] + TableScan [TS_12] (rows=40000000 width=191) + default@customer_address,customer_address,Tbl:COMPLETE,Col:COMPLETE,Output:["ca_address_sk","ca_county","ca_zip"] + <-Map 7 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_131] + PartitionCols:_col1 + Select Operator [SEL_130] (rows=80000000 width=8) + Output:["_col0","_col1"] + Filter Operator [FIL_129] (rows=80000000 width=8) + predicate:c_current_addr_sk is not null + TableScan [TS_9] (rows=80000000 width=8) + default@customer,customer,Tbl:COMPLETE,Col:COMPLETE,Output:["c_customer_sk","c_current_addr_sk"] diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query46.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query46.q.out index dde72e07b8..6d0933abc0 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query46.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query46.q.out @@ -83,134 +83,134 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### Plan optimized by CBO. Vertex dependency in root stage -Map 5 <- Reducer 12 (BROADCAST_EDGE) -Reducer 10 <- Reducer 9 (SIMPLE_EDGE) -Reducer 12 <- Map 11 (CUSTOM_SIMPLE_EDGE) -Reducer 2 <- Map 1 (SIMPLE_EDGE), Reducer 10 (SIMPLE_EDGE) -Reducer 3 <- Map 15 (SIMPLE_EDGE), Reducer 2 (SIMPLE_EDGE) +Map 8 <- Reducer 13 (BROADCAST_EDGE) +Reducer 10 <- Map 14 (SIMPLE_EDGE), Reducer 9 (SIMPLE_EDGE) +Reducer 11 <- Map 15 (SIMPLE_EDGE), Reducer 10 (SIMPLE_EDGE) +Reducer 13 <- Map 12 (CUSTOM_SIMPLE_EDGE) +Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 5 (SIMPLE_EDGE) +Reducer 3 <- Reducer 2 (SIMPLE_EDGE), Reducer 7 (SIMPLE_EDGE) Reducer 4 <- Reducer 3 (SIMPLE_EDGE) -Reducer 6 <- Map 11 (SIMPLE_EDGE), Map 5 (SIMPLE_EDGE) -Reducer 7 <- Map 13 (SIMPLE_EDGE), Reducer 6 (SIMPLE_EDGE) -Reducer 8 <- Map 14 (SIMPLE_EDGE), Reducer 7 (SIMPLE_EDGE) -Reducer 9 <- Map 15 (SIMPLE_EDGE), Reducer 8 (SIMPLE_EDGE) +Reducer 6 <- Map 5 (SIMPLE_EDGE), Reducer 11 (SIMPLE_EDGE) +Reducer 7 <- Reducer 6 (SIMPLE_EDGE) +Reducer 9 <- Map 12 (SIMPLE_EDGE), Map 8 (SIMPLE_EDGE) Stage-0 Fetch Operator limit:100 Stage-1 Reducer 4 vectorized - File Output Operator [FS_176] - Limit [LIM_175] (rows=100 width=594) + File Output Operator [FS_172] + Limit [LIM_171] (rows=100 width=594) Number of rows:100 - Select Operator [SEL_174] (rows=8380115 width=594) + Select Operator [SEL_170] (rows=8380115 width=594) Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] <-Reducer 3 [SIMPLE_EDGE] SHUFFLE [RS_44] Select Operator [SEL_43] (rows=8380115 width=594) Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] Filter Operator [FIL_42] (rows=8380115 width=594) - predicate:(_col10 <> _col6) - Merge Join Operator [MERGEJOIN_147] (rows=8380115 width=594) - Conds:RS_39._col1=RS_169._col0(Inner),Output:["_col2","_col3","_col4","_col6","_col7","_col8","_col10"] - <-Map 15 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_169] - PartitionCols:_col0 - Select Operator [SEL_168] (rows=40000000 width=97) - Output:["_col0","_col1"] - TableScan [TS_34] (rows=40000000 width=97) - default@customer_address,current_addr,Tbl:COMPLETE,Col:COMPLETE,Output:["ca_address_sk","ca_city"] + predicate:(_col5 <> _col8) + Merge Join Operator [MERGEJOIN_143] (rows=8380115 width=594) + Conds:RS_39._col0=RS_169._col1(Inner),Output:["_col2","_col3","_col5","_col6","_col8","_col9","_col10"] <-Reducer 2 [SIMPLE_EDGE] SHUFFLE [RS_39] - PartitionCols:_col1 - Merge Join Operator [MERGEJOIN_146] (rows=8380115 width=505) - Conds:RS_150._col0=RS_173._col1(Inner),Output:["_col1","_col2","_col3","_col4","_col6","_col7","_col8"] - <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_150] + PartitionCols:_col0 + Merge Join Operator [MERGEJOIN_138] (rows=80000000 width=277) + Conds:RS_146._col1=RS_148._col0(Inner),Output:["_col0","_col2","_col3","_col5"] + <-Map 5 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_148] PartitionCols:_col0 - Select Operator [SEL_149] (rows=80000000 width=188) + Select Operator [SEL_147] (rows=40000000 width=97) + Output:["_col0","_col1"] + TableScan [TS_3] (rows=40000000 width=97) + default@customer_address,current_addr,Tbl:COMPLETE,Col:COMPLETE,Output:["ca_address_sk","ca_city"] + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_146] + PartitionCols:_col1 + Select Operator [SEL_145] (rows=80000000 width=188) Output:["_col0","_col1","_col2","_col3"] - Filter Operator [FIL_148] (rows=80000000 width=188) + Filter Operator [FIL_144] (rows=80000000 width=188) predicate:c_current_addr_sk is not null TableScan [TS_0] (rows=80000000 width=188) default@customer,customer,Tbl:COMPLETE,Col:COMPLETE,Output:["c_customer_sk","c_current_addr_sk","c_first_name","c_last_name"] - <-Reducer 10 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_173] - PartitionCols:_col1 - Select Operator [SEL_172] (rows=8380115 width=321) - Output:["_col0","_col1","_col2","_col3","_col4"] - Group By Operator [GBY_171] (rows=8380115 width=321) - Output:["_col0","_col1","_col2","_col3","_col4","_col5"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3 - <-Reducer 9 [SIMPLE_EDGE] - SHUFFLE [RS_31] - PartitionCols:_col0, _col1, _col2, _col3 - Group By Operator [GBY_30] (rows=8380115 width=321) - Output:["_col0","_col1","_col2","_col3","_col4","_col5"],aggregations:["sum(_col6)","sum(_col7)"],keys:_col1, _col12, _col3, _col5 - Merge Join Operator [MERGEJOIN_145] (rows=8380115 width=97) - Conds:RS_26._col3=RS_170._col0(Inner),Output:["_col1","_col3","_col5","_col6","_col7","_col12"] + <-Reducer 7 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_169] + PartitionCols:_col1 + Select Operator [SEL_168] (rows=8380115 width=321) + Output:["_col0","_col1","_col2","_col3","_col4"] + Group By Operator [GBY_167] (rows=8380115 width=321) + Output:["_col0","_col1","_col2","_col3","_col4","_col5"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3 + <-Reducer 6 [SIMPLE_EDGE] + SHUFFLE [RS_33] + PartitionCols:_col0, _col1, _col2, _col3 + Group By Operator [GBY_32] (rows=8380115 width=321) + Output:["_col0","_col1","_col2","_col3","_col4","_col5"],aggregations:["sum(_col6)","sum(_col7)"],keys:_col1, _col12, _col3, _col5 + Merge Join Operator [MERGEJOIN_142] (rows=8380115 width=97) + Conds:RS_28._col3=RS_149._col0(Inner),Output:["_col1","_col3","_col5","_col6","_col7","_col12"] + <-Map 5 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_149] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_147] + <-Reducer 11 [SIMPLE_EDGE] + SHUFFLE [RS_28] + PartitionCols:_col3 + Merge Join Operator [MERGEJOIN_141] (rows=8380115 width=4) + Conds:RS_25._col2=RS_166._col0(Inner),Output:["_col1","_col3","_col5","_col6","_col7"] <-Map 15 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_170] + SHUFFLE [RS_166] PartitionCols:_col0 - Please refer to the previous Select Operator [SEL_168] - <-Reducer 8 [SIMPLE_EDGE] - SHUFFLE [RS_26] - PartitionCols:_col3 - Merge Join Operator [MERGEJOIN_144] (rows=8380115 width=4) - Conds:RS_23._col2=RS_167._col0(Inner),Output:["_col1","_col3","_col5","_col6","_col7"] + Select Operator [SEL_165] (rows=1855 width=4) + Output:["_col0"] + Filter Operator [FIL_164] (rows=1855 width=12) + predicate:((hd_dep_count = 2) or (hd_vehicle_count = 1)) + TableScan [TS_14] (rows=7200 width=12) + default@household_demographics,household_demographics,Tbl:COMPLETE,Col:COMPLETE,Output:["hd_demo_sk","hd_dep_count","hd_vehicle_count"] + <-Reducer 10 [SIMPLE_EDGE] + SHUFFLE [RS_25] + PartitionCols:_col2 + Merge Join Operator [MERGEJOIN_140] (rows=32526589 width=90) + Conds:RS_22._col4=RS_163._col0(Inner),Output:["_col1","_col2","_col3","_col5","_col6","_col7"] <-Map 14 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_167] + SHUFFLE [RS_163] PartitionCols:_col0 - Select Operator [SEL_166] (rows=1855 width=4) + Select Operator [SEL_162] (rows=35 width=4) Output:["_col0"] - Filter Operator [FIL_165] (rows=1855 width=12) - predicate:((hd_dep_count = 2) or (hd_vehicle_count = 1)) - TableScan [TS_12] (rows=7200 width=12) - default@household_demographics,household_demographics,Tbl:COMPLETE,Col:COMPLETE,Output:["hd_demo_sk","hd_dep_count","hd_vehicle_count"] - <-Reducer 7 [SIMPLE_EDGE] - SHUFFLE [RS_23] - PartitionCols:_col2 - Merge Join Operator [MERGEJOIN_143] (rows=32526589 width=90) - Conds:RS_20._col4=RS_164._col0(Inner),Output:["_col1","_col2","_col3","_col5","_col6","_col7"] - <-Map 13 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_164] + Filter Operator [FIL_161] (rows=35 width=97) + predicate:(s_city) IN ('Cedar Grove', 'Wildwood', 'Union', 'Salem', 'Highland Park') + TableScan [TS_11] (rows=1704 width=97) + default@store,store,Tbl:COMPLETE,Col:COMPLETE,Output:["s_store_sk","s_city"] + <-Reducer 9 [SIMPLE_EDGE] + SHUFFLE [RS_22] + PartitionCols:_col4 + Merge Join Operator [MERGEJOIN_139] (rows=196204013 width=218) + Conds:RS_160._col0=RS_152._col0(Inner),Output:["_col1","_col2","_col3","_col4","_col5","_col6","_col7"] + <-Map 12 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_152] PartitionCols:_col0 - Select Operator [SEL_163] (rows=35 width=4) + Select Operator [SEL_151] (rows=783 width=4) Output:["_col0"] - Filter Operator [FIL_162] (rows=35 width=97) - predicate:(s_city) IN ('Cedar Grove', 'Wildwood', 'Union', 'Salem', 'Highland Park') - TableScan [TS_9] (rows=1704 width=97) - default@store,store,Tbl:COMPLETE,Col:COMPLETE,Output:["s_store_sk","s_city"] - <-Reducer 6 [SIMPLE_EDGE] - SHUFFLE [RS_20] - PartitionCols:_col4 - Merge Join Operator [MERGEJOIN_142] (rows=196204013 width=218) - Conds:RS_161._col0=RS_153._col0(Inner),Output:["_col1","_col2","_col3","_col4","_col5","_col6","_col7"] - <-Map 11 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_153] - PartitionCols:_col0 - Select Operator [SEL_152] (rows=783 width=4) - Output:["_col0"] - Filter Operator [FIL_151] (rows=783 width=12) - predicate:((d_dow) IN (6, 0) and (d_year) IN (1998, 1999, 2000)) - TableScan [TS_6] (rows=73049 width=12) - default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year","d_dow"] - <-Map 5 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_161] - PartitionCols:_col0 - Select Operator [SEL_160] (rows=457565061 width=237) - Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7"] - Filter Operator [FIL_159] (rows=457565061 width=237) - predicate:((ss_sold_date_sk BETWEEN DynamicValue(RS_18_date_dim_d_date_sk_min) AND DynamicValue(RS_18_date_dim_d_date_sk_max) and in_bloom_filter(ss_sold_date_sk, DynamicValue(RS_18_date_dim_d_date_sk_bloom_filter))) and ss_addr_sk is not null and ss_customer_sk is not null and ss_hdemo_sk is not null and ss_sold_date_sk is not null and ss_store_sk is not null) - TableScan [TS_3] (rows=575995635 width=237) - default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_customer_sk","ss_hdemo_sk","ss_addr_sk","ss_store_sk","ss_ticket_number","ss_coupon_amt","ss_net_profit"] - <-Reducer 12 [BROADCAST_EDGE] vectorized - BROADCAST [RS_158] - Group By Operator [GBY_157] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] - <-Map 11 [CUSTOM_SIMPLE_EDGE] vectorized - SHUFFLE [RS_156] - Group By Operator [GBY_155] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] - Select Operator [SEL_154] (rows=783 width=4) - Output:["_col0"] - Please refer to the previous Select Operator [SEL_152] + Filter Operator [FIL_150] (rows=783 width=12) + predicate:((d_dow) IN (6, 0) and (d_year) IN (1998, 1999, 2000)) + TableScan [TS_8] (rows=73049 width=12) + default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year","d_dow"] + <-Map 8 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_160] + PartitionCols:_col0 + Select Operator [SEL_159] (rows=457565061 width=237) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7"] + Filter Operator [FIL_158] (rows=457565061 width=237) + predicate:((ss_sold_date_sk BETWEEN DynamicValue(RS_20_date_dim_d_date_sk_min) AND DynamicValue(RS_20_date_dim_d_date_sk_max) and in_bloom_filter(ss_sold_date_sk, DynamicValue(RS_20_date_dim_d_date_sk_bloom_filter))) and ss_addr_sk is not null and ss_customer_sk is not null and ss_hdemo_sk is not null and ss_sold_date_sk is not null and ss_store_sk is not null) + TableScan [TS_5] (rows=575995635 width=237) + default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_customer_sk","ss_hdemo_sk","ss_addr_sk","ss_store_sk","ss_ticket_number","ss_coupon_amt","ss_net_profit"] + <-Reducer 13 [BROADCAST_EDGE] vectorized + BROADCAST [RS_157] + Group By Operator [GBY_156] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] + <-Map 12 [CUSTOM_SIMPLE_EDGE] vectorized + SHUFFLE [RS_155] + Group By Operator [GBY_154] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] + Select Operator [SEL_153] (rows=783 width=4) + Output:["_col0"] + Please refer to the previous Select Operator [SEL_151] diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query53.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query53.q.out index a13d0f9c09..a569e0473c 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query53.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query53.q.out @@ -87,7 +87,7 @@ Stage-0 Select Operator [SEL_24] (rows=25 width=228) Output:["_col0","_col1","_col2"] Filter Operator [FIL_36] (rows=25 width=228) - predicate:CASE WHEN ((avg_window_0 > 0)) THEN (((abs((_col2 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (null) END + predicate:CASE WHEN ((avg_window_0 > 0)) THEN (((abs((_col2 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (false) END Select Operator [SEL_23] (rows=50 width=116) Output:["avg_window_0","_col0","_col2"] PTF Operator [PTF_22] (rows=50 width=116) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query54.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query54.q.out index 8d10899c63..282103825a 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query54.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query54.q.out @@ -1,7 +1,7 @@ -Warning: Shuffle Join MERGEJOIN[269][tables = [$hdt$_0, $hdt$_1]] in Stage 'Reducer 2' is a cross product -Warning: Shuffle Join MERGEJOIN[278][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3, $hdt$_4, $hdt$_5]] in Stage 'Reducer 6' is a cross product -Warning: Shuffle Join MERGEJOIN[277][tables = [$hdt$_1, $hdt$_2]] in Stage 'Reducer 15' is a cross product -Warning: Shuffle Join MERGEJOIN[279][tables = [$hdt$_1, $hdt$_2, $hdt$_0]] in Stage 'Reducer 7' is a cross product +Warning: Shuffle Join MERGEJOIN[268][tables = [$hdt$_2, $hdt$_3]] in Stage 'Reducer 3' is a cross product +Warning: Shuffle Join MERGEJOIN[269][tables = [$hdt$_2, $hdt$_3, $hdt$_1]] in Stage 'Reducer 4' is a cross product +Warning: Shuffle Join MERGEJOIN[277][tables = [$hdt$_1, $hdt$_2]] in Stage 'Reducer 14' is a cross product +Warning: Shuffle Join MERGEJOIN[278][tables = [$hdt$_1, $hdt$_2, $hdt$_0]] in Stage 'Reducer 8' is a cross product PREHOOK: query: explain with my_customers as ( select distinct c_customer_sk @@ -133,277 +133,277 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### Plan optimized by CBO. Vertex dependency in root stage -Map 18 <- Reducer 26 (BROADCAST_EDGE), Union 19 (CONTAINS) -Map 24 <- Reducer 26 (BROADCAST_EDGE), Union 19 (CONTAINS) +Map 19 <- Reducer 27 (BROADCAST_EDGE), Union 20 (CONTAINS) +Map 25 <- Reducer 27 (BROADCAST_EDGE), Union 20 (CONTAINS) Reducer 10 <- Reducer 9 (SIMPLE_EDGE) -Reducer 12 <- Map 11 (SIMPLE_EDGE) -Reducer 13 <- Reducer 12 (CUSTOM_SIMPLE_EDGE) -Reducer 14 <- Map 11 (SIMPLE_EDGE) -Reducer 15 <- Reducer 14 (CUSTOM_SIMPLE_EDGE), Reducer 17 (CUSTOM_SIMPLE_EDGE) -Reducer 16 <- Map 11 (SIMPLE_EDGE) -Reducer 17 <- Reducer 16 (CUSTOM_SIMPLE_EDGE) -Reducer 2 <- Map 1 (CUSTOM_SIMPLE_EDGE), Reducer 13 (CUSTOM_SIMPLE_EDGE) -Reducer 20 <- Map 25 (SIMPLE_EDGE), Union 19 (SIMPLE_EDGE) -Reducer 21 <- Map 27 (SIMPLE_EDGE), Reducer 20 (SIMPLE_EDGE) +Reducer 11 <- Reducer 10 (SIMPLE_EDGE) +Reducer 12 <- Reducer 2 (CUSTOM_SIMPLE_EDGE) +Reducer 13 <- Map 1 (SIMPLE_EDGE) +Reducer 14 <- Reducer 13 (CUSTOM_SIMPLE_EDGE), Reducer 16 (CUSTOM_SIMPLE_EDGE) +Reducer 15 <- Map 1 (SIMPLE_EDGE) +Reducer 16 <- Reducer 15 (CUSTOM_SIMPLE_EDGE) +Reducer 2 <- Map 1 (SIMPLE_EDGE) +Reducer 21 <- Map 26 (SIMPLE_EDGE), Union 20 (SIMPLE_EDGE) Reducer 22 <- Map 28 (SIMPLE_EDGE), Reducer 21 (SIMPLE_EDGE) -Reducer 23 <- Reducer 22 (SIMPLE_EDGE) -Reducer 26 <- Map 25 (CUSTOM_SIMPLE_EDGE) -Reducer 3 <- Reducer 2 (SIMPLE_EDGE), Reducer 23 (SIMPLE_EDGE) +Reducer 23 <- Map 29 (SIMPLE_EDGE), Reducer 22 (SIMPLE_EDGE) +Reducer 24 <- Reducer 23 (SIMPLE_EDGE) +Reducer 27 <- Map 26 (CUSTOM_SIMPLE_EDGE) +Reducer 3 <- Reducer 12 (CUSTOM_SIMPLE_EDGE), Reducer 2 (CUSTOM_SIMPLE_EDGE) Reducer 31 <- Map 30 (SIMPLE_EDGE), Map 32 (SIMPLE_EDGE) -Reducer 4 <- Map 29 (SIMPLE_EDGE), Reducer 3 (SIMPLE_EDGE) -Reducer 5 <- Reducer 31 (SIMPLE_EDGE), Reducer 4 (SIMPLE_EDGE) -Reducer 6 <- Reducer 12 (CUSTOM_SIMPLE_EDGE), Reducer 5 (CUSTOM_SIMPLE_EDGE) -Reducer 7 <- Reducer 15 (CUSTOM_SIMPLE_EDGE), Reducer 6 (CUSTOM_SIMPLE_EDGE) -Reducer 8 <- Reducer 7 (SIMPLE_EDGE) +Reducer 4 <- Map 17 (CUSTOM_SIMPLE_EDGE), Reducer 3 (CUSTOM_SIMPLE_EDGE) +Reducer 5 <- Map 18 (SIMPLE_EDGE), Reducer 4 (SIMPLE_EDGE) +Reducer 6 <- Reducer 24 (SIMPLE_EDGE), Reducer 5 (SIMPLE_EDGE) +Reducer 7 <- Reducer 31 (SIMPLE_EDGE), Reducer 6 (SIMPLE_EDGE) +Reducer 8 <- Reducer 14 (CUSTOM_SIMPLE_EDGE), Reducer 7 (CUSTOM_SIMPLE_EDGE) Reducer 9 <- Reducer 8 (SIMPLE_EDGE) Stage-0 Fetch Operator limit:100 Stage-1 - Reducer 10 vectorized - File Output Operator [FS_353] - Limit [LIM_352] (rows=1 width=16) + Reducer 11 vectorized + File Output Operator [FS_352] + Limit [LIM_351] (rows=1 width=16) Number of rows:100 - Select Operator [SEL_351] (rows=1 width=16) + Select Operator [SEL_350] (rows=1 width=16) Output:["_col0","_col1","_col2"] - <-Reducer 9 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_350] - Select Operator [SEL_349] (rows=1 width=16) + <-Reducer 10 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_349] + Select Operator [SEL_348] (rows=1 width=16) Output:["_col0","_col1","_col2"] - Group By Operator [GBY_348] (rows=1 width=12) + Group By Operator [GBY_347] (rows=1 width=12) Output:["_col0","_col1"],aggregations:["count(VALUE._col0)"],keys:KEY._col0 - <-Reducer 8 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_347] + <-Reducer 9 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_346] PartitionCols:_col0 - Group By Operator [GBY_346] (rows=1 width=12) + Group By Operator [GBY_345] (rows=1 width=12) Output:["_col0","_col1"],aggregations:["count()"],keys:_col0 - Select Operator [SEL_345] (rows=1 width=116) + Select Operator [SEL_344] (rows=1 width=116) Output:["_col0"] - Group By Operator [GBY_344] (rows=1 width=116) + Group By Operator [GBY_343] (rows=1 width=116) Output:["_col0","_col1"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0 - <-Reducer 7 [SIMPLE_EDGE] + <-Reducer 8 [SIMPLE_EDGE] SHUFFLE [RS_118] PartitionCols:_col0 - Group By Operator [GBY_117] (rows=312 width=116) + Group By Operator [GBY_117] (rows=13 width=116) Output:["_col0","_col1"],aggregations:["sum(_col1)"],keys:_col0 - Select Operator [SEL_116] (rows=624257222 width=127) + Select Operator [SEL_116] (rows=24970288 width=123) Output:["_col0","_col1"] - Filter Operator [FIL_115] (rows=624257222 width=127) + Filter Operator [FIL_115] (rows=24970288 width=123) predicate:_col2 BETWEEN _col3 AND _col4 - Select Operator [SEL_114] (rows=5618315000 width=127) + Select Operator [SEL_114] (rows=224732600 width=123) Output:["_col0","_col1","_col2","_col3","_col4"] - Merge Join Operator [MERGEJOIN_279] (rows=5618315000 width=127) + Merge Join Operator [MERGEJOIN_278] (rows=224732600 width=123) Conds:(Inner),Output:["_col0","_col2","_col6","_col13","_col15"] - <-Reducer 15 [CUSTOM_SIMPLE_EDGE] + <-Reducer 14 [CUSTOM_SIMPLE_EDGE] PARTITION_ONLY_SHUFFLE [RS_111] Merge Join Operator [MERGEJOIN_277] (rows=25 width=4) Conds:(Right Outer),Output:["_col0"] - <-Reducer 14 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_335] - Group By Operator [GBY_334] (rows=25 width=4) + <-Reducer 13 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_334] + Group By Operator [GBY_333] (rows=25 width=4) Output:["_col0"],keys:KEY._col0 - <-Map 11 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_301] + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_297] PartitionCols:_col0 - Group By Operator [GBY_298] (rows=25 width=4) + Group By Operator [GBY_294] (rows=25 width=4) Output:["_col0"],keys:_col0 - Select Operator [SEL_295] (rows=50 width=12) + Select Operator [SEL_291] (rows=50 width=12) Output:["_col0"] - Filter Operator [FIL_293] (rows=50 width=12) + Filter Operator [FIL_289] (rows=50 width=12) predicate:((d_moy = 3) and (d_year = 1999)) - TableScan [TS_26] (rows=73049 width=12) + TableScan [TS_23] (rows=73049 width=12) default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_month_seq","d_year","d_moy"] - <-Reducer 17 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_343] - Select Operator [SEL_342] (rows=1 width=8) - Filter Operator [FIL_341] (rows=1 width=8) + <-Reducer 16 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_342] + Select Operator [SEL_341] (rows=1 width=8) + Filter Operator [FIL_340] (rows=1 width=8) predicate:(sq_count_check(_col0) <= 1) - Group By Operator [GBY_340] (rows=1 width=8) + Group By Operator [GBY_339] (rows=1 width=8) Output:["_col0"],aggregations:["count(VALUE._col0)"] - <-Reducer 16 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_339] - Group By Operator [GBY_338] (rows=1 width=8) + <-Reducer 15 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_338] + Group By Operator [GBY_337] (rows=1 width=8) Output:["_col0"],aggregations:["count()"] - Select Operator [SEL_337] (rows=25 width=4) - Group By Operator [GBY_336] (rows=25 width=4) + Select Operator [SEL_336] (rows=25 width=4) + Group By Operator [GBY_335] (rows=25 width=4) Output:["_col0"],keys:KEY._col0 - <-Map 11 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_302] + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_298] PartitionCols:_col0 - Group By Operator [GBY_299] (rows=25 width=4) + Group By Operator [GBY_295] (rows=25 width=4) Output:["_col0"],keys:_col0 - Select Operator [SEL_296] (rows=50 width=12) + Select Operator [SEL_292] (rows=50 width=12) Output:["_col0"] - Please refer to the previous Filter Operator [FIL_293] - <-Reducer 6 [CUSTOM_SIMPLE_EDGE] + Please refer to the previous Filter Operator [FIL_289] + <-Reducer 7 [CUSTOM_SIMPLE_EDGE] PARTITION_ONLY_SHUFFLE [RS_112] - Select Operator [SEL_107] (rows=224732600 width=119) + Select Operator [SEL_107] (rows=8989304 width=12) Output:["_col0","_col4","_col11","_col13"] - Merge Join Operator [MERGEJOIN_278] (rows=224732600 width=119) - Conds:(Left Outer),Output:["_col2","_col4","_col7","_col13"] - <-Reducer 12 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_305] - Group By Operator [GBY_303] (rows=25 width=4) - Output:["_col0"],keys:KEY._col0 - <-Map 11 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_300] + Merge Join Operator [MERGEJOIN_276] (rows=8989304 width=12) + Conds:RS_104._col8=RS_105._col0(Inner),Output:["_col0","_col3","_col6","_col7"] + <-Reducer 31 [SIMPLE_EDGE] + SHUFFLE [RS_105] + PartitionCols:_col0 + Merge Join Operator [MERGEJOIN_274] (rows=39720279 width=4) + Conds:RS_329._col1, _col2=RS_332._col0, _col1(Inner),Output:["_col0"] + <-Map 30 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_329] + PartitionCols:_col1, _col2 + Select Operator [SEL_328] (rows=40000000 width=188) + Output:["_col0","_col1","_col2"] + Filter Operator [FIL_327] (rows=40000000 width=188) + predicate:(ca_county is not null and ca_state is not null) + TableScan [TS_82] (rows=40000000 width=188) + default@customer_address,customer_address,Tbl:COMPLETE,Col:COMPLETE,Output:["ca_address_sk","ca_county","ca_state"] + <-Map 32 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_332] + PartitionCols:_col0, _col1 + Select Operator [SEL_331] (rows=1704 width=184) + Output:["_col0","_col1"] + Filter Operator [FIL_330] (rows=1704 width=184) + predicate:(s_county is not null and s_state is not null) + TableScan [TS_85] (rows=1704 width=184) + default@store,store,Tbl:COMPLETE,Col:COMPLETE,Output:["s_county","s_state"] + <-Reducer 6 [SIMPLE_EDGE] + SHUFFLE [RS_104] + PartitionCols:_col8 + Merge Join Operator [MERGEJOIN_275] (rows=8989304 width=16) + Conds:RS_101._col5=RS_326._col0(Inner),Output:["_col0","_col3","_col6","_col7","_col8"] + <-Reducer 24 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_326] PartitionCols:_col0 - Group By Operator [GBY_297] (rows=25 width=4) - Output:["_col0"],keys:_col0 - Select Operator [SEL_294] (rows=50 width=12) - Output:["_col0"] - Please refer to the previous Filter Operator [FIL_293] - <-Reducer 5 [CUSTOM_SIMPLE_EDGE] - PARTITION_ONLY_SHUFFLE [RS_104] - Merge Join Operator [MERGEJOIN_276] (rows=8989304 width=8) - Conds:RS_101._col5=RS_102._col0(Inner),Output:["_col2","_col4","_col7"] - <-Reducer 31 [SIMPLE_EDGE] - SHUFFLE [RS_102] - PartitionCols:_col0 - Merge Join Operator [MERGEJOIN_275] (rows=39720279 width=4) - Conds:RS_330._col1, _col2=RS_333._col0, _col1(Inner),Output:["_col0"] - <-Map 30 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_330] - PartitionCols:_col1, _col2 - Select Operator [SEL_329] (rows=40000000 width=188) - Output:["_col0","_col1","_col2"] - Filter Operator [FIL_328] (rows=40000000 width=188) - predicate:(ca_county is not null and ca_state is not null) - TableScan [TS_74] (rows=40000000 width=188) - default@customer_address,customer_address,Tbl:COMPLETE,Col:COMPLETE,Output:["ca_address_sk","ca_county","ca_state"] - <-Map 32 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_333] + Group By Operator [GBY_325] (rows=55046 width=8) + Output:["_col0","_col1"],keys:KEY._col0, KEY._col1 + <-Reducer 23 [SIMPLE_EDGE] + SHUFFLE [RS_79] PartitionCols:_col0, _col1 - Select Operator [SEL_332] (rows=1704 width=184) - Output:["_col0","_col1"] - Filter Operator [FIL_331] (rows=1704 width=184) - predicate:(s_county is not null and s_state is not null) - TableScan [TS_77] (rows=1704 width=184) - default@store,store,Tbl:COMPLETE,Col:COMPLETE,Output:["s_county","s_state"] - <-Reducer 4 [SIMPLE_EDGE] + Group By Operator [GBY_78] (rows=55046 width=8) + Output:["_col0","_col1"],keys:_col5, _col6 + Merge Join Operator [MERGEJOIN_273] (rows=110092 width=8) + Conds:RS_74._col1=RS_324._col0(Inner),Output:["_col5","_col6"] + <-Map 29 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_324] + PartitionCols:_col0 + Select Operator [SEL_323] (rows=80000000 width=8) + Output:["_col0","_col1"] + Filter Operator [FIL_322] (rows=80000000 width=8) + predicate:c_current_addr_sk is not null + TableScan [TS_65] (rows=80000000 width=8) + default@customer,customer,Tbl:COMPLETE,Col:COMPLETE,Output:["c_customer_sk","c_current_addr_sk"] + <-Reducer 22 [SIMPLE_EDGE] + SHUFFLE [RS_74] + PartitionCols:_col1 + Merge Join Operator [MERGEJOIN_272] (rows=110092 width=0) + Conds:RS_71._col2=RS_321._col0(Inner),Output:["_col1"] + <-Map 28 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_321] + PartitionCols:_col0 + Select Operator [SEL_320] (rows=453 width=4) + Output:["_col0"] + Filter Operator [FIL_319] (rows=453 width=186) + predicate:((i_category = 'Jewelry') and (i_class = 'consignment')) + TableScan [TS_62] (rows=462000 width=186) + default@item,item,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_class","i_category"] + <-Reducer 21 [SIMPLE_EDGE] + SHUFFLE [RS_71] + PartitionCols:_col2 + Merge Join Operator [MERGEJOIN_271] (rows=11665117 width=7) + Conds:Union 20._col0=RS_315._col0(Inner),Output:["_col1","_col2"] + <-Map 26 [SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_315] + PartitionCols:_col0 + Select Operator [SEL_314] (rows=50 width=4) + Output:["_col0"] + Filter Operator [FIL_313] (rows=50 width=12) + predicate:((d_moy = 3) and (d_year = 1999)) + TableScan [TS_59] (rows=73049 width=12) + default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year","d_moy"] + <-Union 20 [SIMPLE_EDGE] + <-Map 19 [CONTAINS] vectorized + Reduce Output Operator [RS_358] + PartitionCols:_col0 + Select Operator [SEL_357] (rows=285117831 width=11) + Output:["_col0","_col1","_col2"] + Filter Operator [FIL_356] (rows=285117831 width=11) + predicate:((cs_sold_date_sk BETWEEN DynamicValue(RS_69_date_dim_d_date_sk_min) AND DynamicValue(RS_69_date_dim_d_date_sk_max) and in_bloom_filter(cs_sold_date_sk, DynamicValue(RS_69_date_dim_d_date_sk_bloom_filter))) and cs_bill_customer_sk is not null and cs_sold_date_sk is not null) + TableScan [TS_279] (rows=287989836 width=11) + Output:["cs_sold_date_sk","cs_bill_customer_sk","cs_item_sk"] + <-Reducer 27 [BROADCAST_EDGE] vectorized + BROADCAST [RS_354] + Group By Operator [GBY_353] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] + <-Map 26 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_318] + Group By Operator [GBY_317] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] + Select Operator [SEL_316] (rows=50 width=4) + Output:["_col0"] + Please refer to the previous Select Operator [SEL_314] + <-Map 25 [CONTAINS] vectorized + Reduce Output Operator [RS_361] + PartitionCols:_col0 + Select Operator [SEL_360] (rows=143930993 width=11) + Output:["_col0","_col1","_col2"] + Filter Operator [FIL_359] (rows=143930993 width=11) + predicate:((ws_sold_date_sk BETWEEN DynamicValue(RS_69_date_dim_d_date_sk_min) AND DynamicValue(RS_69_date_dim_d_date_sk_max) and in_bloom_filter(ws_sold_date_sk, DynamicValue(RS_69_date_dim_d_date_sk_bloom_filter))) and ws_bill_customer_sk is not null and ws_sold_date_sk is not null) + TableScan [TS_284] (rows=144002668 width=11) + Output:["ws_sold_date_sk","ws_item_sk","ws_bill_customer_sk"] + <-Reducer 27 [BROADCAST_EDGE] vectorized + BROADCAST [RS_355] + Please refer to the previous Group By Operator [GBY_353] + <-Reducer 5 [SIMPLE_EDGE] SHUFFLE [RS_101] PartitionCols:_col5 - Merge Join Operator [MERGEJOIN_274] (rows=8989304 width=12) - Conds:RS_98._col0=RS_327._col0(Inner),Output:["_col2","_col4","_col5","_col7"] - <-Map 29 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_327] + Merge Join Operator [MERGEJOIN_270] (rows=525327388 width=118) + Conds:RS_98._col2=RS_312._col0(Inner),Output:["_col0","_col3","_col5","_col6"] + <-Map 18 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_312] PartitionCols:_col0 - Select Operator [SEL_326] (rows=73049 width=8) - Output:["_col0","_col1"] - TableScan [TS_72] (rows=73049 width=8) - default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_month_seq"] - <-Reducer 3 [SIMPLE_EDGE] + Select Operator [SEL_311] (rows=525327388 width=114) + Output:["_col0","_col1","_col2"] + Filter Operator [FIL_310] (rows=525327388 width=114) + predicate:(ss_customer_sk is not null and ss_sold_date_sk is not null) + TableScan [TS_48] (rows=575995635 width=114) + default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_customer_sk","ss_ext_sales_price"] + <-Reducer 4 [SIMPLE_EDGE] SHUFFLE [RS_98] - PartitionCols:_col0 - Merge Join Operator [MERGEJOIN_273] (rows=8989304 width=8) - Conds:RS_95._col1=RS_325._col0(Inner),Output:["_col0","_col2","_col4","_col5"] - <-Reducer 2 [SIMPLE_EDGE] - SHUFFLE [RS_95] - PartitionCols:_col1 - Merge Join Operator [MERGEJOIN_269] (rows=525327388 width=114) - Conds:(Inner),Output:["_col0","_col1","_col2"] - <-Map 1 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_292] - Select Operator [SEL_291] (rows=525327388 width=114) - Output:["_col0","_col1","_col2"] - Filter Operator [FIL_290] (rows=525327388 width=114) - predicate:(ss_customer_sk is not null and ss_sold_date_sk is not null) - TableScan [TS_23] (rows=575995635 width=114) - default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_customer_sk","ss_ext_sales_price"] - <-Reducer 13 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_311] - Select Operator [SEL_310] (rows=1 width=8) - Filter Operator [FIL_309] (rows=1 width=8) + PartitionCols:_col2 + Merge Join Operator [MERGEJOIN_269] (rows=1826225 width=12) + Conds:(Inner),Output:["_col0","_col2","_col3"] + <-Map 17 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_309] + Select Operator [SEL_308] (rows=73049 width=8) + Output:["_col0","_col1"] + TableScan [TS_46] (rows=73049 width=8) + default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_month_seq"] + <-Reducer 3 [CUSTOM_SIMPLE_EDGE] + PARTITION_ONLY_SHUFFLE [RS_95] + Merge Join Operator [MERGEJOIN_268] (rows=25 width=4) + Conds:(Right Outer),Output:["_col0"] + <-Reducer 2 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_300] + Group By Operator [GBY_299] (rows=25 width=4) + Output:["_col0"],keys:KEY._col0 + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_296] + PartitionCols:_col0 + Group By Operator [GBY_293] (rows=25 width=4) + Output:["_col0"],keys:_col0 + Select Operator [SEL_290] (rows=50 width=12) + Output:["_col0"] + Please refer to the previous Filter Operator [FIL_289] + <-Reducer 12 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_307] + Select Operator [SEL_306] (rows=1 width=8) + Filter Operator [FIL_305] (rows=1 width=8) predicate:(sq_count_check(_col0) <= 1) - Group By Operator [GBY_308] (rows=1 width=8) + Group By Operator [GBY_304] (rows=1 width=8) Output:["_col0"],aggregations:["count(VALUE._col0)"] - <-Reducer 12 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_307] - Group By Operator [GBY_306] (rows=1 width=8) + <-Reducer 2 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_303] + Group By Operator [GBY_302] (rows=1 width=8) Output:["_col0"],aggregations:["count()"] - Select Operator [SEL_304] (rows=25 width=4) - Please refer to the previous Group By Operator [GBY_303] - <-Reducer 23 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_325] - PartitionCols:_col0 - Group By Operator [GBY_324] (rows=55046 width=8) - Output:["_col0","_col1"],keys:KEY._col0, KEY._col1 - <-Reducer 22 [SIMPLE_EDGE] - SHUFFLE [RS_69] - PartitionCols:_col0, _col1 - Group By Operator [GBY_68] (rows=55046 width=8) - Output:["_col0","_col1"],keys:_col5, _col6 - Merge Join Operator [MERGEJOIN_272] (rows=110092 width=8) - Conds:RS_64._col1=RS_323._col0(Inner),Output:["_col5","_col6"] - <-Map 28 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_323] - PartitionCols:_col0 - Select Operator [SEL_322] (rows=80000000 width=8) - Output:["_col0","_col1"] - Filter Operator [FIL_321] (rows=80000000 width=8) - predicate:c_current_addr_sk is not null - TableScan [TS_55] (rows=80000000 width=8) - default@customer,customer,Tbl:COMPLETE,Col:COMPLETE,Output:["c_customer_sk","c_current_addr_sk"] - <-Reducer 21 [SIMPLE_EDGE] - SHUFFLE [RS_64] - PartitionCols:_col1 - Merge Join Operator [MERGEJOIN_271] (rows=110092 width=0) - Conds:RS_61._col2=RS_320._col0(Inner),Output:["_col1"] - <-Map 27 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_320] - PartitionCols:_col0 - Select Operator [SEL_319] (rows=453 width=4) - Output:["_col0"] - Filter Operator [FIL_318] (rows=453 width=186) - predicate:((i_category = 'Jewelry') and (i_class = 'consignment')) - TableScan [TS_52] (rows=462000 width=186) - default@item,item,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_class","i_category"] - <-Reducer 20 [SIMPLE_EDGE] - SHUFFLE [RS_61] - PartitionCols:_col2 - Merge Join Operator [MERGEJOIN_270] (rows=11665117 width=7) - Conds:Union 19._col0=RS_314._col0(Inner),Output:["_col1","_col2"] - <-Map 25 [SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_314] - PartitionCols:_col0 - Select Operator [SEL_313] (rows=50 width=4) - Output:["_col0"] - Filter Operator [FIL_312] (rows=50 width=12) - predicate:((d_moy = 3) and (d_year = 1999)) - TableScan [TS_49] (rows=73049 width=12) - default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year","d_moy"] - <-Union 19 [SIMPLE_EDGE] - <-Map 18 [CONTAINS] vectorized - Reduce Output Operator [RS_359] - PartitionCols:_col0 - Select Operator [SEL_358] (rows=285117831 width=11) - Output:["_col0","_col1","_col2"] - Filter Operator [FIL_357] (rows=285117831 width=11) - predicate:((cs_sold_date_sk BETWEEN DynamicValue(RS_59_date_dim_d_date_sk_min) AND DynamicValue(RS_59_date_dim_d_date_sk_max) and in_bloom_filter(cs_sold_date_sk, DynamicValue(RS_59_date_dim_d_date_sk_bloom_filter))) and cs_bill_customer_sk is not null and cs_sold_date_sk is not null) - TableScan [TS_280] (rows=287989836 width=11) - Output:["cs_sold_date_sk","cs_bill_customer_sk","cs_item_sk"] - <-Reducer 26 [BROADCAST_EDGE] vectorized - BROADCAST [RS_355] - Group By Operator [GBY_354] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] - <-Map 25 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_317] - Group By Operator [GBY_316] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] - Select Operator [SEL_315] (rows=50 width=4) - Output:["_col0"] - Please refer to the previous Select Operator [SEL_313] - <-Map 24 [CONTAINS] vectorized - Reduce Output Operator [RS_362] - PartitionCols:_col0 - Select Operator [SEL_361] (rows=143930993 width=11) - Output:["_col0","_col1","_col2"] - Filter Operator [FIL_360] (rows=143930993 width=11) - predicate:((ws_sold_date_sk BETWEEN DynamicValue(RS_59_date_dim_d_date_sk_min) AND DynamicValue(RS_59_date_dim_d_date_sk_max) and in_bloom_filter(ws_sold_date_sk, DynamicValue(RS_59_date_dim_d_date_sk_bloom_filter))) and ws_bill_customer_sk is not null and ws_sold_date_sk is not null) - TableScan [TS_285] (rows=144002668 width=11) - Output:["ws_sold_date_sk","ws_item_sk","ws_bill_customer_sk"] - <-Reducer 26 [BROADCAST_EDGE] vectorized - BROADCAST [RS_356] - Please refer to the previous Group By Operator [GBY_354] + Select Operator [SEL_301] (rows=25 width=4) + Please refer to the previous Group By Operator [GBY_299] diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query6.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query6.q.out index 7aea119ac3..b124531e2c 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query6.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query6.q.out @@ -1,4 +1,4 @@ -Warning: Map Join MAPJOIN[170][bigTable=?] in task 'Map 11' is a cross product +Warning: Map Join MAPJOIN[168][bigTable=?] in task 'Map 1' is a cross product PREHOOK: query: explain select a.ca_state state, count(*) cnt from customer_address a @@ -64,174 +64,176 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### Plan optimized by CBO. Vertex dependency in root stage -Map 1 <- Reducer 3 (BROADCAST_EDGE) -Map 11 <- Reducer 5 (BROADCAST_EDGE) +Map 1 <- Reducer 9 (BROADCAST_EDGE) +Map 12 <- Reducer 10 (BROADCAST_EDGE) +Map 13 <- Map 12 (BROADCAST_EDGE), Reducer 15 (BROADCAST_EDGE) Map 14 <- Reducer 17 (BROADCAST_EDGE) -Map 6 <- Map 1 (BROADCAST_EDGE), Reducer 15 (BROADCAST_EDGE) -Reducer 10 <- Reducer 9 (SIMPLE_EDGE) -Reducer 12 <- Map 11 (SIMPLE_EDGE), Map 13 (SIMPLE_EDGE) +Reducer 10 <- Map 7 (SIMPLE_EDGE) Reducer 15 <- Map 14 (CUSTOM_SIMPLE_EDGE) Reducer 17 <- Map 16 (SIMPLE_EDGE) -Reducer 3 <- Map 2 (SIMPLE_EDGE) -Reducer 4 <- Map 2 (SIMPLE_EDGE) -Reducer 5 <- Reducer 4 (CUSTOM_SIMPLE_EDGE) -Reducer 7 <- Map 6 (SIMPLE_EDGE), Reducer 12 (SIMPLE_EDGE) -Reducer 8 <- Map 14 (SIMPLE_EDGE), Reducer 7 (SIMPLE_EDGE) -Reducer 9 <- Reducer 8 (SIMPLE_EDGE) +Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 11 (SIMPLE_EDGE) +Reducer 3 <- Map 13 (SIMPLE_EDGE), Reducer 2 (SIMPLE_EDGE) +Reducer 4 <- Map 14 (SIMPLE_EDGE), Reducer 3 (SIMPLE_EDGE) +Reducer 5 <- Reducer 4 (SIMPLE_EDGE) +Reducer 6 <- Reducer 5 (SIMPLE_EDGE) +Reducer 8 <- Map 7 (SIMPLE_EDGE) +Reducer 9 <- Reducer 8 (CUSTOM_SIMPLE_EDGE) Stage-0 Fetch Operator limit:100 Stage-1 - Reducer 10 vectorized - File Output Operator [FS_233] - Limit [LIM_232] (rows=1 width=94) + Reducer 6 vectorized + File Output Operator [FS_234] + Limit [LIM_233] (rows=1 width=94) Number of rows:100 - Select Operator [SEL_231] (rows=1 width=94) + Select Operator [SEL_232] (rows=1 width=94) Output:["_col0","_col1"] - <-Reducer 9 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_230] - Filter Operator [FIL_229] (rows=1 width=94) + <-Reducer 5 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_231] + Filter Operator [FIL_230] (rows=1 width=94) predicate:(_col1 >= 10L) - Group By Operator [GBY_228] (rows=1 width=94) + Group By Operator [GBY_229] (rows=1 width=94) Output:["_col0","_col1"],aggregations:["count(VALUE._col0)"],keys:KEY._col0 - <-Reducer 8 [SIMPLE_EDGE] + <-Reducer 4 [SIMPLE_EDGE] SHUFFLE [RS_68] PartitionCols:_col0 Group By Operator [GBY_67] (rows=1 width=94) - Output:["_col0","_col1"],aggregations:["count()"],keys:_col10 + Output:["_col0","_col1"],aggregations:["count()"],keys:_col4 Merge Join Operator [MERGEJOIN_174] (rows=500 width=86) - Conds:RS_63._col4=RS_204._col0(Inner),Output:["_col10"] + Conds:RS_63._col6=RS_218._col0(Inner),Output:["_col4"] <-Map 14 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_204] + SHUFFLE [RS_218] PartitionCols:_col0 - Select Operator [SEL_203] (rows=154000 width=227) + Select Operator [SEL_217] (rows=154000 width=227) Output:["_col0"] - Filter Operator [FIL_202] (rows=154000 width=227) + Filter Operator [FIL_216] (rows=154000 width=227) predicate:(_col1 > _col4) - Map Join Operator [MAPJOIN_201] (rows=462000 width=227) - Conds:SEL_200._col2=RS_198._col0(Inner),HybridGraceHashJoin:true,Output:["_col0","_col1","_col4"] + Map Join Operator [MAPJOIN_215] (rows=462000 width=227) + Conds:SEL_214._col2=RS_212._col0(Inner),HybridGraceHashJoin:true,Output:["_col0","_col1","_col4"] <-Reducer 17 [BROADCAST_EDGE] vectorized - BROADCAST [RS_198] + BROADCAST [RS_212] PartitionCols:_col0 - Select Operator [SEL_197] (rows=10 width=202) + Select Operator [SEL_211] (rows=10 width=202) Output:["_col0","_col1"] - Group By Operator [GBY_196] (rows=10 width=210) + Group By Operator [GBY_210] (rows=10 width=210) Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)","count(VALUE._col1)"],keys:KEY._col0 <-Map 16 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_195] + SHUFFLE [RS_209] PartitionCols:_col0 - Group By Operator [GBY_194] (rows=10 width=210) + Group By Operator [GBY_208] (rows=10 width=210) Output:["_col0","_col1","_col2"],aggregations:["sum(i_current_price)","count(i_current_price)"],keys:i_category - Filter Operator [FIL_193] (rows=462000 width=201) + Filter Operator [FIL_207] (rows=462000 width=201) predicate:i_category is not null TableScan [TS_42] (rows=462000 width=201) default@item,j,Tbl:COMPLETE,Col:COMPLETE,Output:["i_current_price","i_category"] - <-Select Operator [SEL_200] (rows=462000 width=205) + <-Select Operator [SEL_214] (rows=462000 width=205) Output:["_col0","_col1","_col2"] - Filter Operator [FIL_199] (rows=462000 width=205) + Filter Operator [FIL_213] (rows=462000 width=205) predicate:i_category is not null TableScan [TS_39] (rows=462000 width=205) default@item,i,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_current_price","i_category"] - <-Reducer 7 [SIMPLE_EDGE] + <-Reducer 3 [SIMPLE_EDGE] SHUFFLE [RS_63] - PartitionCols:_col4 + PartitionCols:_col6 Merge Join Operator [MERGEJOIN_173] (rows=7192227 width=90) - Conds:RS_213._col5=RS_61._col0(Inner),Output:["_col4","_col10"] - <-Map 6 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_213] - PartitionCols:_col5 - Map Join Operator [MAPJOIN_212] (rows=7192227 width=4) - Conds:RS_192._col0=SEL_211._col0(Inner),HybridGraceHashJoin:true,Output:["_col4","_col5"] - <-Map 1 [BROADCAST_EDGE] vectorized - BROADCAST [RS_192] - PartitionCols:_col0 - Map Join Operator [MAPJOIN_191] (rows=660 width=4) - Conds:SEL_190._col1=RS_188._col0(Inner),HybridGraceHashJoin:true,Output:["_col0"] - <-Reducer 3 [BROADCAST_EDGE] vectorized - BROADCAST [RS_188] - PartitionCols:_col0 - Group By Operator [GBY_187] (rows=25 width=4) - Output:["_col0"],keys:KEY._col0 - <-Map 2 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_185] - PartitionCols:_col0 - Group By Operator [GBY_183] (rows=25 width=4) - Output:["_col0"],keys:d_month_seq - Select Operator [SEL_181] (rows=50 width=12) - Output:["d_month_seq"] - Filter Operator [FIL_179] (rows=50 width=12) - predicate:((d_moy = 2) and (d_year = 2000) and d_month_seq is not null) - TableScan [TS_3] (rows=73049 width=12) - default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_month_seq","d_year","d_moy"] - <-Select Operator [SEL_190] (rows=73049 width=8) - Output:["_col0","_col1"] - Filter Operator [FIL_189] (rows=73049 width=8) - predicate:d_month_seq is not null - TableScan [TS_0] (rows=73049 width=8) - default@date_dim,d,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_month_seq"] - <-Select Operator [SEL_211] (rows=525327388 width=11) - Output:["_col0","_col1","_col2"] - Filter Operator [FIL_210] (rows=525327388 width=11) - predicate:((ss_item_sk BETWEEN DynamicValue(RS_64_i_i_item_sk_min) AND DynamicValue(RS_64_i_i_item_sk_max) and in_bloom_filter(ss_item_sk, DynamicValue(RS_64_i_i_item_sk_bloom_filter))) and ss_customer_sk is not null and ss_sold_date_sk is not null) - TableScan [TS_10] (rows=575995635 width=11) - default@store_sales,s,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_item_sk","ss_customer_sk"] - <-Reducer 15 [BROADCAST_EDGE] vectorized - BROADCAST [RS_209] - Group By Operator [GBY_208] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] - <-Map 14 [CUSTOM_SIMPLE_EDGE] vectorized - SHUFFLE [RS_207] - Group By Operator [GBY_206] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] - Select Operator [SEL_205] (rows=154000 width=4) - Output:["_col0"] - Please refer to the previous Select Operator [SEL_203] - <-Reducer 12 [SIMPLE_EDGE] - SHUFFLE [RS_61] + Conds:RS_60._col0=RS_228._col2(Inner),Output:["_col4","_col6"] + <-Map 13 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_228] + PartitionCols:_col2 + Select Operator [SEL_227] (rows=7192227 width=4) + Output:["_col1","_col2"] + Map Join Operator [MAPJOIN_226] (rows=7192227 width=4) + Conds:RS_206._col0=SEL_225._col0(Inner),HybridGraceHashJoin:true,Output:["_col4","_col5"] + <-Map 12 [BROADCAST_EDGE] vectorized + BROADCAST [RS_206] + PartitionCols:_col0 + Map Join Operator [MAPJOIN_205] (rows=660 width=4) + Conds:SEL_204._col1=RS_202._col0(Inner),HybridGraceHashJoin:true,Output:["_col0"] + <-Reducer 10 [BROADCAST_EDGE] vectorized + BROADCAST [RS_202] + PartitionCols:_col0 + Group By Operator [GBY_201] (rows=25 width=4) + Output:["_col0"],keys:KEY._col0 + <-Map 7 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_186] + PartitionCols:_col0 + Group By Operator [GBY_184] (rows=25 width=4) + Output:["_col0"],keys:d_month_seq + Select Operator [SEL_182] (rows=50 width=12) + Output:["d_month_seq"] + Filter Operator [FIL_180] (rows=50 width=12) + predicate:((d_moy = 2) and (d_year = 2000) and d_month_seq is not null) + TableScan [TS_3] (rows=73049 width=12) + default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_month_seq","d_year","d_moy"] + <-Select Operator [SEL_204] (rows=73049 width=8) + Output:["_col0","_col1"] + Filter Operator [FIL_203] (rows=73049 width=8) + predicate:d_month_seq is not null + TableScan [TS_19] (rows=73049 width=8) + default@date_dim,d,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_month_seq"] + <-Select Operator [SEL_225] (rows=525327388 width=11) + Output:["_col0","_col1","_col2"] + Filter Operator [FIL_224] (rows=525327388 width=11) + predicate:((ss_item_sk BETWEEN DynamicValue(RS_64_i_i_item_sk_min) AND DynamicValue(RS_64_i_i_item_sk_max) and in_bloom_filter(ss_item_sk, DynamicValue(RS_64_i_i_item_sk_bloom_filter))) and ss_customer_sk is not null and ss_sold_date_sk is not null) + TableScan [TS_29] (rows=575995635 width=11) + default@store_sales,s,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_item_sk","ss_customer_sk"] + <-Reducer 15 [BROADCAST_EDGE] vectorized + BROADCAST [RS_223] + Group By Operator [GBY_222] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] + <-Map 14 [CUSTOM_SIMPLE_EDGE] vectorized + SHUFFLE [RS_221] + Group By Operator [GBY_220] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] + Select Operator [SEL_219] (rows=154000 width=4) + Output:["_col0"] + Please refer to the previous Select Operator [SEL_217] + <-Reducer 2 [SIMPLE_EDGE] + SHUFFLE [RS_60] PartitionCols:_col0 - Merge Join Operator [MERGEJOIN_171] (rows=80000000 width=90) - Conds:RS_225._col1=RS_227._col0(Inner),Output:["_col0","_col4"] - <-Map 11 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_225] + Merge Join Operator [MERGEJOIN_169] (rows=80000000 width=90) + Conds:RS_198._col1=RS_200._col0(Inner),Output:["_col0","_col4"] + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_198] PartitionCols:_col1 - Map Join Operator [MAPJOIN_224] (rows=80000000 width=8) + Map Join Operator [MAPJOIN_197] (rows=80000000 width=8) Conds:(Inner),Output:["_col0","_col1"] - <-Reducer 5 [BROADCAST_EDGE] vectorized - BROADCAST [RS_221] - Select Operator [SEL_220] (rows=1 width=8) - Filter Operator [FIL_219] (rows=1 width=8) + <-Reducer 9 [BROADCAST_EDGE] vectorized + BROADCAST [RS_194] + Select Operator [SEL_193] (rows=1 width=8) + Filter Operator [FIL_192] (rows=1 width=8) predicate:(sq_count_check(_col0) <= 1) - Group By Operator [GBY_218] (rows=1 width=8) + Group By Operator [GBY_191] (rows=1 width=8) Output:["_col0"],aggregations:["count(VALUE._col0)"] - <-Reducer 4 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_217] - Group By Operator [GBY_216] (rows=1 width=8) + <-Reducer 8 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_190] + Group By Operator [GBY_189] (rows=1 width=8) Output:["_col0"],aggregations:["count()"] - Select Operator [SEL_215] (rows=25 width=4) - Group By Operator [GBY_214] (rows=25 width=4) + Select Operator [SEL_188] (rows=25 width=4) + Group By Operator [GBY_187] (rows=25 width=4) Output:["_col0"],keys:KEY._col0 - <-Map 2 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_186] + <-Map 7 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_185] PartitionCols:_col0 - Group By Operator [GBY_184] (rows=25 width=4) + Group By Operator [GBY_183] (rows=25 width=4) Output:["_col0"],keys:d_month_seq - Select Operator [SEL_182] (rows=50 width=12) + Select Operator [SEL_181] (rows=50 width=12) Output:["d_month_seq"] - Filter Operator [FIL_180] (rows=50 width=12) + Filter Operator [FIL_179] (rows=50 width=12) predicate:((d_moy = 2) and (d_year = 2000)) Please refer to the previous TableScan [TS_3] - <-Select Operator [SEL_223] (rows=80000000 width=8) + <-Select Operator [SEL_196] (rows=80000000 width=8) Output:["_col0","_col1"] - Filter Operator [FIL_222] (rows=80000000 width=8) + Filter Operator [FIL_195] (rows=80000000 width=8) predicate:c_current_addr_sk is not null - TableScan [TS_13] (rows=80000000 width=8) + TableScan [TS_0] (rows=80000000 width=8) default@customer,c,Tbl:COMPLETE,Col:COMPLETE,Output:["c_customer_sk","c_current_addr_sk"] - <-Map 13 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_227] + <-Map 11 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_200] PartitionCols:_col0 - Select Operator [SEL_226] (rows=40000000 width=90) + Select Operator [SEL_199] (rows=40000000 width=90) Output:["_col0","_col1"] - TableScan [TS_30] (rows=40000000 width=90) + TableScan [TS_17] (rows=40000000 width=90) default@customer_address,a,Tbl:COMPLETE,Col:COMPLETE,Output:["ca_address_sk","ca_state"] diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query63.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query63.q.out index 5620b819fb..000aecd8ea 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query63.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query63.q.out @@ -89,7 +89,7 @@ Stage-0 Select Operator [SEL_24] (rows=65 width=228) Output:["_col0","_col1","_col2"] Filter Operator [FIL_36] (rows=65 width=228) - predicate:CASE WHEN ((avg_window_0 > 0)) THEN (((abs((_col2 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (null) END + predicate:CASE WHEN ((avg_window_0 > 0)) THEN (((abs((_col2 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (false) END Select Operator [SEL_23] (rows=130 width=116) Output:["avg_window_0","_col0","_col2"] PTF Operator [PTF_22] (rows=130 width=116) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query68.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query68.q.out index dd4ce4eb84..137139f87e 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query68.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query68.q.out @@ -97,134 +97,134 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### Plan optimized by CBO. Vertex dependency in root stage -Map 5 <- Reducer 12 (BROADCAST_EDGE) -Reducer 10 <- Reducer 9 (SIMPLE_EDGE) -Reducer 12 <- Map 11 (CUSTOM_SIMPLE_EDGE) -Reducer 2 <- Map 1 (SIMPLE_EDGE), Reducer 10 (SIMPLE_EDGE) -Reducer 3 <- Map 15 (SIMPLE_EDGE), Reducer 2 (SIMPLE_EDGE) +Map 8 <- Reducer 13 (BROADCAST_EDGE) +Reducer 10 <- Map 14 (SIMPLE_EDGE), Reducer 9 (SIMPLE_EDGE) +Reducer 11 <- Map 15 (SIMPLE_EDGE), Reducer 10 (SIMPLE_EDGE) +Reducer 13 <- Map 12 (CUSTOM_SIMPLE_EDGE) +Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 5 (SIMPLE_EDGE) +Reducer 3 <- Reducer 2 (SIMPLE_EDGE), Reducer 7 (SIMPLE_EDGE) Reducer 4 <- Reducer 3 (SIMPLE_EDGE) -Reducer 6 <- Map 11 (SIMPLE_EDGE), Map 5 (SIMPLE_EDGE) -Reducer 7 <- Map 13 (SIMPLE_EDGE), Reducer 6 (SIMPLE_EDGE) -Reducer 8 <- Map 14 (SIMPLE_EDGE), Reducer 7 (SIMPLE_EDGE) -Reducer 9 <- Map 15 (SIMPLE_EDGE), Reducer 8 (SIMPLE_EDGE) +Reducer 6 <- Map 5 (SIMPLE_EDGE), Reducer 11 (SIMPLE_EDGE) +Reducer 7 <- Reducer 6 (SIMPLE_EDGE) +Reducer 9 <- Map 12 (SIMPLE_EDGE), Map 8 (SIMPLE_EDGE) Stage-0 Fetch Operator limit:100 Stage-1 Reducer 4 vectorized - File Output Operator [FS_176] - Limit [LIM_175] (rows=100 width=706) + File Output Operator [FS_172] + Limit [LIM_171] (rows=100 width=706) Number of rows:100 - Select Operator [SEL_174] (rows=727776 width=706) + Select Operator [SEL_170] (rows=727776 width=706) Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7"] <-Reducer 3 [SIMPLE_EDGE] SHUFFLE [RS_44] Select Operator [SEL_43] (rows=727776 width=706) Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7"] Filter Operator [FIL_42] (rows=727776 width=706) - predicate:(_col11 <> _col6) - Merge Join Operator [MERGEJOIN_147] (rows=727776 width=706) - Conds:RS_39._col1=RS_169._col0(Inner),Output:["_col2","_col3","_col4","_col6","_col7","_col8","_col9","_col11"] - <-Map 15 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_169] - PartitionCols:_col0 - Select Operator [SEL_168] (rows=40000000 width=97) - Output:["_col0","_col1"] - TableScan [TS_34] (rows=40000000 width=97) - default@customer_address,current_addr,Tbl:COMPLETE,Col:COMPLETE,Output:["ca_address_sk","ca_city"] + predicate:(_col5 <> _col8) + Merge Join Operator [MERGEJOIN_143] (rows=727776 width=706) + Conds:RS_39._col0=RS_169._col1(Inner),Output:["_col2","_col3","_col5","_col6","_col8","_col9","_col10","_col11"] <-Reducer 2 [SIMPLE_EDGE] SHUFFLE [RS_39] - PartitionCols:_col1 - Merge Join Operator [MERGEJOIN_146] (rows=727776 width=617) - Conds:RS_150._col0=RS_173._col1(Inner),Output:["_col1","_col2","_col3","_col4","_col6","_col7","_col8","_col9"] - <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_150] + PartitionCols:_col0 + Merge Join Operator [MERGEJOIN_138] (rows=80000000 width=277) + Conds:RS_146._col1=RS_148._col0(Inner),Output:["_col0","_col2","_col3","_col5"] + <-Map 5 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_148] PartitionCols:_col0 - Select Operator [SEL_149] (rows=80000000 width=188) + Select Operator [SEL_147] (rows=40000000 width=97) + Output:["_col0","_col1"] + TableScan [TS_3] (rows=40000000 width=97) + default@customer_address,current_addr,Tbl:COMPLETE,Col:COMPLETE,Output:["ca_address_sk","ca_city"] + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_146] + PartitionCols:_col1 + Select Operator [SEL_145] (rows=80000000 width=188) Output:["_col0","_col1","_col2","_col3"] - Filter Operator [FIL_148] (rows=80000000 width=188) + Filter Operator [FIL_144] (rows=80000000 width=188) predicate:c_current_addr_sk is not null TableScan [TS_0] (rows=80000000 width=188) default@customer,customer,Tbl:COMPLETE,Col:COMPLETE,Output:["c_customer_sk","c_current_addr_sk","c_first_name","c_last_name"] - <-Reducer 10 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_173] - PartitionCols:_col1 - Select Operator [SEL_172] (rows=727776 width=433) - Output:["_col0","_col1","_col2","_col3","_col4","_col5"] - Group By Operator [GBY_171] (rows=727776 width=433) - Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3 - <-Reducer 9 [SIMPLE_EDGE] - SHUFFLE [RS_31] - PartitionCols:_col0, _col1, _col2, _col3 - Group By Operator [GBY_30] (rows=727776 width=433) - Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"],aggregations:["sum(_col6)","sum(_col7)","sum(_col8)"],keys:_col1, _col13, _col3, _col5 - Merge Join Operator [MERGEJOIN_145] (rows=727776 width=97) - Conds:RS_26._col3=RS_170._col0(Inner),Output:["_col1","_col3","_col5","_col6","_col7","_col8","_col13"] + <-Reducer 7 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_169] + PartitionCols:_col1 + Select Operator [SEL_168] (rows=727776 width=433) + Output:["_col0","_col1","_col2","_col3","_col4","_col5"] + Group By Operator [GBY_167] (rows=727776 width=433) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)"],keys:KEY._col0, KEY._col1, KEY._col2, KEY._col3 + <-Reducer 6 [SIMPLE_EDGE] + SHUFFLE [RS_33] + PartitionCols:_col0, _col1, _col2, _col3 + Group By Operator [GBY_32] (rows=727776 width=433) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"],aggregations:["sum(_col6)","sum(_col7)","sum(_col8)"],keys:_col1, _col13, _col3, _col5 + Merge Join Operator [MERGEJOIN_142] (rows=727776 width=97) + Conds:RS_28._col3=RS_149._col0(Inner),Output:["_col1","_col3","_col5","_col6","_col7","_col8","_col13"] + <-Map 5 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_149] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_147] + <-Reducer 11 [SIMPLE_EDGE] + SHUFFLE [RS_28] + PartitionCols:_col3 + Merge Join Operator [MERGEJOIN_141] (rows=727776 width=4) + Conds:RS_25._col2=RS_166._col0(Inner),Output:["_col1","_col3","_col5","_col6","_col7","_col8"] <-Map 15 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_170] + SHUFFLE [RS_166] PartitionCols:_col0 - Please refer to the previous Select Operator [SEL_168] - <-Reducer 8 [SIMPLE_EDGE] - SHUFFLE [RS_26] - PartitionCols:_col3 - Merge Join Operator [MERGEJOIN_144] (rows=727776 width=4) - Conds:RS_23._col2=RS_167._col0(Inner),Output:["_col1","_col3","_col5","_col6","_col7","_col8"] + Select Operator [SEL_165] (rows=1855 width=4) + Output:["_col0"] + Filter Operator [FIL_164] (rows=1855 width=12) + predicate:((hd_dep_count = 2) or (hd_vehicle_count = 1)) + TableScan [TS_14] (rows=7200 width=12) + default@household_demographics,household_demographics,Tbl:COMPLETE,Col:COMPLETE,Output:["hd_demo_sk","hd_dep_count","hd_vehicle_count"] + <-Reducer 10 [SIMPLE_EDGE] + SHUFFLE [RS_25] + PartitionCols:_col2 + Merge Join Operator [MERGEJOIN_140] (rows=2824787 width=4) + Conds:RS_22._col4=RS_163._col0(Inner),Output:["_col1","_col2","_col3","_col5","_col6","_col7","_col8"] <-Map 14 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_167] + SHUFFLE [RS_163] PartitionCols:_col0 - Select Operator [SEL_166] (rows=1855 width=4) + Select Operator [SEL_162] (rows=14 width=4) Output:["_col0"] - Filter Operator [FIL_165] (rows=1855 width=12) - predicate:((hd_dep_count = 2) or (hd_vehicle_count = 1)) - TableScan [TS_12] (rows=7200 width=12) - default@household_demographics,household_demographics,Tbl:COMPLETE,Col:COMPLETE,Output:["hd_demo_sk","hd_dep_count","hd_vehicle_count"] - <-Reducer 7 [SIMPLE_EDGE] - SHUFFLE [RS_23] - PartitionCols:_col2 - Merge Join Operator [MERGEJOIN_143] (rows=2824787 width=4) - Conds:RS_20._col4=RS_164._col0(Inner),Output:["_col1","_col2","_col3","_col5","_col6","_col7","_col8"] - <-Map 13 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_164] + Filter Operator [FIL_161] (rows=14 width=97) + predicate:(s_city) IN ('Cedar Grove', 'Wildwood') + TableScan [TS_11] (rows=1704 width=97) + default@store,store,Tbl:COMPLETE,Col:COMPLETE,Output:["s_store_sk","s_city"] + <-Reducer 9 [SIMPLE_EDGE] + SHUFFLE [RS_22] + PartitionCols:_col4 + Merge Join Operator [MERGEJOIN_139] (rows=42598570 width=185) + Conds:RS_160._col0=RS_152._col0(Inner),Output:["_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8"] + <-Map 12 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_152] PartitionCols:_col0 - Select Operator [SEL_163] (rows=14 width=4) + Select Operator [SEL_151] (rows=170 width=4) Output:["_col0"] - Filter Operator [FIL_162] (rows=14 width=97) - predicate:(s_city) IN ('Cedar Grove', 'Wildwood') - TableScan [TS_9] (rows=1704 width=97) - default@store,store,Tbl:COMPLETE,Col:COMPLETE,Output:["s_store_sk","s_city"] - <-Reducer 6 [SIMPLE_EDGE] - SHUFFLE [RS_20] - PartitionCols:_col4 - Merge Join Operator [MERGEJOIN_142] (rows=42598570 width=185) - Conds:RS_161._col0=RS_153._col0(Inner),Output:["_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8"] - <-Map 11 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_153] - PartitionCols:_col0 - Select Operator [SEL_152] (rows=170 width=4) - Output:["_col0"] - Filter Operator [FIL_151] (rows=170 width=12) - predicate:((d_year) IN (1998, 1999, 2000) and d_dom BETWEEN 1 AND 2) - TableScan [TS_6] (rows=73049 width=12) - default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year","d_dom"] - <-Map 5 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_161] - PartitionCols:_col0 - Select Operator [SEL_160] (rows=457565061 width=343) - Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8"] - Filter Operator [FIL_159] (rows=457565061 width=343) - predicate:((ss_sold_date_sk BETWEEN DynamicValue(RS_18_date_dim_d_date_sk_min) AND DynamicValue(RS_18_date_dim_d_date_sk_max) and in_bloom_filter(ss_sold_date_sk, DynamicValue(RS_18_date_dim_d_date_sk_bloom_filter))) and ss_addr_sk is not null and ss_customer_sk is not null and ss_hdemo_sk is not null and ss_sold_date_sk is not null and ss_store_sk is not null) - TableScan [TS_3] (rows=575995635 width=343) - default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_customer_sk","ss_hdemo_sk","ss_addr_sk","ss_store_sk","ss_ticket_number","ss_ext_sales_price","ss_ext_list_price","ss_ext_tax"] - <-Reducer 12 [BROADCAST_EDGE] vectorized - BROADCAST [RS_158] - Group By Operator [GBY_157] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] - <-Map 11 [CUSTOM_SIMPLE_EDGE] vectorized - SHUFFLE [RS_156] - Group By Operator [GBY_155] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] - Select Operator [SEL_154] (rows=170 width=4) - Output:["_col0"] - Please refer to the previous Select Operator [SEL_152] + Filter Operator [FIL_150] (rows=170 width=12) + predicate:((d_year) IN (1998, 1999, 2000) and d_dom BETWEEN 1 AND 2) + TableScan [TS_8] (rows=73049 width=12) + default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year","d_dom"] + <-Map 8 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_160] + PartitionCols:_col0 + Select Operator [SEL_159] (rows=457565061 width=343) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8"] + Filter Operator [FIL_158] (rows=457565061 width=343) + predicate:((ss_sold_date_sk BETWEEN DynamicValue(RS_20_date_dim_d_date_sk_min) AND DynamicValue(RS_20_date_dim_d_date_sk_max) and in_bloom_filter(ss_sold_date_sk, DynamicValue(RS_20_date_dim_d_date_sk_bloom_filter))) and ss_addr_sk is not null and ss_customer_sk is not null and ss_hdemo_sk is not null and ss_sold_date_sk is not null and ss_store_sk is not null) + TableScan [TS_5] (rows=575995635 width=343) + default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_customer_sk","ss_hdemo_sk","ss_addr_sk","ss_store_sk","ss_ticket_number","ss_ext_sales_price","ss_ext_list_price","ss_ext_tax"] + <-Reducer 13 [BROADCAST_EDGE] vectorized + BROADCAST [RS_157] + Group By Operator [GBY_156] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] + <-Map 12 [CUSTOM_SIMPLE_EDGE] vectorized + SHUFFLE [RS_155] + Group By Operator [GBY_154] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] + Select Operator [SEL_153] (rows=170 width=4) + Output:["_col0"] + Please refer to the previous Select Operator [SEL_151] diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query70.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query70.q.out index a49314c858..f551755a23 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query70.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query70.q.out @@ -109,6 +109,16 @@ Stage-0 SHUFFLE [RS_168] Select Operator [SEL_167] (rows=1 width=492) Output:["_col0","_col1","_col2","_col3","_col4","_col5"] +<<<<<<< HEAD + PTF Operator [PTF_165] (rows=1 width=304) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col2 DESC NULLS LAST","partition by:":"(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END"}] + Select Operator [SEL_164] (rows=1 width=304) + Output:["_col0","_col1","_col2","_col3"] + <-Reducer 4 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_163] + PartitionCols:(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END + Select Operator [SEL_162] (rows=1 width=304) +======= PTF Operator [PTF_166] (rows=1 width=304) Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col2 DESC NULLS LAST","partition by:":"(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END"}] Select Operator [SEL_165] (rows=1 width=304) @@ -117,6 +127,7 @@ Stage-0 SHUFFLE [RS_164] PartitionCols:(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END Select Operator [SEL_163] (rows=1 width=304) +>>>>>>> asf/master Output:["_col0","_col1","_col2","_col3"] Group By Operator [GBY_162] (rows=1 width=304) Output:["_col0","_col1","_col2","_col3"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1, KEY._col2 diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query72.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query72.q.out index 1a9c2cf203..d0900a1221 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query72.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query72.q.out @@ -101,14 +101,14 @@ Stage-0 limit:100 Stage-1 Reducer 12 vectorized - File Output Operator [FS_277] - Limit [LIM_276] (rows=100 width=312) + File Output Operator [FS_279] + Limit [LIM_278] (rows=100 width=312) Number of rows:100 - Select Operator [SEL_275] (rows=193558220 width=312) + Select Operator [SEL_277] (rows=193558220 width=312) Output:["_col0","_col1","_col2","_col3","_col4","_col5"] <-Reducer 11 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_274] - Group By Operator [GBY_273] (rows=193558220 width=312) + SHUFFLE [RS_276] + Group By Operator [GBY_275] (rows=193558220 width=312) Output:["_col0","_col1","_col2","_col3","_col4","_col5"],aggregations:["count(VALUE._col0)","count(VALUE._col1)","count(VALUE._col2)"],keys:KEY._col0, KEY._col1, KEY._col2 <-Reducer 10 [SIMPLE_EDGE] SHUFFLE [RS_64] @@ -117,12 +117,12 @@ Stage-0 Output:["_col0","_col1","_col2","_col3","_col4","_col5"],aggregations:["count(_col3)","count(_col4)","count()"],keys:_col0, _col1, _col2 Select Operator [SEL_61] (rows=499184560 width=292) Output:["_col0","_col1","_col2","_col3","_col4"] - Merge Join Operator [MERGEJOIN_243] (rows=499184560 width=292) - Conds:RS_58._col4, _col6=RS_272._col0, _col1(Left Outer),Output:["_col13","_col15","_col19","_col25"] + Merge Join Operator [MERGEJOIN_245] (rows=499184560 width=292) + Conds:RS_58._col4, _col6=RS_274._col0, _col1(Left Outer),Output:["_col13","_col15","_col19","_col25"] <-Map 24 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_272] + SHUFFLE [RS_274] PartitionCols:_col0, _col1 - Select Operator [SEL_271] (rows=28798881 width=8) + Select Operator [SEL_273] (rows=28798881 width=8) Output:["_col0","_col1"] TableScan [TS_56] (rows=28798881 width=8) default@catalog_returns,catalog_returns,Tbl:COMPLETE,Col:COMPLETE,Output:["cr_item_sk","cr_order_number"] @@ -131,50 +131,50 @@ Stage-0 PartitionCols:_col4, _col6 Select Operator [SEL_55] (rows=193558220 width=300) Output:["_col4","_col6","_col13","_col15","_col19","_col25"] - Merge Join Operator [MERGEJOIN_242] (rows=193558220 width=300) - Conds:RS_52._col5=RS_270._col0(Left Outer),Output:["_col4","_col6","_col13","_col20","_col24","_col25"] + Merge Join Operator [MERGEJOIN_244] (rows=193558220 width=300) + Conds:RS_52._col4=RS_272._col0(Inner),Output:["_col4","_col6","_col13","_col20","_col21","_col25"] <-Map 23 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_270] + SHUFFLE [RS_272] PartitionCols:_col0 - Select Operator [SEL_269] (rows=2300 width=4) - Output:["_col0"] - TableScan [TS_27] (rows=2300 width=4) - default@promotion,promotion,Tbl:COMPLETE,Col:COMPLETE,Output:["p_promo_sk"] + Select Operator [SEL_271] (rows=462000 width=188) + Output:["_col0","_col1"] + TableScan [TS_27] (rows=462000 width=188) + default@item,item,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_item_desc"] <-Reducer 8 [SIMPLE_EDGE] SHUFFLE [RS_52] - PartitionCols:_col5 - Merge Join Operator [MERGEJOIN_241] (rows=193558220 width=299) - Conds:RS_49._col4=RS_268._col0(Inner),Output:["_col4","_col5","_col6","_col13","_col20","_col24"] - <-Map 22 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_268] - PartitionCols:_col0 - Select Operator [SEL_267] (rows=462000 width=188) - Output:["_col0","_col1"] - TableScan [TS_25] (rows=462000 width=188) - default@item,item,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_item_desc"] - <-Reducer 7 [SIMPLE_EDGE] - SHUFFLE [RS_49] - PartitionCols:_col4 - Filter Operator [FIL_48] (rows=193558220 width=131) - predicate:(_col22 > _col14) - Merge Join Operator [MERGEJOIN_240] (rows=580674662 width=131) - Conds:RS_45._col1=RS_266._col0(Inner),Output:["_col4","_col5","_col6","_col13","_col14","_col20","_col22"] + PartitionCols:_col4 + Filter Operator [FIL_51] (rows=193558220 width=132) + predicate:(_col23 > _col14) + Merge Join Operator [MERGEJOIN_243] (rows=580674662 width=132) + Conds:RS_48._col1=RS_270._col0(Inner),Output:["_col4","_col6","_col13","_col14","_col20","_col21","_col23"] + <-Map 22 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_270] + PartitionCols:_col0 + Select Operator [SEL_269] (rows=73049 width=12) + Output:["_col0","_col1"] + TableScan [TS_25] (rows=73049 width=98) + default@date_dim,d3,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_date"] + <-Reducer 7 [SIMPLE_EDGE] + SHUFFLE [RS_48] + PartitionCols:_col1 + Merge Join Operator [MERGEJOIN_242] (rows=580674662 width=127) + Conds:RS_45._col5=RS_268._col0(Left Outer),Output:["_col1","_col4","_col6","_col13","_col14","_col20","_col21"] <-Map 21 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_266] + SHUFFLE [RS_268] PartitionCols:_col0 - Select Operator [SEL_265] (rows=73049 width=12) - Output:["_col0","_col1"] - TableScan [TS_23] (rows=73049 width=98) - default@date_dim,d3,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_date"] + Select Operator [SEL_267] (rows=2300 width=4) + Output:["_col0"] + TableScan [TS_23] (rows=2300 width=4) + default@promotion,promotion,Tbl:COMPLETE,Col:COMPLETE,Output:["p_promo_sk"] <-Reducer 6 [SIMPLE_EDGE] SHUFFLE [RS_45] - PartitionCols:_col1 - Merge Join Operator [MERGEJOIN_239] (rows=580674662 width=127) - Conds:RS_42._col17=RS_264._col0(Inner),Output:["_col1","_col4","_col5","_col6","_col13","_col14","_col20"] + PartitionCols:_col5 + Merge Join Operator [MERGEJOIN_241] (rows=580674662 width=127) + Conds:RS_42._col17=RS_266._col0(Inner),Output:["_col1","_col4","_col5","_col6","_col13","_col14","_col20"] <-Map 20 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_264] + SHUFFLE [RS_266] PartitionCols:_col0 - Select Operator [SEL_263] (rows=27 width=104) + Select Operator [SEL_265] (rows=27 width=104) Output:["_col0","_col1"] TableScan [TS_21] (rows=27 width=104) default@warehouse,warehouse,Tbl:COMPLETE,Col:COMPLETE,Output:["w_warehouse_sk","w_warehouse_name"] @@ -183,88 +183,88 @@ Stage-0 PartitionCols:_col17 Filter Operator [FIL_41] (rows=580674662 width=39) predicate:(_col18 < _col7) - Merge Join Operator [MERGEJOIN_238] (rows=1742023986 width=39) - Conds:RS_38._col10, _col4=RS_262._col0, _col1(Inner),Output:["_col1","_col4","_col5","_col6","_col7","_col13","_col14","_col17","_col18"] + Merge Join Operator [MERGEJOIN_240] (rows=1742023986 width=39) + Conds:RS_38._col10, _col4=RS_264._col0, _col1(Inner),Output:["_col1","_col4","_col5","_col6","_col7","_col13","_col14","_col17","_col18"] <-Map 19 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_262] + SHUFFLE [RS_264] PartitionCols:_col0, _col1 - Select Operator [SEL_261] (rows=37584000 width=15) + Select Operator [SEL_263] (rows=37584000 width=15) Output:["_col0","_col1","_col2","_col3"] TableScan [TS_19] (rows=37584000 width=15) default@inventory,inventory,Tbl:COMPLETE,Col:COMPLETE,Output:["inv_date_sk","inv_item_sk","inv_warehouse_sk","inv_quantity_on_hand"] <-Reducer 4 [SIMPLE_EDGE] SHUFFLE [RS_38] PartitionCols:_col10, _col4 - Merge Join Operator [MERGEJOIN_237] (rows=2899758 width=30) + Merge Join Operator [MERGEJOIN_239] (rows=2899758 width=30) Conds:RS_35._col0=RS_36._col2(Inner),Output:["_col1","_col4","_col5","_col6","_col7","_col10","_col13","_col14"] <-Reducer 16 [SIMPLE_EDGE] SHUFFLE [RS_36] PartitionCols:_col2 - Merge Join Operator [MERGEJOIN_236] (rows=3621 width=20) - Conds:RS_246._col1=RS_249._col1(Inner),Output:["_col0","_col2","_col3","_col4"] + Merge Join Operator [MERGEJOIN_238] (rows=3621 width=20) + Conds:RS_248._col1=RS_251._col1(Inner),Output:["_col0","_col2","_col3","_col4"] <-Map 15 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_246] + SHUFFLE [RS_248] PartitionCols:_col1 - Select Operator [SEL_245] (rows=73049 width=8) + Select Operator [SEL_247] (rows=73049 width=8) Output:["_col0","_col1"] - Filter Operator [FIL_244] (rows=73049 width=8) + Filter Operator [FIL_246] (rows=73049 width=8) predicate:d_week_seq is not null TableScan [TS_9] (rows=73049 width=8) default@date_dim,d2,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_week_seq"] <-Map 18 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_249] + SHUFFLE [RS_251] PartitionCols:_col1 - Select Operator [SEL_248] (rows=652 width=16) + Select Operator [SEL_250] (rows=652 width=16) Output:["_col0","_col1","_col2"] - Filter Operator [FIL_247] (rows=652 width=106) + Filter Operator [FIL_249] (rows=652 width=106) predicate:((d_year = 2001) and d_week_seq is not null) TableScan [TS_12] (rows=73049 width=106) default@date_dim,d1,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_date","d_week_seq","d_year"] <-Reducer 3 [SIMPLE_EDGE] SHUFFLE [RS_35] PartitionCols:_col0 - Merge Join Operator [MERGEJOIN_235] (rows=8179029 width=21) - Conds:RS_32._col3=RS_260._col0(Inner),Output:["_col0","_col1","_col4","_col5","_col6","_col7"] + Merge Join Operator [MERGEJOIN_237] (rows=8179029 width=21) + Conds:RS_32._col3=RS_262._col0(Inner),Output:["_col0","_col1","_col4","_col5","_col6","_col7"] <-Map 14 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_260] + SHUFFLE [RS_262] PartitionCols:_col0 - Select Operator [SEL_259] (rows=1440 width=4) + Select Operator [SEL_261] (rows=1440 width=4) Output:["_col0"] - Filter Operator [FIL_258] (rows=1440 width=96) + Filter Operator [FIL_260] (rows=1440 width=96) predicate:(hd_buy_potential = '1001-5000') TableScan [TS_6] (rows=7200 width=96) default@household_demographics,household_demographics,Tbl:COMPLETE,Col:COMPLETE,Output:["hd_demo_sk","hd_buy_potential"] <-Reducer 2 [SIMPLE_EDGE] SHUFFLE [RS_32] PartitionCols:_col3 - Merge Join Operator [MERGEJOIN_234] (rows=40895144 width=27) - Conds:RS_254._col2=RS_257._col0(Inner),Output:["_col0","_col1","_col3","_col4","_col5","_col6","_col7"] + Merge Join Operator [MERGEJOIN_236] (rows=40895144 width=27) + Conds:RS_256._col2=RS_259._col0(Inner),Output:["_col0","_col1","_col3","_col4","_col5","_col6","_col7"] <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_254] + SHUFFLE [RS_256] PartitionCols:_col2 - Select Operator [SEL_253] (rows=282274763 width=31) + Select Operator [SEL_255] (rows=282274763 width=31) Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7"] - Filter Operator [FIL_252] (rows=282274763 width=31) + Filter Operator [FIL_254] (rows=282274763 width=31) predicate:((cs_sold_date_sk BETWEEN DynamicValue(RS_36_d1_d_date_sk_min) AND DynamicValue(RS_36_d1_d_date_sk_max) and in_bloom_filter(cs_sold_date_sk, DynamicValue(RS_36_d1_d_date_sk_bloom_filter))) and cs_bill_cdemo_sk is not null and cs_bill_hdemo_sk is not null and cs_ship_date_sk is not null and cs_sold_date_sk is not null) TableScan [TS_0] (rows=287989836 width=31) default@catalog_sales,catalog_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["cs_sold_date_sk","cs_ship_date_sk","cs_bill_cdemo_sk","cs_bill_hdemo_sk","cs_item_sk","cs_promo_sk","cs_order_number","cs_quantity"] <-Reducer 17 [BROADCAST_EDGE] vectorized - BROADCAST [RS_251] - Group By Operator [GBY_250] (rows=1 width=12) + BROADCAST [RS_253] + Group By Operator [GBY_252] (rows=1 width=12) Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] <-Reducer 16 [CUSTOM_SIMPLE_EDGE] - SHUFFLE [RS_138] - Group By Operator [GBY_137] (rows=1 width=12) + SHUFFLE [RS_140] + Group By Operator [GBY_139] (rows=1 width=12) Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] - Select Operator [SEL_136] (rows=3621 width=8) + Select Operator [SEL_138] (rows=3621 width=8) Output:["_col0"] - Please refer to the previous Merge Join Operator [MERGEJOIN_236] + Please refer to the previous Merge Join Operator [MERGEJOIN_238] <-Map 13 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_257] + SHUFFLE [RS_259] PartitionCols:_col0 - Select Operator [SEL_256] (rows=265971 width=4) + Select Operator [SEL_258] (rows=265971 width=4) Output:["_col0"] - Filter Operator [FIL_255] (rows=265971 width=89) + Filter Operator [FIL_257] (rows=265971 width=89) predicate:(cd_marital_status = 'M') TableScan [TS_3] (rows=1861800 width=89) default@customer_demographics,customer_demographics,Tbl:COMPLETE,Col:COMPLETE,Output:["cd_demo_sk","cd_marital_status"] diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query73.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query73.q.out index 52b0c26588..8d3ddcc527 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query73.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query73.q.out @@ -101,7 +101,7 @@ Stage-0 SHUFFLE [RS_122] PartitionCols:_col1 Filter Operator [FIL_121] (rows=5 width=12) - predicate:_col2 BETWEEN 1 AND 5 + predicate:_col2 BETWEEN 1L AND 5L Select Operator [SEL_120] (rows=788766 width=12) Output:["_col0","_col1","_col2"] Group By Operator [GBY_119] (rows=788766 width=12) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query74.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query74.q.out index 525217b526..36c7b7975c 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query74.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query74.q.out @@ -171,7 +171,7 @@ Stage-0 Select Operator [SEL_88] (rows=12248094 width=280) Output:["_col0","_col1","_col2"] Filter Operator [FIL_87] (rows=12248094 width=732) - predicate:CASE WHEN (_col4 is not null) THEN (CASE WHEN (_col2) THEN (((_col6 / _col1) > (_col10 / _col4))) ELSE ((null > (_col10 / _col4))) END) ELSE (CASE WHEN (_col2) THEN (((_col6 / _col1) > null)) ELSE (null) END) END + predicate:CASE WHEN (_col4 is not null) THEN (CASE WHEN (_col2) THEN (((_col6 / _col1) > (_col10 / _col4))) ELSE (null) END) ELSE (null) END Merge Join Operator [MERGEJOIN_283] (rows=24496188 width=732) Conds:RS_84._col3=RS_345._col0(Inner),Output:["_col1","_col2","_col4","_col6","_col7","_col8","_col9","_col10"] <-Reducer 20 [SIMPLE_EDGE] vectorized diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query78.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query78.q.out index ef4d6dbc21..bb3bcd30d8 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query78.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query78.q.out @@ -143,8 +143,8 @@ Reducer 18 <- Map 17 (SIMPLE_EDGE), Map 19 (SIMPLE_EDGE) Reducer 2 <- Map 1 (SIMPLE_EDGE), Reducer 15 (SIMPLE_EDGE) Reducer 21 <- Map 20 (SIMPLE_EDGE), Map 22 (SIMPLE_EDGE) Reducer 3 <- Reducer 2 (SIMPLE_EDGE) -Reducer 4 <- Reducer 3 (ONE_TO_ONE_EDGE), Reducer 9 (ONE_TO_ONE_EDGE) -Reducer 5 <- Reducer 12 (SIMPLE_EDGE), Reducer 4 (SIMPLE_EDGE) +Reducer 4 <- Reducer 3 (SIMPLE_EDGE), Reducer 9 (SIMPLE_EDGE) +Reducer 5 <- Reducer 12 (ONE_TO_ONE_EDGE), Reducer 4 (SIMPLE_EDGE) Reducer 6 <- Reducer 5 (SIMPLE_EDGE) Reducer 7 <- Map 1 (CUSTOM_SIMPLE_EDGE) Reducer 8 <- Map 1 (SIMPLE_EDGE), Reducer 18 (SIMPLE_EDGE) @@ -152,194 +152,196 @@ Reducer 9 <- Reducer 8 (SIMPLE_EDGE) Stage-0 Fetch Operator - limit:100 + limit:-1 Stage-1 Reducer 6 vectorized - File Output Operator [FS_238] - Limit [LIM_237] (rows=100 width=484) - Number of rows:100 - Select Operator [SEL_236] (rows=462576000046 width=483) - Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9"] - <-Reducer 5 [SIMPLE_EDGE] - SHUFFLE [RS_73] - Select Operator [SEL_72] (rows=462576000046 width=719) - Output:["_col0","_col1","_col6","_col7","_col8","_col9","_col10","_col11","_col12"] - Filter Operator [FIL_71] (rows=462576000046 width=702) - predicate:CASE WHEN (_col11 is not null) THEN ((_col11 > 0L)) ELSE (false) END - Merge Join Operator [MERGEJOIN_191] (rows=925152000093 width=702) - Conds:RS_68._col1=RS_235._col0(Left Outer),Output:["_col0","_col1","_col2","_col3","_col4","_col7","_col8","_col9","_col11","_col12","_col13"] - <-Reducer 12 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_235] - PartitionCols:_col0 - Select Operator [SEL_234] (rows=101592102 width=235) - Output:["_col0","_col1","_col2","_col3"] - Group By Operator [GBY_233] (rows=101592102 width=239) + File Output Operator [FS_270] + Select Operator [SEL_269] (rows=100 width=484) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9"] + Limit [LIM_268] (rows=100 width=720) + Number of rows:100 + Select Operator [SEL_267] (rows=203549242538 width=719) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8"] + <-Reducer 5 [SIMPLE_EDGE] + SHUFFLE [RS_73] + Select Operator [SEL_72] (rows=203549242538 width=719) + Output:["_col0","_col1","_col6","_col7","_col8","_col9","_col10","_col11","_col12"] + Merge Join Operator [MERGEJOIN_220] (rows=203549242538 width=703) + Conds:RS_69._col0, _col1=RS_266._col0, _col1(Inner),Output:["_col0","_col1","_col2","_col3","_col4","_col6","_col7","_col8","_col11","_col12","_col13"] + <-Reducer 12 [ONE_TO_ONE_EDGE] vectorized + FORWARD [RS_266] + PartitionCols:_col0, _col1 + Filter Operator [FIL_265] (rows=13513323 width=239) + predicate:(_col2 > 0L) + Group By Operator [GBY_264] (rows=40539971 width=239) Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)"],keys:KEY._col0, KEY._col1 <-Reducer 11 [SIMPLE_EDGE] - SHUFFLE [RS_65] + SHUFFLE [RS_62] PartitionCols:_col0, _col1 - Group By Operator [GBY_64] (rows=101592102 width=239) + Group By Operator [GBY_61] (rows=40539971 width=239) Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(_col4)","sum(_col5)","sum(_col6)"],keys:_col2, _col3 - Merge Join Operator [MERGEJOIN_189] (rows=101592102 width=233) - Conds:RS_198._col0=RS_61._col0(Inner),Output:["_col2","_col3","_col4","_col5","_col6"] + Merge Join Operator [MERGEJOIN_218] (rows=40539971 width=235) + Conds:RS_227._col0=RS_58._col0(Inner),Output:["_col2","_col3","_col4","_col5","_col6"] <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_198] + SHUFFLE [RS_227] PartitionCols:_col0 - Select Operator [SEL_193] (rows=652 width=4) + Select Operator [SEL_222] (rows=652 width=4) Output:["_col0"] - Filter Operator [FIL_192] (rows=652 width=8) + Filter Operator [FIL_221] (rows=652 width=8) predicate:(d_year = 2000) TableScan [TS_0] (rows=73049 width=8) default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year"] <-Reducer 21 [SIMPLE_EDGE] - SHUFFLE [RS_61] + SHUFFLE [RS_58] PartitionCols:_col0 - Select Operator [SEL_59] (rows=286549727 width=239) + Select Operator [SEL_56] (rows=113538342 width=239) Output:["_col0","_col1","_col2","_col3","_col4","_col5"] - Filter Operator [FIL_58] (rows=286549727 width=240) + Filter Operator [FIL_55] (rows=113538342 width=242) predicate:_col8 is null - Merge Join Operator [MERGEJOIN_188] (rows=468719906 width=240) - Conds:RS_230._col2, _col3=RS_232._col0, _col1(Left Outer),Output:["_col0","_col1","_col2","_col4","_col5","_col6","_col8"] + Merge Join Operator [MERGEJOIN_217] (rows=254644510 width=242) + Conds:RS_261._col1, _col3=RS_263._col0, _col1(Left Outer),Output:["_col0","_col1","_col2","_col4","_col5","_col6","_col8"] <-Map 20 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_230] - PartitionCols:_col2, _col3 - Select Operator [SEL_229] (rows=286549727 width=242) + SHUFFLE [RS_261] + PartitionCols:_col1, _col3 + Select Operator [SEL_260] (rows=143930993 width=243) Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] - Filter Operator [FIL_228] (rows=286549727 width=242) - predicate:((cs_sold_date_sk BETWEEN DynamicValue(RS_60_date_dim_d_date_sk_min) AND DynamicValue(RS_60_date_dim_d_date_sk_max) and in_bloom_filter(cs_sold_date_sk, DynamicValue(RS_60_date_dim_d_date_sk_bloom_filter))) and cs_sold_date_sk is not null) - TableScan [TS_50] (rows=287989836 width=242) - default@catalog_sales,catalog_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["cs_sold_date_sk","cs_bill_customer_sk","cs_item_sk","cs_order_number","cs_quantity","cs_wholesale_cost","cs_sales_price"] + Filter Operator [FIL_259] (rows=143930993 width=243) + predicate:((ws_sold_date_sk BETWEEN DynamicValue(RS_57_date_dim_d_date_sk_min) AND DynamicValue(RS_57_date_dim_d_date_sk_max) and in_bloom_filter(ws_sold_date_sk, DynamicValue(RS_57_date_dim_d_date_sk_bloom_filter))) and ws_bill_customer_sk is not null and ws_sold_date_sk is not null) + TableScan [TS_47] (rows=144002668 width=243) + default@web_sales,web_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ws_sold_date_sk","ws_item_sk","ws_bill_customer_sk","ws_order_number","ws_quantity","ws_wholesale_cost","ws_sales_price"] <-Reducer 13 [BROADCAST_EDGE] vectorized - BROADCAST [RS_227] - Group By Operator [GBY_226] (rows=1 width=12) + BROADCAST [RS_258] + Group By Operator [GBY_257] (rows=1 width=12) Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] <-Map 1 [CUSTOM_SIMPLE_EDGE] vectorized - SHUFFLE [RS_205] - Group By Operator [GBY_202] (rows=1 width=12) + SHUFFLE [RS_234] + Group By Operator [GBY_231] (rows=1 width=12) Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] - Select Operator [SEL_199] (rows=652 width=4) + Select Operator [SEL_228] (rows=652 width=4) Output:["_col0"] - Please refer to the previous Select Operator [SEL_193] + Please refer to the previous Select Operator [SEL_222] <-Map 22 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_232] + SHUFFLE [RS_263] PartitionCols:_col0, _col1 - Select Operator [SEL_231] (rows=28798881 width=8) + Select Operator [SEL_262] (rows=14398467 width=8) Output:["_col0","_col1"] - TableScan [TS_53] (rows=28798881 width=8) - default@catalog_returns,catalog_returns,Tbl:COMPLETE,Col:COMPLETE,Output:["cr_item_sk","cr_order_number"] + TableScan [TS_50] (rows=14398467 width=8) + default@web_returns,web_returns,Tbl:COMPLETE,Col:COMPLETE,Output:["wr_item_sk","wr_order_number"] <-Reducer 4 [SIMPLE_EDGE] - SHUFFLE [RS_68] - PartitionCols:_col1 - Filter Operator [FIL_45] (rows=4580227799 width=471) - predicate:CASE WHEN (_col7 is not null) THEN ((_col7 > 0L)) ELSE (false) END - Merge Join Operator [MERGEJOIN_190] (rows=9160455599 width=471) - Conds:RS_215._col1, _col0=RS_225._col1, _col0(Left Outer),Output:["_col0","_col1","_col2","_col3","_col4","_col7","_col8","_col9"] - <-Reducer 3 [ONE_TO_ONE_EDGE] vectorized - FORWARD [RS_215] - PartitionCols:_col1, _col0 - Select Operator [SEL_214] (rows=114214965 width=239) - Output:["_col0","_col1","_col2","_col3","_col4"] - Group By Operator [GBY_213] (rows=114214965 width=239) - Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)"],keys:KEY._col0, KEY._col1 - <-Reducer 2 [SIMPLE_EDGE] - SHUFFLE [RS_18] - PartitionCols:_col0, _col1 - Group By Operator [GBY_17] (rows=114214965 width=239) - Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(_col4)","sum(_col5)","sum(_col6)"],keys:_col3, _col2 - Merge Join Operator [MERGEJOIN_185] (rows=114214965 width=217) - Conds:RS_194._col0=RS_14._col0(Inner),Output:["_col2","_col3","_col4","_col5","_col6"] - <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_194] - PartitionCols:_col0 - Please refer to the previous Select Operator [SEL_193] - <-Reducer 15 [SIMPLE_EDGE] - SHUFFLE [RS_14] - PartitionCols:_col0 - Select Operator [SEL_12] (rows=319876350 width=233) - Output:["_col0","_col1","_col2","_col3","_col4","_col5"] - Filter Operator [FIL_11] (rows=319876350 width=235) - predicate:_col8 is null - Merge Join Operator [MERGEJOIN_184] (rows=883006376 width=235) - Conds:RS_210._col1, _col3=RS_212._col0, _col1(Left Outer),Output:["_col0","_col1","_col2","_col4","_col5","_col6","_col8"] - <-Map 14 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_210] - PartitionCols:_col1, _col3 - Select Operator [SEL_209] (rows=550076554 width=233) - Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] - Filter Operator [FIL_208] (rows=550076554 width=233) - predicate:((ss_sold_date_sk BETWEEN DynamicValue(RS_13_date_dim_d_date_sk_min) AND DynamicValue(RS_13_date_dim_d_date_sk_max) and in_bloom_filter(ss_sold_date_sk, DynamicValue(RS_13_date_dim_d_date_sk_bloom_filter))) and ss_sold_date_sk is not null) - TableScan [TS_3] (rows=575995635 width=233) - default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_item_sk","ss_customer_sk","ss_ticket_number","ss_quantity","ss_wholesale_cost","ss_sales_price"] - <-Reducer 7 [BROADCAST_EDGE] vectorized - BROADCAST [RS_207] - Group By Operator [GBY_206] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] - <-Map 1 [CUSTOM_SIMPLE_EDGE] vectorized - SHUFFLE [RS_203] - Group By Operator [GBY_200] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] - Select Operator [SEL_195] (rows=652 width=4) - Output:["_col0"] - Please refer to the previous Select Operator [SEL_193] - <-Map 16 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_212] - PartitionCols:_col0, _col1 - Select Operator [SEL_211] (rows=57591150 width=8) - Output:["_col0","_col1"] - TableScan [TS_6] (rows=57591150 width=8) - default@store_returns,store_returns,Tbl:COMPLETE,Col:COMPLETE,Output:["sr_item_sk","sr_ticket_number"] - <-Reducer 9 [ONE_TO_ONE_EDGE] vectorized - FORWARD [RS_225] - PartitionCols:_col1, _col0 - Select Operator [SEL_224] (rows=40539971 width=239) - Output:["_col0","_col1","_col2","_col3","_col4"] - Group By Operator [GBY_223] (rows=40539971 width=239) - Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)"],keys:KEY._col0, KEY._col1 - <-Reducer 8 [SIMPLE_EDGE] - SHUFFLE [RS_39] - PartitionCols:_col0, _col1 - Group By Operator [GBY_38] (rows=40539971 width=239) - Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(_col4)","sum(_col5)","sum(_col6)"],keys:_col3, _col2 - Merge Join Operator [MERGEJOIN_187] (rows=40539971 width=235) - Conds:RS_196._col0=RS_35._col0(Inner),Output:["_col2","_col3","_col4","_col5","_col6"] - <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_196] - PartitionCols:_col0 - Please refer to the previous Select Operator [SEL_193] - <-Reducer 18 [SIMPLE_EDGE] - SHUFFLE [RS_35] - PartitionCols:_col0 - Select Operator [SEL_33] (rows=113538342 width=239) - Output:["_col0","_col1","_col2","_col3","_col4","_col5"] - Filter Operator [FIL_32] (rows=113538342 width=242) - predicate:_col8 is null - Merge Join Operator [MERGEJOIN_186] (rows=254679677 width=242) - Conds:RS_220._col1, _col3=RS_222._col0, _col1(Left Outer),Output:["_col0","_col1","_col2","_col4","_col5","_col6","_col8"] - <-Map 17 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_220] - PartitionCols:_col1, _col3 - Select Operator [SEL_219] (rows=143966864 width=243) - Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] - Filter Operator [FIL_218] (rows=143966864 width=243) - predicate:((ws_sold_date_sk BETWEEN DynamicValue(RS_34_date_dim_d_date_sk_min) AND DynamicValue(RS_34_date_dim_d_date_sk_max) and in_bloom_filter(ws_sold_date_sk, DynamicValue(RS_34_date_dim_d_date_sk_bloom_filter))) and ws_sold_date_sk is not null) - TableScan [TS_24] (rows=144002668 width=243) - default@web_sales,web_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ws_sold_date_sk","ws_item_sk","ws_bill_customer_sk","ws_order_number","ws_quantity","ws_wholesale_cost","ws_sales_price"] - <-Reducer 10 [BROADCAST_EDGE] vectorized - BROADCAST [RS_217] - Group By Operator [GBY_216] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] - <-Map 1 [CUSTOM_SIMPLE_EDGE] vectorized - SHUFFLE [RS_204] - Group By Operator [GBY_201] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] - Select Operator [SEL_197] (rows=652 width=4) - Output:["_col0"] - Please refer to the previous Select Operator [SEL_193] - <-Map 19 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_222] - PartitionCols:_col0, _col1 - Select Operator [SEL_221] (rows=14398467 width=8) - Output:["_col0","_col1"] - TableScan [TS_27] (rows=14398467 width=8) - default@web_returns,web_returns,Tbl:COMPLETE,Col:COMPLETE,Output:["wr_item_sk","wr_order_number"] + SHUFFLE [RS_69] + PartitionCols:_col0, _col1 + Merge Join Operator [MERGEJOIN_219] (rows=7613716536 width=471) + Conds:RS_244._col1=RS_256._col0(Inner),Output:["_col0","_col1","_col2","_col3","_col4","_col6","_col7","_col8"] + <-Reducer 3 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_244] + PartitionCols:_col1 + Select Operator [SEL_243] (rows=114214965 width=239) + Output:["_col0","_col1","_col2","_col3","_col4"] + Group By Operator [GBY_242] (rows=114214965 width=239) + Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)"],keys:KEY._col0, KEY._col1 + <-Reducer 2 [SIMPLE_EDGE] + SHUFFLE [RS_18] + PartitionCols:_col0, _col1 + Group By Operator [GBY_17] (rows=114214965 width=239) + Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(_col4)","sum(_col5)","sum(_col6)"],keys:_col3, _col2 + Merge Join Operator [MERGEJOIN_214] (rows=114214965 width=218) + Conds:RS_223._col0=RS_14._col0(Inner),Output:["_col2","_col3","_col4","_col5","_col6"] + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_223] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_222] + <-Reducer 15 [SIMPLE_EDGE] + SHUFFLE [RS_14] + PartitionCols:_col0 + Select Operator [SEL_12] (rows=319876350 width=233) + Output:["_col0","_col1","_col2","_col3","_col4","_col5"] + Filter Operator [FIL_11] (rows=319876350 width=236) + predicate:_col8 is null + Merge Join Operator [MERGEJOIN_213] (rows=857669906 width=236) + Conds:RS_239._col1, _col3=RS_241._col0, _col1(Left Outer),Output:["_col0","_col1","_col2","_col4","_col5","_col6","_col8"] + <-Map 14 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_239] + PartitionCols:_col1, _col3 + Select Operator [SEL_238] (rows=525327388 width=233) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] + Filter Operator [FIL_237] (rows=525327388 width=233) + predicate:((ss_sold_date_sk BETWEEN DynamicValue(RS_13_date_dim_d_date_sk_min) AND DynamicValue(RS_13_date_dim_d_date_sk_max) and in_bloom_filter(ss_sold_date_sk, DynamicValue(RS_13_date_dim_d_date_sk_bloom_filter))) and ss_customer_sk is not null and ss_sold_date_sk is not null) + TableScan [TS_3] (rows=575995635 width=233) + default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_item_sk","ss_customer_sk","ss_ticket_number","ss_quantity","ss_wholesale_cost","ss_sales_price"] + <-Reducer 7 [BROADCAST_EDGE] vectorized + BROADCAST [RS_236] + Group By Operator [GBY_235] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] + <-Map 1 [CUSTOM_SIMPLE_EDGE] vectorized + SHUFFLE [RS_232] + Group By Operator [GBY_229] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] + Select Operator [SEL_224] (rows=652 width=4) + Output:["_col0"] + Please refer to the previous Select Operator [SEL_222] + <-Map 16 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_241] + PartitionCols:_col0, _col1 + Select Operator [SEL_240] (rows=57591150 width=8) + Output:["_col0","_col1"] + TableScan [TS_6] (rows=57591150 width=8) + default@store_returns,store_returns,Tbl:COMPLETE,Col:COMPLETE,Output:["sr_item_sk","sr_ticket_number"] + <-Reducer 9 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_256] + PartitionCols:_col0 + Select Operator [SEL_255] (rows=33694814 width=235) + Output:["_col0","_col1","_col2","_col3"] + Filter Operator [FIL_254] (rows=33694814 width=239) + predicate:(_col2 > 0L) + Select Operator [SEL_253] (rows=101084444 width=239) + Output:["_col1","_col2","_col3","_col4"] + Group By Operator [GBY_252] (rows=101084444 width=239) + Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)"],keys:KEY._col0, KEY._col1 + <-Reducer 8 [SIMPLE_EDGE] + SHUFFLE [RS_39] + PartitionCols:_col0, _col1 + Group By Operator [GBY_38] (rows=101084444 width=239) + Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(_col4)","sum(_col5)","sum(_col6)"],keys:_col2, _col3 + Merge Join Operator [MERGEJOIN_216] (rows=101084444 width=233) + Conds:RS_225._col0=RS_35._col0(Inner),Output:["_col2","_col3","_col4","_col5","_col6"] + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_225] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_222] + <-Reducer 18 [SIMPLE_EDGE] + SHUFFLE [RS_35] + PartitionCols:_col0 + Select Operator [SEL_33] (rows=285117831 width=239) + Output:["_col0","_col1","_col2","_col3","_col4","_col5"] + Filter Operator [FIL_32] (rows=285117831 width=240) + predicate:_col8 is null + Merge Join Operator [MERGEJOIN_215] (rows=466377701 width=240) + Conds:RS_249._col2, _col3=RS_251._col0, _col1(Left Outer),Output:["_col0","_col1","_col2","_col4","_col5","_col6","_col8"] + <-Map 17 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_249] + PartitionCols:_col2, _col3 + Select Operator [SEL_248] (rows=285117831 width=242) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] + Filter Operator [FIL_247] (rows=285117831 width=242) + predicate:((cs_sold_date_sk BETWEEN DynamicValue(RS_34_date_dim_d_date_sk_min) AND DynamicValue(RS_34_date_dim_d_date_sk_max) and in_bloom_filter(cs_sold_date_sk, DynamicValue(RS_34_date_dim_d_date_sk_bloom_filter))) and cs_bill_customer_sk is not null and cs_sold_date_sk is not null) + TableScan [TS_24] (rows=287989836 width=242) + default@catalog_sales,catalog_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["cs_sold_date_sk","cs_bill_customer_sk","cs_item_sk","cs_order_number","cs_quantity","cs_wholesale_cost","cs_sales_price"] + <-Reducer 10 [BROADCAST_EDGE] vectorized + BROADCAST [RS_246] + Group By Operator [GBY_245] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] + <-Map 1 [CUSTOM_SIMPLE_EDGE] vectorized + SHUFFLE [RS_233] + Group By Operator [GBY_230] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] + Select Operator [SEL_226] (rows=652 width=4) + Output:["_col0"] + Please refer to the previous Select Operator [SEL_222] + <-Map 19 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_251] + PartitionCols:_col0, _col1 + Select Operator [SEL_250] (rows=28798881 width=8) + Output:["_col0","_col1"] + TableScan [TS_27] (rows=28798881 width=8) + default@catalog_returns,catalog_returns,Tbl:COMPLETE,Col:COMPLETE,Output:["cr_item_sk","cr_order_number"] diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query86.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query86.q.out index 638cce1b46..ec4358f82a 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query86.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query86.q.out @@ -82,12 +82,12 @@ Stage-0 Select Operator [SEL_78] (rows=3060 width=490) Output:["_col0","_col1","_col2","_col3","_col4","_col5"] PTF Operator [PTF_77] (rows=3060 width=302) - Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col2 DESC NULLS LAST","partition by:":"(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END"}] + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col2 DESC NULLS LAST","partition by:":"(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END"}] Select Operator [SEL_76] (rows=3060 width=302) Output:["_col0","_col1","_col2","_col3"] <-Reducer 4 [SIMPLE_EDGE] vectorized SHUFFLE [RS_75] - PartitionCols:(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END + PartitionCols:(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END Select Operator [SEL_74] (rows=3060 width=302) Output:["_col0","_col1","_col2","_col3"] Group By Operator [GBY_73] (rows=3060 width=302) diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query88.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query88.q.out index 64919cafe7..ff05345222 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query88.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query88.q.out @@ -320,7 +320,7 @@ Stage-0 Select Operator [SEL_660] (rows=817 width=4) Output:["_col0"] Filter Operator [FIL_659] (rows=817 width=12) - predicate:((((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and (hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5)) + predicate:((((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (hd_dep_count) IN (3, 0, 1)) TableScan [TS_3] (rows=7200 width=12) default@household_demographics,household_demographics,Tbl:COMPLETE,Col:COMPLETE,Output:["hd_demo_sk","hd_dep_count","hd_vehicle_count"] <-Map 56 [SIMPLE_EDGE] vectorized diff --git ql/src/test/results/clientpositive/perf/tez/constraints/query89.q.out ql/src/test/results/clientpositive/perf/tez/constraints/query89.q.out index 3049fec95c..387a7e19ca 100644 --- ql/src/test/results/clientpositive/perf/tez/constraints/query89.q.out +++ ql/src/test/results/clientpositive/perf/tez/constraints/query89.q.out @@ -89,7 +89,7 @@ Stage-0 Select Operator [SEL_106] (rows=4804228 width=801) Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8"] Filter Operator [FIL_105] (rows=4804228 width=689) - predicate:CASE WHEN ((avg_window_0 <> 0)) THEN (((abs((_col6 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (null) END + predicate:CASE WHEN ((avg_window_0 <> 0)) THEN (((abs((_col6 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (false) END Select Operator [SEL_104] (rows=9608456 width=577) Output:["avg_window_0","_col0","_col1","_col2","_col3","_col4","_col5","_col6"] PTF Operator [PTF_103] (rows=9608456 width=577) diff --git ql/src/test/results/clientpositive/perf/tez/query11.q.out ql/src/test/results/clientpositive/perf/tez/query11.q.out index da1c349ff0..d3e2311bef 100644 --- ql/src/test/results/clientpositive/perf/tez/query11.q.out +++ ql/src/test/results/clientpositive/perf/tez/query11.q.out @@ -199,7 +199,7 @@ Stage-0 Select Operator [SEL_92] (rows=12248093 width=85) Output:["_col0"] Filter Operator [FIL_91] (rows=12248093 width=537) - predicate:CASE WHEN (_col3 is not null) THEN (CASE WHEN (_col6) THEN (((_col1 / _col5) > (_col9 / _col3))) ELSE ((null > (_col9 / _col3))) END) ELSE (CASE WHEN (_col6) THEN (((_col1 / _col5) > null)) ELSE (null) END) END + predicate:CASE WHEN (_col3 is not null) THEN (CASE WHEN (_col6) THEN (((_col1 / _col5) > (_col9 / _col3))) ELSE (null) END) ELSE (null) END Merge Join Operator [MERGEJOIN_287] (rows=24496186 width=537) Conds:RS_88._col2=RS_351._col0(Inner),Output:["_col1","_col3","_col5","_col6","_col8","_col9"] <-Reducer 20 [SIMPLE_EDGE] vectorized diff --git ql/src/test/results/clientpositive/perf/tez/query21.q.out ql/src/test/results/clientpositive/perf/tez/query21.q.out index 382775a8cc..9bc3464748 100644 --- ql/src/test/results/clientpositive/perf/tez/query21.q.out +++ ql/src/test/results/clientpositive/perf/tez/query21.q.out @@ -88,7 +88,7 @@ Stage-0 <-Reducer 5 [SIMPLE_EDGE] vectorized SHUFFLE [RS_92] Filter Operator [FIL_91] (rows=231983 width=216) - predicate:CASE WHEN ((_col2 > 0L)) THEN ((UDFToDouble(_col3) / UDFToDouble(_col2)) BETWEEN 0.666667D AND 1.5D) ELSE (null) END + predicate:CASE WHEN ((_col2 > 0L)) THEN ((UDFToDouble(_col3) / UDFToDouble(_col2)) BETWEEN 0.666667D AND 1.5D) ELSE (false) END Group By Operator [GBY_90] (rows=463966 width=216) Output:["_col0","_col1","_col2","_col3"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)"],keys:KEY._col0, KEY._col1 <-Reducer 4 [SIMPLE_EDGE] diff --git ql/src/test/results/clientpositive/perf/tez/query31.q.out ql/src/test/results/clientpositive/perf/tez/query31.q.out index c0762b7bd4..579d5695c1 100644 --- ql/src/test/results/clientpositive/perf/tez/query31.q.out +++ ql/src/test/results/clientpositive/perf/tez/query31.q.out @@ -158,7 +158,7 @@ Stage-0 Select Operator [SEL_138] (rows=110 width=550) Output:["_col0","_col1","_col2","_col3","_col4","_col5"] Filter Operator [FIL_136] (rows=110 width=778) - predicate:(CASE WHEN ((_col11 > 0)) THEN (CASE WHEN (_col2) THEN (((_col6 / _col1) > (_col9 / _col11))) ELSE ((null > (_col9 / _col11))) END) ELSE (CASE WHEN (_col2) THEN (((_col6 / _col1) > null)) ELSE (null) END) END and CASE WHEN ((_col9 > 0)) THEN (CASE WHEN (_col7) THEN (((_col4 / _col6) > (_col13 / _col9))) ELSE ((null > (_col13 / _col9))) END) ELSE (CASE WHEN (_col7) THEN (((_col4 / _col6) > null)) ELSE (null) END) END) + predicate:(CASE WHEN ((_col11 > 0)) THEN (CASE WHEN (_col2) THEN (((_col6 / _col1) > (_col9 / _col11))) ELSE (null) END) ELSE (null) END and CASE WHEN ((_col9 > 0)) THEN (CASE WHEN (_col7) THEN (((_col4 / _col6) > (_col13 / _col9))) ELSE (null) END) ELSE (null) END) Merge Join Operator [MERGEJOIN_450] (rows=440 width=778) Conds:RS_133._col0=RS_134._col0(Inner),Output:["_col1","_col2","_col4","_col6","_col7","_col8","_col9","_col11","_col13"] <-Reducer 22 [ONE_TO_ONE_EDGE] diff --git ql/src/test/results/clientpositive/perf/tez/query34.q.out ql/src/test/results/clientpositive/perf/tez/query34.q.out index 4640899c73..678e45bc04 100644 --- ql/src/test/results/clientpositive/perf/tez/query34.q.out +++ ql/src/test/results/clientpositive/perf/tez/query34.q.out @@ -109,7 +109,7 @@ Stage-0 SHUFFLE [RS_124] PartitionCols:_col1 Filter Operator [FIL_123] (rows=6 width=12) - predicate:_col2 BETWEEN 15 AND 20 + predicate:_col2 BETWEEN 15L AND 20L Select Operator [SEL_122] (rows=5521356 width=12) Output:["_col0","_col1","_col2"] Group By Operator [GBY_121] (rows=5521356 width=12) diff --git ql/src/test/results/clientpositive/perf/tez/query36.q.out ql/src/test/results/clientpositive/perf/tez/query36.q.out index 064837a3cf..d031995372 100644 --- ql/src/test/results/clientpositive/perf/tez/query36.q.out +++ ql/src/test/results/clientpositive/perf/tez/query36.q.out @@ -93,12 +93,12 @@ Stage-0 Select Operator [SEL_105] (rows=3060 width=490) Output:["_col0","_col1","_col2","_col3","_col4","_col5"] PTF Operator [PTF_104] (rows=3060 width=414) - Function definitions:[{},{"name:":"windowingtablefunction","order by:":"(_col2 / _col3) ASC NULLS FIRST","partition by:":"(grouping(_col4, 1) + grouping(_col4, 0)), CASE WHEN ((grouping(_col4, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END"}] + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"(_col2 / _col3) ASC NULLS FIRST","partition by:":"(grouping(_col4, 1) + grouping(_col4, 0)), CASE WHEN ((grouping(_col4, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END"}] Select Operator [SEL_103] (rows=3060 width=414) Output:["_col0","_col1","_col2","_col3","_col4"] <-Reducer 5 [SIMPLE_EDGE] vectorized SHUFFLE [RS_102] - PartitionCols:(grouping(_col4, 1) + grouping(_col4, 0)), CASE WHEN ((grouping(_col4, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END + PartitionCols:(grouping(_col4, 1) + grouping(_col4, 0)), CASE WHEN ((grouping(_col4, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END Select Operator [SEL_101] (rows=3060 width=414) Output:["_col0","_col1","_col2","_col3","_col4"] Group By Operator [GBY_100] (rows=3060 width=414) diff --git ql/src/test/results/clientpositive/perf/tez/query4.q.out ql/src/test/results/clientpositive/perf/tez/query4.q.out index bb0d7ba3f5..1fda50b68a 100644 --- ql/src/test/results/clientpositive/perf/tez/query4.q.out +++ ql/src/test/results/clientpositive/perf/tez/query4.q.out @@ -281,7 +281,7 @@ Stage-0 Select Operator [SEL_140] (rows=7323197 width=85) Output:["_col0"] Filter Operator [FIL_139] (rows=7323197 width=537) - predicate:CASE WHEN (_col3 is not null) THEN (CASE WHEN (_col9) THEN (((_col11 / _col8) > (_col14 / _col3))) ELSE ((null > (_col14 / _col3))) END) ELSE (CASE WHEN (_col9) THEN (((_col11 / _col8) > null)) ELSE (null) END) END + predicate:CASE WHEN (_col3 is not null) THEN (CASE WHEN (_col9) THEN (((_col11 / _col8) > (_col14 / _col3))) ELSE (null) END) ELSE (null) END Merge Join Operator [MERGEJOIN_472] (rows=14646395 width=537) Conds:RS_136._col2=RS_554._col0(Inner),Output:["_col3","_col8","_col9","_col11","_col13","_col14"] <-Reducer 30 [SIMPLE_EDGE] vectorized @@ -345,7 +345,7 @@ Stage-0 FORWARD [RS_136] PartitionCols:_col2 Filter Operator [FIL_135] (rows=12248093 width=668) - predicate:CASE WHEN (_col6) THEN (CASE WHEN (_col9) THEN (((_col11 / _col8) > (_col1 / _col5))) ELSE ((null > (_col1 / _col5))) END) ELSE (CASE WHEN (_col9) THEN (((_col11 / _col8) > null)) ELSE (null) END) END + predicate:CASE WHEN (_col6) THEN (CASE WHEN (_col9) THEN (((_col11 / _col8) > (_col1 / _col5))) ELSE (null) END) ELSE (null) END Merge Join Operator [MERGEJOIN_471] (rows=24496186 width=668) Conds:RS_132._col2=RS_548._col0(Inner),Output:["_col1","_col2","_col3","_col5","_col6","_col8","_col9","_col11"] <-Reducer 26 [SIMPLE_EDGE] vectorized diff --git ql/src/test/results/clientpositive/perf/tez/query42.q.out ql/src/test/results/clientpositive/perf/tez/query42.q.out index 922a58cca7..02adc5e251 100644 --- ql/src/test/results/clientpositive/perf/tez/query42.q.out +++ ql/src/test/results/clientpositive/perf/tez/query42.q.out @@ -60,68 +60,70 @@ Reducer 7 <- Map 6 (CUSTOM_SIMPLE_EDGE) Stage-0 Fetch Operator - limit:100 + limit:-1 Stage-1 Reducer 5 vectorized - File Output Operator [FS_74] - Limit [LIM_73] (rows=100 width=210) - Number of rows:100 - Select Operator [SEL_72] (rows=110 width=210) - Output:["_col0","_col1","_col2","_col3"] - <-Reducer 4 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_71] - Select Operator [SEL_70] (rows=110 width=318) - Output:["_col0","_col1","_col3"] - Group By Operator [GBY_69] (rows=110 width=206) - Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1 - <-Reducer 3 [SIMPLE_EDGE] - SHUFFLE [RS_17] - PartitionCols:_col0, _col1 - Group By Operator [GBY_16] (rows=120 width=206) - Output:["_col0","_col1","_col2"],aggregations:["sum(_col2)"],keys:_col5, _col6 - Merge Join Operator [MERGEJOIN_54] (rows=2301098 width=94) - Conds:RS_12._col1=RS_68._col0(Inner),Output:["_col2","_col5","_col6"] - <-Map 8 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_68] - PartitionCols:_col0 - Select Operator [SEL_67] (rows=7333 width=97) - Output:["_col0","_col1","_col2"] - Filter Operator [FIL_66] (rows=7333 width=101) - predicate:((i_manager_id = 1) and i_item_sk is not null) - TableScan [TS_6] (rows=462000 width=101) - default@item,item,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_category_id","i_category","i_manager_id"] - <-Reducer 2 [SIMPLE_EDGE] - SHUFFLE [RS_12] - PartitionCols:_col1 - Merge Join Operator [MERGEJOIN_53] (rows=15062131 width=4) - Conds:RS_65._col0=RS_57._col0(Inner),Output:["_col1","_col2"] - <-Map 6 [SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_57] - PartitionCols:_col0 - Select Operator [SEL_56] (rows=50 width=4) - Output:["_col0"] - Filter Operator [FIL_55] (rows=50 width=12) - predicate:((d_moy = 12) and (d_year = 1998) and d_date_sk is not null) - TableScan [TS_3] (rows=73049 width=12) - default@date_dim,dt,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year","d_moy"] - <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_65] - PartitionCols:_col0 - Select Operator [SEL_64] (rows=550076554 width=114) - Output:["_col0","_col1","_col2"] - Filter Operator [FIL_63] (rows=550076554 width=114) - predicate:((ss_sold_date_sk BETWEEN DynamicValue(RS_10_dt_d_date_sk_min) AND DynamicValue(RS_10_dt_d_date_sk_max) and in_bloom_filter(ss_sold_date_sk, DynamicValue(RS_10_dt_d_date_sk_bloom_filter))) and ss_item_sk is not null and ss_sold_date_sk is not null) - TableScan [TS_0] (rows=575995635 width=114) - default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_item_sk","ss_ext_sales_price"] - <-Reducer 7 [BROADCAST_EDGE] vectorized - BROADCAST [RS_62] - Group By Operator [GBY_61] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] - <-Map 6 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_60] - Group By Operator [GBY_59] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] - Select Operator [SEL_58] (rows=50 width=4) - Output:["_col0"] - Please refer to the previous Select Operator [SEL_56] + File Output Operator [FS_75] + Select Operator [SEL_74] (rows=100 width=210) + Output:["_col0","_col1","_col2","_col3"] + Limit [LIM_73] (rows=100 width=318) + Number of rows:100 + Select Operator [SEL_72] (rows=110 width=318) + Output:["_col0","_col1","_col2"] + <-Reducer 4 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_71] + Select Operator [SEL_70] (rows=110 width=318) + Output:["_col0","_col1","_col3"] + Group By Operator [GBY_69] (rows=110 width=206) + Output:["_col0","_col1","_col2"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1 + <-Reducer 3 [SIMPLE_EDGE] + SHUFFLE [RS_17] + PartitionCols:_col0, _col1 + Group By Operator [GBY_16] (rows=120 width=206) + Output:["_col0","_col1","_col2"],aggregations:["sum(_col2)"],keys:_col5, _col6 + Merge Join Operator [MERGEJOIN_54] (rows=2301098 width=94) + Conds:RS_12._col1=RS_68._col0(Inner),Output:["_col2","_col5","_col6"] + <-Map 8 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_68] + PartitionCols:_col0 + Select Operator [SEL_67] (rows=7333 width=97) + Output:["_col0","_col1","_col2"] + Filter Operator [FIL_66] (rows=7333 width=101) + predicate:((i_manager_id = 1) and i_item_sk is not null) + TableScan [TS_6] (rows=462000 width=101) + default@item,item,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_category_id","i_category","i_manager_id"] + <-Reducer 2 [SIMPLE_EDGE] + SHUFFLE [RS_12] + PartitionCols:_col1 + Merge Join Operator [MERGEJOIN_53] (rows=15062131 width=4) + Conds:RS_65._col0=RS_57._col0(Inner),Output:["_col1","_col2"] + <-Map 6 [SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_57] + PartitionCols:_col0 + Select Operator [SEL_56] (rows=50 width=4) + Output:["_col0"] + Filter Operator [FIL_55] (rows=50 width=12) + predicate:((d_moy = 12) and (d_year = 1998) and d_date_sk is not null) + TableScan [TS_3] (rows=73049 width=12) + default@date_dim,dt,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year","d_moy"] + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_65] + PartitionCols:_col0 + Select Operator [SEL_64] (rows=550076554 width=114) + Output:["_col0","_col1","_col2"] + Filter Operator [FIL_63] (rows=550076554 width=114) + predicate:((ss_sold_date_sk BETWEEN DynamicValue(RS_10_dt_d_date_sk_min) AND DynamicValue(RS_10_dt_d_date_sk_max) and in_bloom_filter(ss_sold_date_sk, DynamicValue(RS_10_dt_d_date_sk_bloom_filter))) and ss_item_sk is not null and ss_sold_date_sk is not null) + TableScan [TS_0] (rows=575995635 width=114) + default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_item_sk","ss_ext_sales_price"] + <-Reducer 7 [BROADCAST_EDGE] vectorized + BROADCAST [RS_62] + Group By Operator [GBY_61] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] + <-Map 6 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_60] + Group By Operator [GBY_59] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] + Select Operator [SEL_58] (rows=50 width=4) + Output:["_col0"] + Please refer to the previous Select Operator [SEL_56] diff --git ql/src/test/results/clientpositive/perf/tez/query45.q.out ql/src/test/results/clientpositive/perf/tez/query45.q.out index c2f9374c4b..19d74d98b7 100644 --- ql/src/test/results/clientpositive/perf/tez/query45.q.out +++ ql/src/test/results/clientpositive/perf/tez/query45.q.out @@ -52,15 +52,15 @@ POSTHOOK: Output: hdfs://### HDFS PATH ### Plan optimized by CBO. Vertex dependency in root stage -Map 13 <- Reducer 16 (BROADCAST_EDGE) -Reducer 10 <- Reducer 14 (SIMPLE_EDGE), Reducer 9 (SIMPLE_EDGE) +Map 12 <- Reducer 15 (BROADCAST_EDGE) +Reducer 10 <- Reducer 13 (SIMPLE_EDGE), Reducer 9 (SIMPLE_EDGE) Reducer 11 <- Map 8 (SIMPLE_EDGE) -Reducer 12 <- Map 8 (CUSTOM_SIMPLE_EDGE) -Reducer 14 <- Map 13 (SIMPLE_EDGE), Map 15 (SIMPLE_EDGE) -Reducer 16 <- Map 15 (CUSTOM_SIMPLE_EDGE) +Reducer 13 <- Map 12 (SIMPLE_EDGE), Map 14 (SIMPLE_EDGE) +Reducer 15 <- Map 14 (CUSTOM_SIMPLE_EDGE) +Reducer 17 <- Map 16 (CUSTOM_SIMPLE_EDGE) Reducer 2 <- Map 1 (SIMPLE_EDGE), Map 7 (SIMPLE_EDGE) Reducer 3 <- Reducer 10 (SIMPLE_EDGE), Reducer 2 (SIMPLE_EDGE) -Reducer 4 <- Reducer 12 (CUSTOM_SIMPLE_EDGE), Reducer 3 (CUSTOM_SIMPLE_EDGE) +Reducer 4 <- Reducer 17 (CUSTOM_SIMPLE_EDGE), Reducer 3 (CUSTOM_SIMPLE_EDGE) Reducer 5 <- Reducer 4 (SIMPLE_EDGE) Reducer 6 <- Reducer 5 (SIMPLE_EDGE) Reducer 9 <- Map 8 (SIMPLE_EDGE), Reducer 11 (ONE_TO_ONE_EDGE) @@ -82,101 +82,101 @@ Stage-0 <-Reducer 4 [SIMPLE_EDGE] SHUFFLE [RS_53] PartitionCols:_col0, _col1 - Group By Operator [GBY_52] (rows=4858260 width=299) + Group By Operator [GBY_52] (rows=3715140 width=299) Output:["_col0","_col1","_col2"],aggregations:["sum(_col3)"],keys:_col8, _col7 - Top N Key Operator [TNK_82] (rows=10246864 width=418) + Top N Key Operator [TNK_82] (rows=10246864 width=310) keys:_col8, _col7,sort order:++,top n:100 - Select Operator [SEL_51] (rows=10246864 width=418) + Select Operator [SEL_51] (rows=10246864 width=310) Output:["_col3","_col7","_col8"] - Filter Operator [FIL_50] (rows=10246864 width=418) - predicate:((substr(_col8, 1, 5)) IN ('85669', '86197', '88274', '83405', '86475', '85392', '85460', '80348', '81792') or CASE WHEN ((_col14 = 0L)) THEN (false) WHEN (_col17 is not null) THEN (true) WHEN (_col13 is null) THEN (null) WHEN ((_col15 < _col14)) THEN (null) ELSE (false) END) - Select Operator [SEL_49] (rows=10246864 width=418) - Output:["_col3","_col7","_col8","_col13","_col14","_col15","_col17"] - Merge Join Operator [MERGEJOIN_133] (rows=10246864 width=418) - Conds:(Inner),Output:["_col3","_col4","_col6","_col8","_col12","_col16","_col17"] - <-Reducer 12 [CUSTOM_SIMPLE_EDGE] vectorized + Filter Operator [FIL_50] (rows=10246864 width=310) + predicate:(((_col14 <> 0L) and _col16 is not null) or (substr(_col8, 1, 5)) IN ('85669', '86197', '88274', '83405', '86475', '85392', '85460', '80348', '81792')) + Select Operator [SEL_49] (rows=10246864 width=310) + Output:["_col3","_col7","_col8","_col14","_col16"] + Merge Join Operator [MERGEJOIN_133] (rows=10246864 width=310) + Conds:(Inner),Output:["_col3","_col4","_col8","_col12","_col16"] + <-Reducer 17 [CUSTOM_SIMPLE_EDGE] vectorized PARTITION_ONLY_SHUFFLE [RS_166] - Group By Operator [GBY_165] (rows=1 width=16) - Output:["_col0","_col1"],aggregations:["count(VALUE._col0)","count(VALUE._col1)"] - <-Map 8 [CUSTOM_SIMPLE_EDGE] vectorized - SHUFFLE [RS_150] - Group By Operator [GBY_148] (rows=1 width=16) - Output:["_col0","_col1"],aggregations:["count()","count(i_item_id)"] - Select Operator [SEL_145] (rows=11 width=104) - Output:["i_item_id"] - Filter Operator [FIL_142] (rows=11 width=104) + Group By Operator [GBY_165] (rows=1 width=8) + Output:["_col0"],aggregations:["count(VALUE._col0)"] + <-Map 16 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_164] + Group By Operator [GBY_163] (rows=1 width=8) + Output:["_col0"],aggregations:["count()"] + Select Operator [SEL_162] (rows=11 width=4) + Filter Operator [FIL_161] (rows=11 width=4) predicate:(i_item_sk) IN (2, 3, 5, 7, 11, 13, 17, 19, 23, 29) - TableScan [TS_6] (rows=462000 width=104) - default@item,item,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_item_id"] + TableScan [TS_33] (rows=462000 width=4) + default@item,item,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk"] <-Reducer 3 [CUSTOM_SIMPLE_EDGE] PARTITION_ONLY_SHUFFLE [RS_46] - Merge Join Operator [MERGEJOIN_132] (rows=10246864 width=402) - Conds:RS_43._col0=RS_44._col6(Inner),Output:["_col3","_col4","_col6","_col8","_col12"] + Merge Join Operator [MERGEJOIN_132] (rows=10246864 width=302) + Conds:RS_43._col0=RS_44._col6(Inner),Output:["_col3","_col4","_col8","_col12"] <-Reducer 10 [SIMPLE_EDGE] SHUFFLE [RS_44] PartitionCols:_col6 - Merge Join Operator [MERGEJOIN_131] (rows=10246864 width=219) - Conds:RS_29._col0=RS_30._col1(Inner),Output:["_col1","_col3","_col6","_col7"] - <-Reducer 14 [SIMPLE_EDGE] + Merge Join Operator [MERGEJOIN_131] (rows=10246864 width=119) + Conds:RS_29._col0=RS_30._col1(Inner),Output:["_col3","_col6","_col7"] + <-Reducer 13 [SIMPLE_EDGE] SHUFFLE [RS_30] PartitionCols:_col1 Merge Join Operator [MERGEJOIN_130] (rows=10246864 width=119) - Conds:RS_164._col0=RS_156._col0(Inner),Output:["_col1","_col2","_col3"] - <-Map 15 [SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_156] + Conds:RS_160._col0=RS_152._col0(Inner),Output:["_col1","_col2","_col3"] + <-Map 14 [SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_152] PartitionCols:_col0 - Select Operator [SEL_155] (rows=130 width=12) + Select Operator [SEL_151] (rows=130 width=12) Output:["_col0"] - Filter Operator [FIL_154] (rows=130 width=12) + Filter Operator [FIL_150] (rows=130 width=12) predicate:((d_qoy = 2) and (d_year = 2000) and d_date_sk is not null) TableScan [TS_19] (rows=73049 width=12) default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year","d_qoy"] - <-Map 13 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_164] + <-Map 12 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_160] PartitionCols:_col0 - Select Operator [SEL_163] (rows=143930993 width=123) + Select Operator [SEL_159] (rows=143930993 width=123) Output:["_col0","_col1","_col2","_col3"] - Filter Operator [FIL_162] (rows=143930993 width=123) + Filter Operator [FIL_158] (rows=143930993 width=123) predicate:((ws_sold_date_sk BETWEEN DynamicValue(RS_23_date_dim_d_date_sk_min) AND DynamicValue(RS_23_date_dim_d_date_sk_max) and in_bloom_filter(ws_sold_date_sk, DynamicValue(RS_23_date_dim_d_date_sk_bloom_filter))) and ws_bill_customer_sk is not null and ws_item_sk is not null and ws_sold_date_sk is not null) TableScan [TS_16] (rows=144002668 width=123) default@web_sales,web_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ws_sold_date_sk","ws_item_sk","ws_bill_customer_sk","ws_sales_price"] - <-Reducer 16 [BROADCAST_EDGE] vectorized - BROADCAST [RS_161] - Group By Operator [GBY_160] (rows=1 width=12) + <-Reducer 15 [BROADCAST_EDGE] vectorized + BROADCAST [RS_157] + Group By Operator [GBY_156] (rows=1 width=12) Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] - <-Map 15 [CUSTOM_SIMPLE_EDGE] vectorized - PARTITION_ONLY_SHUFFLE [RS_159] - Group By Operator [GBY_158] (rows=1 width=12) + <-Map 14 [CUSTOM_SIMPLE_EDGE] vectorized + PARTITION_ONLY_SHUFFLE [RS_155] + Group By Operator [GBY_154] (rows=1 width=12) Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] - Select Operator [SEL_157] (rows=130 width=4) + Select Operator [SEL_153] (rows=130 width=4) Output:["_col0"] - Please refer to the previous Select Operator [SEL_155] + Please refer to the previous Select Operator [SEL_151] <-Reducer 9 [SIMPLE_EDGE] SHUFFLE [RS_29] PartitionCols:_col0 - Merge Join Operator [MERGEJOIN_129] (rows=462007 width=104) - Conds:RS_146._col1=RS_153._col0(Left Outer),Output:["_col0","_col1","_col3"] + Merge Join Operator [MERGEJOIN_129] (rows=462007 width=4) + Conds:RS_144._col1=RS_149._col0(Left Outer),Output:["_col0","_col3"] <-Map 8 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_146] + SHUFFLE [RS_144] PartitionCols:_col1 - Select Operator [SEL_143] (rows=462000 width=104) + Select Operator [SEL_142] (rows=462000 width=104) Output:["_col0","_col1"] Filter Operator [FIL_140] (rows=462000 width=104) predicate:i_item_sk is not null - Please refer to the previous TableScan [TS_6] + TableScan [TS_6] (rows=462000 width=104) + default@item,item,Tbl:COMPLETE,Col:COMPLETE,Output:["i_item_sk","i_item_id"] <-Reducer 11 [ONE_TO_ONE_EDGE] vectorized - FORWARD [RS_153] + FORWARD [RS_149] PartitionCols:_col0 - Select Operator [SEL_152] (rows=5 width=104) + Select Operator [SEL_148] (rows=5 width=104) Output:["_col0","_col1"] - Group By Operator [GBY_151] (rows=5 width=100) + Group By Operator [GBY_147] (rows=5 width=100) Output:["_col0"],keys:KEY._col0 <-Map 8 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_149] + SHUFFLE [RS_146] PartitionCols:_col0 - Group By Operator [GBY_147] (rows=5 width=100) + Group By Operator [GBY_145] (rows=5 width=100) Output:["_col0"],keys:i_item_id - Select Operator [SEL_144] (rows=11 width=104) + Select Operator [SEL_143] (rows=11 width=104) Output:["i_item_id"] Filter Operator [FIL_141] (rows=11 width=104) predicate:(i_item_sk) IN (2, 3, 5, 7, 11, 13, 17, 19, 23, 29) diff --git ql/src/test/results/clientpositive/perf/tez/query53.q.out ql/src/test/results/clientpositive/perf/tez/query53.q.out index e9153f3a06..6cd8a7dd2d 100644 --- ql/src/test/results/clientpositive/perf/tez/query53.q.out +++ ql/src/test/results/clientpositive/perf/tez/query53.q.out @@ -88,7 +88,7 @@ Stage-0 Select Operator [SEL_30] (rows=25 width=228) Output:["_col0","_col1","_col2"] Filter Operator [FIL_46] (rows=25 width=228) - predicate:CASE WHEN ((avg_window_0 > 0)) THEN (((abs((_col2 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (null) END + predicate:CASE WHEN ((avg_window_0 > 0)) THEN (((abs((_col2 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (false) END Select Operator [SEL_29] (rows=50 width=116) Output:["avg_window_0","_col0","_col2"] PTF Operator [PTF_28] (rows=50 width=116) diff --git ql/src/test/results/clientpositive/perf/tez/query63.q.out ql/src/test/results/clientpositive/perf/tez/query63.q.out index 0bdd48b728..2627d805e3 100644 --- ql/src/test/results/clientpositive/perf/tez/query63.q.out +++ ql/src/test/results/clientpositive/perf/tez/query63.q.out @@ -90,7 +90,7 @@ Stage-0 Select Operator [SEL_30] (rows=65 width=228) Output:["_col0","_col1","_col2"] Filter Operator [FIL_46] (rows=65 width=228) - predicate:CASE WHEN ((avg_window_0 > 0)) THEN (((abs((_col2 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (null) END + predicate:CASE WHEN ((avg_window_0 > 0)) THEN (((abs((_col2 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (false) END Select Operator [SEL_29] (rows=130 width=116) Output:["avg_window_0","_col0","_col2"] PTF Operator [PTF_28] (rows=130 width=116) diff --git ql/src/test/results/clientpositive/perf/tez/query70.q.out ql/src/test/results/clientpositive/perf/tez/query70.q.out index 8d9d06dd48..2f8303a1c7 100644 --- ql/src/test/results/clientpositive/perf/tez/query70.q.out +++ ql/src/test/results/clientpositive/perf/tez/query70.q.out @@ -109,6 +109,16 @@ Stage-0 SHUFFLE [RS_166] Select Operator [SEL_165] (rows=720 width=492) Output:["_col0","_col1","_col2","_col3","_col4","_col5"] +<<<<<<< HEAD + PTF Operator [PTF_163] (rows=720 width=304) + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col2 DESC NULLS LAST","partition by:":"(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END"}] + Select Operator [SEL_162] (rows=720 width=304) + Output:["_col0","_col1","_col2","_col3"] + <-Reducer 5 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_161] + PartitionCols:(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END + Select Operator [SEL_160] (rows=720 width=304) +======= PTF Operator [PTF_164] (rows=720 width=304) Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col2 DESC NULLS LAST","partition by:":"(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END"}] Select Operator [SEL_163] (rows=720 width=304) @@ -117,6 +127,7 @@ Stage-0 SHUFFLE [RS_162] PartitionCols:(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END Select Operator [SEL_161] (rows=720 width=304) +>>>>>>> asf/master Output:["_col0","_col1","_col2","_col3"] Group By Operator [GBY_160] (rows=720 width=304) Output:["_col0","_col1","_col2","_col3"],aggregations:["sum(VALUE._col0)"],keys:KEY._col0, KEY._col1, KEY._col2 diff --git ql/src/test/results/clientpositive/perf/tez/query73.q.out ql/src/test/results/clientpositive/perf/tez/query73.q.out index 352c7245ea..7b2a4aff6f 100644 --- ql/src/test/results/clientpositive/perf/tez/query73.q.out +++ ql/src/test/results/clientpositive/perf/tez/query73.q.out @@ -103,7 +103,7 @@ Stage-0 SHUFFLE [RS_124] PartitionCols:_col1 Filter Operator [FIL_123] (rows=5 width=12) - predicate:_col2 BETWEEN 1 AND 5 + predicate:_col2 BETWEEN 1L AND 5L Select Operator [SEL_122] (rows=788766 width=12) Output:["_col0","_col1","_col2"] Group By Operator [GBY_121] (rows=788766 width=12) diff --git ql/src/test/results/clientpositive/perf/tez/query74.q.out ql/src/test/results/clientpositive/perf/tez/query74.q.out index 20aade2974..fd0ed306d0 100644 --- ql/src/test/results/clientpositive/perf/tez/query74.q.out +++ ql/src/test/results/clientpositive/perf/tez/query74.q.out @@ -171,7 +171,7 @@ Stage-0 Select Operator [SEL_92] (rows=12248093 width=280) Output:["_col0","_col1","_col2"] Filter Operator [FIL_91] (rows=12248093 width=732) - predicate:CASE WHEN (_col3 is not null) THEN (CASE WHEN (_col6) THEN (((_col1 / _col5) > (_col10 / _col3))) ELSE ((null > (_col10 / _col3))) END) ELSE (CASE WHEN (_col6) THEN (((_col1 / _col5) > null)) ELSE (null) END) END + predicate:CASE WHEN (_col3 is not null) THEN (CASE WHEN (_col6) THEN (((_col1 / _col5) > (_col10 / _col3))) ELSE (null) END) ELSE (null) END Merge Join Operator [MERGEJOIN_287] (rows=24496186 width=732) Conds:RS_88._col2=RS_350._col0(Inner),Output:["_col1","_col3","_col5","_col6","_col7","_col8","_col9","_col10"] <-Reducer 20 [SIMPLE_EDGE] vectorized diff --git ql/src/test/results/clientpositive/perf/tez/query78.q.out ql/src/test/results/clientpositive/perf/tez/query78.q.out index 3d938e1c8e..3f4723121a 100644 --- ql/src/test/results/clientpositive/perf/tez/query78.q.out +++ ql/src/test/results/clientpositive/perf/tez/query78.q.out @@ -152,194 +152,202 @@ Reducer 9 <- Reducer 8 (SIMPLE_EDGE) Stage-0 Fetch Operator - limit:100 + limit:-1 Stage-1 Reducer 6 vectorized - File Output Operator [FS_238] - Limit [LIM_237] (rows=100 width=484) - Number of rows:100 - Select Operator [SEL_236] (rows=232433056973 width=483) - Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9"] - <-Reducer 5 [SIMPLE_EDGE] - SHUFFLE [RS_73] - Select Operator [SEL_72] (rows=232433056973 width=719) - Output:["_col0","_col1","_col6","_col7","_col8","_col9","_col10","_col11","_col12"] - Filter Operator [FIL_71] (rows=232433056973 width=701) - predicate:CASE WHEN (_col11 is not null) THEN ((_col11 > 0L)) ELSE (false) END - Merge Join Operator [MERGEJOIN_191] (rows=464866113946 width=701) - Conds:RS_68._col1=RS_235._col0(Left Outer),Output:["_col0","_col1","_col2","_col3","_col4","_col7","_col8","_col9","_col11","_col12","_col13"] + File Output Operator [FS_275] + Select Operator [SEL_274] (rows=100 width=484) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8","_col9"] + Limit [LIM_273] (rows=100 width=720) + Number of rows:100 + Select Operator [SEL_272] (rows=101774621265 width=719) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8"] + <-Reducer 5 [SIMPLE_EDGE] + SHUFFLE [RS_75] + Select Operator [SEL_74] (rows=101774621265 width=719) + Output:["_col0","_col1","_col6","_col7","_col8","_col9","_col10","_col11","_col12"] + Merge Join Operator [MERGEJOIN_222] (rows=101774621265 width=711) + Conds:RS_71._col1=RS_271._col0(Inner),Output:["_col0","_col1","_col2","_col3","_col4","_col7","_col8","_col9","_col11","_col12","_col13","_col14"] <-Reducer 12 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_235] + SHUFFLE [RS_271] PartitionCols:_col0 - Select Operator [SEL_234] (rows=50796051 width=235) - Output:["_col0","_col1","_col2","_col3"] - Group By Operator [GBY_233] (rows=50796051 width=239) - Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)"],keys:KEY._col0, KEY._col1 - <-Reducer 11 [SIMPLE_EDGE] - SHUFFLE [RS_65] - PartitionCols:_col0, _col1 - Group By Operator [GBY_64] (rows=50796051 width=239) - Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(_col4)","sum(_col5)","sum(_col6)"],keys:_col2, _col3 - Merge Join Operator [MERGEJOIN_189] (rows=50796051 width=233) - Conds:RS_198._col0=RS_61._col0(Inner),Output:["_col2","_col3","_col4","_col5","_col6"] - <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_198] - PartitionCols:_col0 - Select Operator [SEL_193] (rows=652 width=4) - Output:["_col0"] - Filter Operator [FIL_192] (rows=652 width=8) - predicate:((d_year = 2000) and d_date_sk is not null) - TableScan [TS_0] (rows=73049 width=8) - default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year"] - <-Reducer 21 [SIMPLE_EDGE] - SHUFFLE [RS_61] - PartitionCols:_col0 - Select Operator [SEL_59] (rows=143274863 width=239) - Output:["_col0","_col1","_col2","_col3","_col4","_col5"] - Filter Operator [FIL_58] (rows=143274863 width=240) - predicate:_col8 is null - Merge Join Operator [MERGEJOIN_188] (rows=234359952 width=240) - Conds:RS_230._col2, _col3=RS_232._col0, _col1(Left Outer),Output:["_col0","_col1","_col2","_col4","_col5","_col6","_col8"] - <-Map 20 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_230] - PartitionCols:_col2, _col3 - Select Operator [SEL_229] (rows=143274863 width=242) - Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] - Filter Operator [FIL_228] (rows=143274863 width=242) - predicate:((cs_item_sk = cs_item_sk) and (cs_sold_date_sk BETWEEN DynamicValue(RS_60_date_dim_d_date_sk_min) AND DynamicValue(RS_60_date_dim_d_date_sk_max) and in_bloom_filter(cs_sold_date_sk, DynamicValue(RS_60_date_dim_d_date_sk_bloom_filter))) and cs_sold_date_sk is not null) - TableScan [TS_50] (rows=287989836 width=242) - default@catalog_sales,catalog_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["cs_sold_date_sk","cs_bill_customer_sk","cs_item_sk","cs_order_number","cs_quantity","cs_wholesale_cost","cs_sales_price"] - <-Reducer 13 [BROADCAST_EDGE] vectorized - BROADCAST [RS_227] - Group By Operator [GBY_226] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] - <-Map 1 [CUSTOM_SIMPLE_EDGE] vectorized - SHUFFLE [RS_205] - Group By Operator [GBY_202] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] - Select Operator [SEL_199] (rows=652 width=4) - Output:["_col0"] - Please refer to the previous Select Operator [SEL_193] - <-Map 22 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_232] - PartitionCols:_col0, _col1 - Select Operator [SEL_231] (rows=28798881 width=8) - Output:["_col0","_col1"] - TableScan [TS_53] (rows=28798881 width=8) - default@catalog_returns,catalog_returns,Tbl:COMPLETE,Col:COMPLETE,Output:["cr_item_sk","cr_order_number"] + Select Operator [SEL_270] (rows=16847407 width=243) + Output:["_col0","_col1","_col2","_col3","_col4"] + Filter Operator [FIL_269] (rows=16847407 width=239) + predicate:(_col2 > 0L) + Select Operator [SEL_268] (rows=50542222 width=239) + Output:["_col1","_col2","_col3","_col4"] + Group By Operator [GBY_267] (rows=50542222 width=239) + Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)"],keys:KEY._col0, KEY._col1 + <-Reducer 11 [SIMPLE_EDGE] + SHUFFLE [RS_63] + PartitionCols:_col0, _col1 + Group By Operator [GBY_62] (rows=50542222 width=239) + Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(_col4)","sum(_col5)","sum(_col6)"],keys:_col2, _col3 + Merge Join Operator [MERGEJOIN_220] (rows=50542222 width=233) + Conds:RS_229._col0=RS_59._col0(Inner),Output:["_col2","_col3","_col4","_col5","_col6"] + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_229] + PartitionCols:_col0 + Select Operator [SEL_224] (rows=652 width=4) + Output:["_col0"] + Filter Operator [FIL_223] (rows=652 width=8) + predicate:((d_year = 2000) and d_date_sk is not null) + TableScan [TS_0] (rows=73049 width=8) + default@date_dim,date_dim,Tbl:COMPLETE,Col:COMPLETE,Output:["d_date_sk","d_year"] + <-Reducer 21 [SIMPLE_EDGE] + SHUFFLE [RS_59] + PartitionCols:_col0 + Select Operator [SEL_57] (rows=142558915 width=239) + Output:["_col0","_col1","_col2","_col3","_col4","_col5"] + Filter Operator [FIL_56] (rows=142558915 width=240) + predicate:_col8 is null + Merge Join Operator [MERGEJOIN_219] (rows=233188849 width=240) + Conds:RS_264._col2, _col3=RS_266._col0, _col1(Left Outer),Output:["_col0","_col1","_col2","_col4","_col5","_col6","_col8"] + <-Map 20 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_264] + PartitionCols:_col2, _col3 + Select Operator [SEL_263] (rows=142558915 width=242) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] + Filter Operator [FIL_262] (rows=142558915 width=242) + predicate:((cs_item_sk = cs_item_sk) and (cs_sold_date_sk BETWEEN DynamicValue(RS_58_date_dim_d_date_sk_min) AND DynamicValue(RS_58_date_dim_d_date_sk_max) and in_bloom_filter(cs_sold_date_sk, DynamicValue(RS_58_date_dim_d_date_sk_bloom_filter))) and cs_bill_customer_sk is not null and cs_sold_date_sk is not null) + TableScan [TS_48] (rows=287989836 width=242) + default@catalog_sales,catalog_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["cs_sold_date_sk","cs_bill_customer_sk","cs_item_sk","cs_order_number","cs_quantity","cs_wholesale_cost","cs_sales_price"] + <-Reducer 13 [BROADCAST_EDGE] vectorized + BROADCAST [RS_261] + Group By Operator [GBY_260] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] + <-Map 1 [CUSTOM_SIMPLE_EDGE] vectorized + SHUFFLE [RS_236] + Group By Operator [GBY_233] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] + Select Operator [SEL_230] (rows=652 width=4) + Output:["_col0"] + Please refer to the previous Select Operator [SEL_224] + <-Map 22 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_266] + PartitionCols:_col0, _col1 + Select Operator [SEL_265] (rows=28798881 width=8) + Output:["_col0","_col1"] + TableScan [TS_51] (rows=28798881 width=8) + default@catalog_returns,catalog_returns,Tbl:COMPLETE,Col:COMPLETE,Output:["cr_item_sk","cr_order_number"] <-Reducer 4 [SIMPLE_EDGE] - SHUFFLE [RS_68] + SHUFFLE [RS_71] PartitionCols:_col1 - Filter Operator [FIL_45] (rows=4580227799 width=471) - predicate:CASE WHEN (_col7 is not null) THEN ((_col7 > 0L)) ELSE (false) END - Merge Join Operator [MERGEJOIN_190] (rows=9160455599 width=471) - Conds:RS_215._col1, _col0=RS_225._col1, _col0(Left Outer),Output:["_col0","_col1","_col2","_col3","_col4","_col7","_col8","_col9"] - <-Reducer 3 [ONE_TO_ONE_EDGE] vectorized - FORWARD [RS_215] - PartitionCols:_col1, _col0 - Select Operator [SEL_214] (rows=114214965 width=239) - Output:["_col0","_col1","_col2","_col3","_col4"] - Group By Operator [GBY_213] (rows=114214965 width=239) - Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)"],keys:KEY._col0, KEY._col1 - <-Reducer 2 [SIMPLE_EDGE] - SHUFFLE [RS_18] - PartitionCols:_col0, _col1 - Group By Operator [GBY_17] (rows=114214965 width=239) - Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(_col4)","sum(_col5)","sum(_col6)"],keys:_col3, _col2 - Merge Join Operator [MERGEJOIN_185] (rows=114214965 width=217) - Conds:RS_194._col0=RS_14._col0(Inner),Output:["_col2","_col3","_col4","_col5","_col6"] - <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_194] - PartitionCols:_col0 - Please refer to the previous Select Operator [SEL_193] - <-Reducer 15 [SIMPLE_EDGE] - SHUFFLE [RS_14] - PartitionCols:_col0 - Select Operator [SEL_12] (rows=319876350 width=233) - Output:["_col0","_col1","_col2","_col3","_col4","_col5"] - Filter Operator [FIL_11] (rows=319876350 width=235) - predicate:_col8 is null - Merge Join Operator [MERGEJOIN_184] (rows=883006376 width=235) - Conds:RS_210._col1, _col3=RS_212._col0, _col1(Left Outer),Output:["_col0","_col1","_col2","_col4","_col5","_col6","_col8"] - <-Map 14 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_210] - PartitionCols:_col1, _col3 - Select Operator [SEL_209] (rows=550076554 width=233) - Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] - Filter Operator [FIL_208] (rows=550076554 width=233) - predicate:((ss_sold_date_sk BETWEEN DynamicValue(RS_13_date_dim_d_date_sk_min) AND DynamicValue(RS_13_date_dim_d_date_sk_max) and in_bloom_filter(ss_sold_date_sk, DynamicValue(RS_13_date_dim_d_date_sk_bloom_filter))) and ss_sold_date_sk is not null) - TableScan [TS_3] (rows=575995635 width=233) - default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_item_sk","ss_customer_sk","ss_ticket_number","ss_quantity","ss_wholesale_cost","ss_sales_price"] - <-Reducer 7 [BROADCAST_EDGE] vectorized - BROADCAST [RS_207] - Group By Operator [GBY_206] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] - <-Map 1 [CUSTOM_SIMPLE_EDGE] vectorized - SHUFFLE [RS_203] - Group By Operator [GBY_200] (rows=1 width=12) - Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] - Select Operator [SEL_195] (rows=652 width=4) - Output:["_col0"] - Please refer to the previous Select Operator [SEL_193] - <-Map 16 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_212] - PartitionCols:_col0, _col1 - Select Operator [SEL_211] (rows=57591150 width=8) - Output:["_col0","_col1"] + Merge Join Operator [MERGEJOIN_221] (rows=3053485049 width=471) + Conds:RS_247._col1, _col0=RS_259._col1, _col0(Inner),Output:["_col0","_col1","_col2","_col3","_col4","_col7","_col8","_col9"] + <-Reducer 3 [ONE_TO_ONE_EDGE] vectorized + FORWARD [RS_247] + PartitionCols:_col1, _col0 + Select Operator [SEL_246] (rows=114214965 width=239) + Output:["_col0","_col1","_col2","_col3","_col4"] + Group By Operator [GBY_245] (rows=114214965 width=239) + Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)"],keys:KEY._col0, KEY._col1 + <-Reducer 2 [SIMPLE_EDGE] + SHUFFLE [RS_19] + PartitionCols:_col0, _col1 + Group By Operator [GBY_18] (rows=114214965 width=239) + Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(_col4)","sum(_col5)","sum(_col6)"],keys:_col3, _col2 + Merge Join Operator [MERGEJOIN_216] (rows=114214965 width=218) + Conds:RS_225._col0=RS_15._col0(Inner),Output:["_col2","_col3","_col4","_col5","_col6"] + <-Map 1 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_225] + PartitionCols:_col0 + Please refer to the previous Select Operator [SEL_224] + <-Reducer 15 [SIMPLE_EDGE] + SHUFFLE [RS_15] + PartitionCols:_col0 + Select Operator [SEL_13] (rows=319876350 width=233) + Output:["_col0","_col1","_col2","_col3","_col4","_col5"] + Filter Operator [FIL_12] (rows=319876350 width=236) + predicate:_col8 is null + Merge Join Operator [MERGEJOIN_215] (rows=857669906 width=236) + Conds:RS_241._col1, _col3=RS_244._col0, _col1(Left Outer),Output:["_col0","_col1","_col2","_col4","_col5","_col6","_col8"] + <-Map 14 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_241] + PartitionCols:_col1, _col3 + Select Operator [SEL_240] (rows=525327388 width=233) + Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] + Filter Operator [FIL_239] (rows=525327388 width=233) + predicate:((ss_sold_date_sk BETWEEN DynamicValue(RS_14_date_dim_d_date_sk_min) AND DynamicValue(RS_14_date_dim_d_date_sk_max) and in_bloom_filter(ss_sold_date_sk, DynamicValue(RS_14_date_dim_d_date_sk_bloom_filter))) and ss_customer_sk is not null and ss_item_sk is not null and ss_sold_date_sk is not null) + TableScan [TS_3] (rows=575995635 width=233) + default@store_sales,store_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ss_sold_date_sk","ss_item_sk","ss_customer_sk","ss_ticket_number","ss_quantity","ss_wholesale_cost","ss_sales_price"] + <-Reducer 7 [BROADCAST_EDGE] vectorized + BROADCAST [RS_238] + Group By Operator [GBY_237] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] + <-Map 1 [CUSTOM_SIMPLE_EDGE] vectorized + SHUFFLE [RS_234] + Group By Operator [GBY_231] (rows=1 width=12) + Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] + Select Operator [SEL_226] (rows=652 width=4) + Output:["_col0"] + Please refer to the previous Select Operator [SEL_224] + <-Map 16 [SIMPLE_EDGE] vectorized + SHUFFLE [RS_244] + PartitionCols:_col0, _col1 + Select Operator [SEL_243] (rows=57591150 width=8) + Output:["_col0","_col1"] + Filter Operator [FIL_242] (rows=57591150 width=8) + predicate:sr_item_sk is not null TableScan [TS_6] (rows=57591150 width=8) default@store_returns,store_returns,Tbl:COMPLETE,Col:COMPLETE,Output:["sr_item_sk","sr_ticket_number"] - <-Reducer 9 [ONE_TO_ONE_EDGE] vectorized - FORWARD [RS_225] - PartitionCols:_col1, _col0 - Select Operator [SEL_224] (rows=40539971 width=239) - Output:["_col0","_col1","_col2","_col3","_col4"] - Group By Operator [GBY_223] (rows=40539971 width=239) + <-Reducer 9 [ONE_TO_ONE_EDGE] vectorized + FORWARD [RS_259] + PartitionCols:_col1, _col0 + Select Operator [SEL_258] (rows=13513323 width=239) + Output:["_col0","_col1","_col2","_col3","_col4"] + Filter Operator [FIL_257] (rows=13513323 width=239) + predicate:(_col2 > 0L) + Group By Operator [GBY_256] (rows=40539971 width=239) Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(VALUE._col0)","sum(VALUE._col1)","sum(VALUE._col2)"],keys:KEY._col0, KEY._col1 <-Reducer 8 [SIMPLE_EDGE] - SHUFFLE [RS_39] + SHUFFLE [RS_41] PartitionCols:_col0, _col1 - Group By Operator [GBY_38] (rows=40539971 width=239) + Group By Operator [GBY_40] (rows=40539971 width=239) Output:["_col0","_col1","_col2","_col3","_col4"],aggregations:["sum(_col4)","sum(_col5)","sum(_col6)"],keys:_col3, _col2 - Merge Join Operator [MERGEJOIN_187] (rows=40539971 width=235) - Conds:RS_196._col0=RS_35._col0(Inner),Output:["_col2","_col3","_col4","_col5","_col6"] + Merge Join Operator [MERGEJOIN_218] (rows=40539971 width=235) + Conds:RS_227._col0=RS_37._col0(Inner),Output:["_col2","_col3","_col4","_col5","_col6"] <-Map 1 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_196] + SHUFFLE [RS_227] PartitionCols:_col0 - Please refer to the previous Select Operator [SEL_193] + Please refer to the previous Select Operator [SEL_224] <-Reducer 18 [SIMPLE_EDGE] - SHUFFLE [RS_35] + SHUFFLE [RS_37] PartitionCols:_col0 - Select Operator [SEL_33] (rows=113538342 width=239) + Select Operator [SEL_35] (rows=113538342 width=239) Output:["_col0","_col1","_col2","_col3","_col4","_col5"] - Filter Operator [FIL_32] (rows=113538342 width=242) + Filter Operator [FIL_34] (rows=113538342 width=242) predicate:_col8 is null - Merge Join Operator [MERGEJOIN_186] (rows=254679677 width=242) - Conds:RS_220._col1, _col3=RS_222._col0, _col1(Left Outer),Output:["_col0","_col1","_col2","_col4","_col5","_col6","_col8"] + Merge Join Operator [MERGEJOIN_217] (rows=254644510 width=242) + Conds:RS_252._col1, _col3=RS_255._col0, _col1(Left Outer),Output:["_col0","_col1","_col2","_col4","_col5","_col6","_col8"] <-Map 17 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_220] + SHUFFLE [RS_252] PartitionCols:_col1, _col3 - Select Operator [SEL_219] (rows=143966864 width=243) + Select Operator [SEL_251] (rows=143930993 width=243) Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6"] - Filter Operator [FIL_218] (rows=143966864 width=243) - predicate:((ws_sold_date_sk BETWEEN DynamicValue(RS_34_date_dim_d_date_sk_min) AND DynamicValue(RS_34_date_dim_d_date_sk_max) and in_bloom_filter(ws_sold_date_sk, DynamicValue(RS_34_date_dim_d_date_sk_bloom_filter))) and ws_sold_date_sk is not null) - TableScan [TS_24] (rows=144002668 width=243) + Filter Operator [FIL_250] (rows=143930993 width=243) + predicate:((ws_sold_date_sk BETWEEN DynamicValue(RS_36_date_dim_d_date_sk_min) AND DynamicValue(RS_36_date_dim_d_date_sk_max) and in_bloom_filter(ws_sold_date_sk, DynamicValue(RS_36_date_dim_d_date_sk_bloom_filter))) and ws_bill_customer_sk is not null and ws_item_sk is not null and ws_sold_date_sk is not null) + TableScan [TS_25] (rows=144002668 width=243) default@web_sales,web_sales,Tbl:COMPLETE,Col:COMPLETE,Output:["ws_sold_date_sk","ws_item_sk","ws_bill_customer_sk","ws_order_number","ws_quantity","ws_wholesale_cost","ws_sales_price"] <-Reducer 10 [BROADCAST_EDGE] vectorized - BROADCAST [RS_217] - Group By Operator [GBY_216] (rows=1 width=12) + BROADCAST [RS_249] + Group By Operator [GBY_248] (rows=1 width=12) Output:["_col0","_col1","_col2"],aggregations:["min(VALUE._col0)","max(VALUE._col1)","bloom_filter(VALUE._col2, expectedEntries=1000000)"] <-Map 1 [CUSTOM_SIMPLE_EDGE] vectorized - SHUFFLE [RS_204] - Group By Operator [GBY_201] (rows=1 width=12) + SHUFFLE [RS_235] + Group By Operator [GBY_232] (rows=1 width=12) Output:["_col0","_col1","_col2"],aggregations:["min(_col0)","max(_col0)","bloom_filter(_col0, expectedEntries=1000000)"] - Select Operator [SEL_197] (rows=652 width=4) + Select Operator [SEL_228] (rows=652 width=4) Output:["_col0"] - Please refer to the previous Select Operator [SEL_193] + Please refer to the previous Select Operator [SEL_224] <-Map 19 [SIMPLE_EDGE] vectorized - SHUFFLE [RS_222] + SHUFFLE [RS_255] PartitionCols:_col0, _col1 - Select Operator [SEL_221] (rows=14398467 width=8) + Select Operator [SEL_254] (rows=14398467 width=8) Output:["_col0","_col1"] - TableScan [TS_27] (rows=14398467 width=8) - default@web_returns,web_returns,Tbl:COMPLETE,Col:COMPLETE,Output:["wr_item_sk","wr_order_number"] + Filter Operator [FIL_253] (rows=14398467 width=8) + predicate:wr_item_sk is not null + TableScan [TS_28] (rows=14398467 width=8) + default@web_returns,web_returns,Tbl:COMPLETE,Col:COMPLETE,Output:["wr_item_sk","wr_order_number"] diff --git ql/src/test/results/clientpositive/perf/tez/query86.q.out ql/src/test/results/clientpositive/perf/tez/query86.q.out index 2d6d545a5b..dd5b84feb1 100644 --- ql/src/test/results/clientpositive/perf/tez/query86.q.out +++ ql/src/test/results/clientpositive/perf/tez/query86.q.out @@ -82,12 +82,12 @@ Stage-0 Select Operator [SEL_80] (rows=3060 width=490) Output:["_col0","_col1","_col2","_col3","_col4","_col5"] PTF Operator [PTF_79] (rows=3060 width=302) - Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col2 DESC NULLS LAST","partition by:":"(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END"}] + Function definitions:[{},{"name:":"windowingtablefunction","order by:":"_col2 DESC NULLS LAST","partition by:":"(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END"}] Select Operator [SEL_78] (rows=3060 width=302) Output:["_col0","_col1","_col2","_col3"] <-Reducer 4 [SIMPLE_EDGE] vectorized SHUFFLE [RS_77] - PartitionCols:(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = 0)) THEN (_col0) ELSE (CAST( null AS STRING)) END + PartitionCols:(grouping(_col3, 1) + grouping(_col3, 0)), CASE WHEN ((grouping(_col3, 0) = UDFToLong(0))) THEN (_col0) ELSE (CAST( null AS STRING)) END Select Operator [SEL_76] (rows=3060 width=302) Output:["_col0","_col1","_col2","_col3"] Group By Operator [GBY_75] (rows=3060 width=302) diff --git ql/src/test/results/clientpositive/perf/tez/query88.q.out ql/src/test/results/clientpositive/perf/tez/query88.q.out index e02ff3715b..c8e2e6fba4 100644 --- ql/src/test/results/clientpositive/perf/tez/query88.q.out +++ ql/src/test/results/clientpositive/perf/tez/query88.q.out @@ -320,7 +320,7 @@ Stage-0 Select Operator [SEL_660] (rows=817 width=4) Output:["_col0"] Filter Operator [FIL_659] (rows=817 width=12) - predicate:((((hd_dep_count = 3) and hd_vehicle_count is not null) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and (hd_dep_count) IN (3, 0, 1) and (hd_vehicle_count <= 5) and hd_demo_sk is not null) + predicate:((((hd_dep_count = 3) and (hd_vehicle_count <= 5)) or ((hd_dep_count = 0) and (hd_vehicle_count <= 2)) or ((hd_dep_count = 1) and (hd_vehicle_count <= 3))) and ((hd_vehicle_count <= 5) or (hd_vehicle_count <= 2) or (hd_vehicle_count <= 3)) and (hd_dep_count) IN (3, 0, 1) and hd_demo_sk is not null) TableScan [TS_3] (rows=7200 width=12) default@household_demographics,household_demographics,Tbl:COMPLETE,Col:COMPLETE,Output:["hd_demo_sk","hd_dep_count","hd_vehicle_count"] <-Map 56 [SIMPLE_EDGE] vectorized diff --git ql/src/test/results/clientpositive/perf/tez/query89.q.out ql/src/test/results/clientpositive/perf/tez/query89.q.out index 8501822cd2..015600e312 100644 --- ql/src/test/results/clientpositive/perf/tez/query89.q.out +++ ql/src/test/results/clientpositive/perf/tez/query89.q.out @@ -89,7 +89,7 @@ Stage-0 Select Operator [SEL_108] (rows=4804228 width=801) Output:["_col0","_col1","_col2","_col3","_col4","_col5","_col6","_col7","_col8"] Filter Operator [FIL_107] (rows=4804228 width=689) - predicate:CASE WHEN ((avg_window_0 <> 0)) THEN (((abs((_col6 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (null) END + predicate:CASE WHEN ((avg_window_0 <> 0)) THEN (((abs((_col6 - avg_window_0)) / avg_window_0) > 0.1)) ELSE (false) END Select Operator [SEL_106] (rows=9608456 width=577) Output:["avg_window_0","_col0","_col1","_col2","_col3","_col4","_col5","_col6"] PTF Operator [PTF_105] (rows=9608456 width=577) diff --git ql/src/test/results/clientpositive/pointlookup.q.out ql/src/test/results/clientpositive/pointlookup.q.out index 35ece97d90..19f35c3706 100644 --- ql/src/test/results/clientpositive/pointlookup.q.out +++ ql/src/test/results/clientpositive/pointlookup.q.out @@ -352,6 +352,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@inoutputopt #### A masked pattern was here #### 11 +Warning: Shuffle Join JOIN[8][tables = [$hdt$_0, $hdt$_1]] in Stage 'Stage-1:MAPRED' is a cross product PREHOOK: query: select orOutput.key, inOutput.key from orOutput full outer join inOutput on (orOutput.key = inOutput.key) where orOutput.key = null @@ -368,6 +369,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@inoutput POSTHOOK: Input: default@oroutput #### A masked pattern was here #### +Warning: Shuffle Join JOIN[8][tables = [$hdt$_0, $hdt$_1]] in Stage 'Stage-1:MAPRED' is a cross product PREHOOK: query: select orOutput.key, inOutputOpt.key from orOutput full outer join inOutputOpt on (orOutput.key = inOutputOpt.key) where orOutput.key = null diff --git ql/src/test/results/clientpositive/pointlookup2.q.out ql/src/test/results/clientpositive/pointlookup2.q.out index 42d2c787a0..3c3254c63f 100644 --- ql/src/test/results/clientpositive/pointlookup2.q.out +++ ql/src/test/results/clientpositive/pointlookup2.q.out @@ -294,7 +294,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@pcr_t1_n2 POSTHOOK: Input: default@pcr_t1_n2@ds=2000-04-08 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS STRING) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-08' AS STRING) AS `ds1` +OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds1` FROM (SELECT * FROM (SELECT `key`, `value` FROM `default`.`pcr_t1_n2` @@ -534,7 +534,7 @@ POSTHOOK: Input: default@pcr_t1_n2 POSTHOOK: Input: default@pcr_t1_n2@ds=2000-04-08 POSTHOOK: Input: default@pcr_t1_n2@ds=2000-04-09 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS STRING) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-09' AS STRING) AS `ds1` +OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-09' AS VARCHAR(65536)) AS `ds1` FROM (SELECT * FROM (SELECT `key`, `value` FROM `default`.`pcr_t1_n2` @@ -826,6 +826,14 @@ POSTHOOK: Input: default@pcr_t1_n2@ds=2000-04-08 POSTHOOK: Input: default@pcr_t1_n2@ds=2000-04-09 POSTHOOK: Input: default@pcr_t2_n0 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `t0`.`key`, `t0`.`value`, `t0`.`ds`, `t2`.`ds` AS `ds1`, `t2`.`key` AS `key1`, `t2`.`value` AS `value1` +FROM (SELECT `key`, `value`, `ds`, `ds` = '2000-04-08' AS `=`, `ds` = '2000-04-09' AS `=7` +FROM `default`.`pcr_t1_n2` +WHERE `ds` = '2000-04-08' OR `ds` = '2000-04-09') AS `t0` +INNER JOIN (SELECT `ds`, `key`, `value`, `key` = 1 AS `=`, `key` = 2 AS `=7` +FROM `default`.`pcr_t2_n0` +WHERE `key` = 1 OR `key` = 2) AS `t2` ON `t0`.`=` AND `t2`.`=` OR `t0`.`=7` AND `t2`.`=7` +ORDER BY `t2`.`key`, `t2`.`value`, `t0`.`ds` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-2 depends on stages: Stage-1 @@ -1160,6 +1168,14 @@ POSTHOOK: Input: default@pcr_t1_n2@ds=2000-04-09 POSTHOOK: Input: default@pcr_t1_n2@ds=2000-04-10 POSTHOOK: Input: default@pcr_t2_n0 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `t0`.`key`, `t0`.`value`, `t0`.`ds`, `t2`.`ds` AS `ds1`, `t2`.`key` AS `key1`, `t2`.`value` AS `value1` +FROM (SELECT `key`, `value`, `ds`, `key` = 1 AS `=`, `key` = 2 AS `=7` +FROM `default`.`pcr_t1_n2` +WHERE `key` = 1 OR `key` = 2) AS `t0` +INNER JOIN (SELECT `ds`, `key`, `value`, `ds` = '2000-04-08' AS `=`, `ds` = '2000-04-09' AS `=7` +FROM `default`.`pcr_t2_n0` +WHERE `ds` = '2000-04-08' OR `ds` = '2000-04-09') AS `t2` ON `t2`.`=` AND `t0`.`=` OR `t2`.`=7` AND `t0`.`=7` +ORDER BY `t0`.`key`, `t0`.`value`, `t2`.`ds` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-2 depends on stages: Stage-1 @@ -1720,6 +1736,10 @@ POSTHOOK: Input: default@pcr_t1_n2 POSTHOOK: Input: default@pcr_t1_n2@ds=2000-04-08 POSTHOOK: Input: default@pcr_t1_n2@ds=2000-04-09 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, `ds` +FROM `default`.`pcr_t1_n2` +WHERE ROW(`key`, `ds`) IN (ROW(1, '2000-04-08'), ROW(2, '2000-04-09')) +ORDER BY `key`, `value`, `ds` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1904,7 +1924,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@pcr_t1_n2 POSTHOOK: Input: default@pcr_t1_n2@ds=2000-04-08 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS STRING) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-08' AS STRING) AS `ds1` +OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds1` FROM (SELECT * FROM (SELECT `key`, `value` FROM `default`.`pcr_t1_n2` @@ -2144,7 +2164,7 @@ POSTHOOK: Input: default@pcr_t1_n2 POSTHOOK: Input: default@pcr_t1_n2@ds=2000-04-08 POSTHOOK: Input: default@pcr_t1_n2@ds=2000-04-09 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS STRING) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-09' AS STRING) AS `ds1` +OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-09' AS VARCHAR(65536)) AS `ds1` FROM (SELECT * FROM (SELECT `key`, `value` FROM `default`.`pcr_t1_n2` diff --git ql/src/test/results/clientpositive/pointlookup3.q.out ql/src/test/results/clientpositive/pointlookup3.q.out index a3056a515e..4a79e275ad 100644 --- ql/src/test/results/clientpositive/pointlookup3.q.out +++ ql/src/test/results/clientpositive/pointlookup3.q.out @@ -250,7 +250,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@pcr_t1_n1 POSTHOOK: Input: default@pcr_t1_n1@ds1=2000-04-08/ds2=2001-04-08 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `key`, `value`, `ds1`, CAST('2001-04-08' AS STRING) AS `ds2` +OPTIMIZED SQL: SELECT `key`, `value`, `ds1`, CAST('2001-04-08' AS VARCHAR(65536)) AS `ds2` FROM (SELECT `key`, `value`, `ds1` FROM `default`.`pcr_t1_n1` WHERE `ds2` = '2001-04-08' AND (`ds1` = '2000-04-08' AND `key` = 1 OR `ds1` = '2000-04-09' AND `key` = 2) @@ -391,7 +391,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@pcr_t1_n1 POSTHOOK: Input: default@pcr_t1_n1@ds1=2000-04-08/ds2=2001-04-08 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS STRING) AS `ds1`, `t3`.`ds2`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, `t3`.`ds1` AS `ds11`, CAST('2001-04-08' AS STRING) AS `ds21` +OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds1`, `t3`.`ds2`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, `t3`.`ds1` AS `ds11`, CAST('2001-04-08' AS VARCHAR(65536)) AS `ds21` FROM (SELECT * FROM (SELECT `key`, `value`, `ds2` FROM `default`.`pcr_t1_n1` @@ -632,7 +632,7 @@ POSTHOOK: Input: default@pcr_t1_n1 POSTHOOK: Input: default@pcr_t1_n1@ds1=2000-04-08/ds2=2001-04-08 POSTHOOK: Input: default@pcr_t1_n1@ds1=2000-04-09/ds2=2001-04-09 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS STRING) AS `ds1`, `t3`.`ds2`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-09' AS STRING) AS `ds11`, `t3`.`ds20` AS `ds21` +OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds1`, `t3`.`ds2`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-09' AS VARCHAR(65536)) AS `ds11`, `t3`.`ds20` AS `ds21` FROM (SELECT * FROM (SELECT `key`, `value`, `ds2` FROM `default`.`pcr_t1_n1` @@ -926,6 +926,14 @@ POSTHOOK: Input: default@pcr_t1_n1@ds1=2000-04-08/ds2=2001-04-08 POSTHOOK: Input: default@pcr_t1_n1@ds1=2000-04-09/ds2=2001-04-09 POSTHOOK: Input: default@pcr_t1_n1@ds1=2000-04-10/ds2=2001-04-10 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `t0`.`key`, `t0`.`value`, `t0`.`ds1`, `t0`.`ds2`, `t2`.`key` AS `key1`, `t2`.`value` AS `value1`, `t2`.`ds1` AS `ds11`, `t2`.`ds2` AS `ds21` +FROM (SELECT `key`, `value`, `ds1`, `ds2`, `ds1` = '2000-04-08' AS `=`, `ds1` = '2000-04-09' AS `=8` +FROM `default`.`pcr_t1_n1` +WHERE `ds1` = '2000-04-08' OR `ds1` = '2000-04-09') AS `t0` +INNER JOIN (SELECT `key`, `value`, `ds1`, `ds2`, `key` = 1 AS `=`, `key` = 2 AS `=8` +FROM `default`.`pcr_t1_n1` +WHERE `key` = 1 OR `key` = 2) AS `t2` ON `t0`.`=` AND `t2`.`=` OR `t0`.`=8` AND `t2`.`=8` +ORDER BY `t2`.`key`, `t2`.`value`, `t0`.`ds1` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-2 depends on stages: Stage-1 @@ -1484,6 +1492,10 @@ POSTHOOK: Input: default@pcr_t1_n1 POSTHOOK: Input: default@pcr_t1_n1@ds1=2000-04-08/ds2=2001-04-08 POSTHOOK: Input: default@pcr_t1_n1@ds1=2000-04-09/ds2=2001-04-09 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, `ds1`, `ds2` +FROM `default`.`pcr_t1_n1` +WHERE ROW(`key`, `ds1`) IN (ROW(1, '2000-04-08'), ROW(2, '2000-04-09')) +ORDER BY `key`, `value`, `ds1`, `ds2` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1670,6 +1682,11 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@pcr_t1_n1 POSTHOOK: Input: default@pcr_t1_n1@ds1=2000-04-08/ds2=2001-04-08 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, `ds1`, CAST('2001-04-08' AS VARCHAR(65536)) AS `ds2` +FROM (SELECT `key`, `value`, `ds1` +FROM `default`.`pcr_t1_n1` +WHERE ROW(`key`, `ds1`) IN (ROW(1, '2000-04-08'), ROW(2, '2000-04-09')) AND `ds2` = '2001-04-08' +ORDER BY `key`, `value`, `ds1`) AS `t1` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1806,7 +1823,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@pcr_t1_n1 POSTHOOK: Input: default@pcr_t1_n1@ds1=2000-04-08/ds2=2001-04-08 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS STRING) AS `ds1`, `t3`.`ds2`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, `t3`.`ds1` AS `ds11`, CAST('2001-04-08' AS STRING) AS `ds21` +OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds1`, `t3`.`ds2`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, `t3`.`ds1` AS `ds11`, CAST('2001-04-08' AS VARCHAR(65536)) AS `ds21` FROM (SELECT * FROM (SELECT `key`, `value`, `ds2` FROM `default`.`pcr_t1_n1` @@ -2047,7 +2064,7 @@ POSTHOOK: Input: default@pcr_t1_n1 POSTHOOK: Input: default@pcr_t1_n1@ds1=2000-04-08/ds2=2001-04-08 POSTHOOK: Input: default@pcr_t1_n1@ds1=2000-04-09/ds2=2001-04-09 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS STRING) AS `ds1`, `t3`.`ds2`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-09' AS STRING) AS `ds11`, `t3`.`ds20` AS `ds21` +OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds1`, `t3`.`ds2`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-09' AS VARCHAR(65536)) AS `ds11`, `t3`.`ds20` AS `ds21` FROM (SELECT * FROM (SELECT `key`, `value`, `ds2` FROM `default`.`pcr_t1_n1` diff --git ql/src/test/results/clientpositive/pointlookup4.q.out ql/src/test/results/clientpositive/pointlookup4.q.out index efbc8518d4..5cc84bb8b1 100644 --- ql/src/test/results/clientpositive/pointlookup4.q.out +++ ql/src/test/results/clientpositive/pointlookup4.q.out @@ -271,6 +271,10 @@ POSTHOOK: Input: default@pcr_t1_n0 POSTHOOK: Input: default@pcr_t1_n0@ds1=2000-04-08/ds2=2001-04-08 POSTHOOK: Input: default@pcr_t1_n0@ds1=2000-04-09/ds2=2001-04-09 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, `ds1`, `ds2` +FROM `default`.`pcr_t1_n0` +WHERE ROW(`key`, `ds1`, `ds2`) IN (ROW(1, '2000-04-08', '2001-04-08'), ROW(2, '2000-04-09', '2001-04-09')) +ORDER BY `key`, `value`, `ds1`, `ds2` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 diff --git ql/src/test/results/clientpositive/ppd2.q.out ql/src/test/results/clientpositive/ppd2.q.out index a9af979e4f..957d6a00b5 100644 --- ql/src/test/results/clientpositive/ppd2.q.out +++ ql/src/test/results/clientpositive/ppd2.q.out @@ -299,18 +299,18 @@ STAGE PLANS: Map Operator Tree: TableScan alias: srcpart - filterExpr: ((value like 'aaa%') or (value like 'vvv%')) (type: boolean) + filterExpr: ((value like 'aaa%') or (value like 'vvv%')) is true (type: boolean) Statistics: Num rows: 2000 Data size: 21248 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((value like 'aaa%') or (value like 'vvv%')) (type: boolean) - Statistics: Num rows: 2000 Data size: 21248 Basic stats: COMPLETE Column stats: NONE + predicate: ((value like 'aaa%') or (value like 'vvv%')) is true (type: boolean) + Statistics: Num rows: 1000 Data size: 10624 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: UDFToInteger(key) (type: int) outputColumnNames: _col0 - Statistics: Num rows: 2000 Data size: 21248 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1000 Data size: 10624 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 2000 Data size: 21248 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1000 Data size: 10624 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat diff --git ql/src/test/results/clientpositive/ppd_constant_expr.q.out ql/src/test/results/clientpositive/ppd_constant_expr.q.out index 27c13d3df3..104055be5c 100644 --- ql/src/test/results/clientpositive/ppd_constant_expr.q.out +++ ql/src/test/results/clientpositive/ppd_constant_expr.q.out @@ -34,14 +34,14 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src1 - Statistics: Num rows: 25 Data size: 191 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 25 Data size: 191 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: null (type: string), UDFToInteger((UDFToDouble(key) - null)) (type: int), null (type: double) + expressions: null (type: string), null (type: int), null (type: double) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 25 Data size: 191 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 25 Data size: 96 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 25 Data size: 191 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 25 Data size: 96 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.TextInputFormat output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat @@ -50,25 +50,25 @@ STAGE PLANS: Select Operator expressions: _col0 (type: string), _col1 (type: int), _col2 (type: double) outputColumnNames: c1, c2, c3 - Statistics: Num rows: 25 Data size: 191 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 25 Data size: 96 Basic stats: COMPLETE Column stats: COMPLETE Group By Operator aggregations: compute_stats(c1, 'hll'), compute_stats(c2, 'hll'), compute_stats(c3, 'hll') mode: hash outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 1 Data size: 1288 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 1288 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator sort order: - Statistics: Num rows: 1 Data size: 1288 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 1288 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col0 (type: struct), _col1 (type: struct), _col2 (type: struct) Reduce Operator Tree: Group By Operator aggregations: compute_stats(VALUE._col0), compute_stats(VALUE._col1), compute_stats(VALUE._col2) mode: mergepartial outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 1 Data size: 1320 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 1320 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 1320 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 1320 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -142,7 +142,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@src1 POSTHOOK: Output: default@ppd_constant_expr POSTHOOK: Lineage: ppd_constant_expr.c1 EXPRESSION [] -POSTHOOK: Lineage: ppd_constant_expr.c2 EXPRESSION [(src1)src1.FieldSchema(name:key, type:string, comment:default), ] +POSTHOOK: Lineage: ppd_constant_expr.c2 EXPRESSION [] POSTHOOK: Lineage: ppd_constant_expr.c3 EXPRESSION [] PREHOOK: query: SELECT ppd_constant_expr.* FROM ppd_constant_expr PREHOOK: type: QUERY @@ -205,14 +205,14 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src1 - Statistics: Num rows: 25 Data size: 191 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 25 Data size: 191 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: null (type: string), UDFToInteger((UDFToDouble(key) - null)) (type: int), null (type: double) + expressions: null (type: string), null (type: int), null (type: double) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 25 Data size: 191 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 25 Data size: 96 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 25 Data size: 191 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 25 Data size: 96 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.TextInputFormat output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat @@ -221,25 +221,25 @@ STAGE PLANS: Select Operator expressions: _col0 (type: string), _col1 (type: int), _col2 (type: double) outputColumnNames: c1, c2, c3 - Statistics: Num rows: 25 Data size: 191 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 25 Data size: 96 Basic stats: COMPLETE Column stats: COMPLETE Group By Operator aggregations: compute_stats(c1, 'hll'), compute_stats(c2, 'hll'), compute_stats(c3, 'hll') mode: hash outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 1 Data size: 1288 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 1288 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator sort order: - Statistics: Num rows: 1 Data size: 1288 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 1288 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col0 (type: struct), _col1 (type: struct), _col2 (type: struct) Reduce Operator Tree: Group By Operator aggregations: compute_stats(VALUE._col0), compute_stats(VALUE._col1), compute_stats(VALUE._col2) mode: mergepartial outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 1 Data size: 1320 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 1320 Basic stats: COMPLETE Column stats: COMPLETE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 1320 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 1320 Basic stats: COMPLETE Column stats: COMPLETE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -313,7 +313,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@src1 POSTHOOK: Output: default@ppd_constant_expr POSTHOOK: Lineage: ppd_constant_expr.c1 EXPRESSION [] -POSTHOOK: Lineage: ppd_constant_expr.c2 EXPRESSION [(src1)src1.FieldSchema(name:key, type:string, comment:default), ] +POSTHOOK: Lineage: ppd_constant_expr.c2 EXPRESSION [] POSTHOOK: Lineage: ppd_constant_expr.c3 EXPRESSION [] PREHOOK: query: SELECT ppd_constant_expr.* FROM ppd_constant_expr PREHOOK: type: QUERY diff --git ql/src/test/results/clientpositive/ppd_join_filter.q.out ql/src/test/results/clientpositive/ppd_join_filter.q.out index 790c4b503b..11a3caee14 100644 --- ql/src/test/results/clientpositive/ppd_join_filter.q.out +++ ql/src/test/results/clientpositive/ppd_join_filter.q.out @@ -36,7 +36,7 @@ INNER JOIN (SELECT `key`, CAST(MIN(`key`) AS DOUBLE) + CAST(2 AS DOUBLE) AS `k2` FROM `default`.`src` WHERE `key` IS NOT NULL GROUP BY `key` -HAVING CAST(MIN(`key`) AS DOUBLE) + 1 < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` +HAVING CAST(MIN(`key`) AS DOUBLE) + CAST(1 AS DOUBLE) < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` STAGE DEPENDENCIES: Stage-2 is a root stage Stage-1 depends on stages: Stage-2 @@ -385,7 +385,7 @@ INNER JOIN (SELECT `key`, CAST(MIN(`key`) AS DOUBLE) + CAST(2 AS DOUBLE) AS `k2` FROM `default`.`src` WHERE `key` IS NOT NULL GROUP BY `key` -HAVING CAST(MIN(`key`) AS DOUBLE) + 1 < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` +HAVING CAST(MIN(`key`) AS DOUBLE) + CAST(1 AS DOUBLE) < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` STAGE DEPENDENCIES: Stage-2 is a root stage Stage-1 depends on stages: Stage-2 @@ -734,7 +734,7 @@ INNER JOIN (SELECT `key`, CAST(MIN(`key`) AS DOUBLE) + CAST(2 AS DOUBLE) AS `k2` FROM `default`.`src` WHERE `key` IS NOT NULL GROUP BY `key` -HAVING CAST(MIN(`key`) AS DOUBLE) + 1 < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` +HAVING CAST(MIN(`key`) AS DOUBLE) + CAST(1 AS DOUBLE) < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` STAGE DEPENDENCIES: Stage-2 is a root stage Stage-1 depends on stages: Stage-2 @@ -1081,7 +1081,7 @@ INNER JOIN (SELECT `key`, CAST(MIN(`key`) AS DOUBLE) + CAST(2 AS DOUBLE) AS `k2` FROM `default`.`src` WHERE `key` IS NOT NULL GROUP BY `key` -HAVING CAST(MIN(`key`) AS DOUBLE) + 1 < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` +HAVING CAST(MIN(`key`) AS DOUBLE) + CAST(1 AS DOUBLE) < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` STAGE DEPENDENCIES: Stage-2 is a root stage Stage-1 depends on stages: Stage-2 diff --git ql/src/test/results/clientpositive/ppd_udf_case.q.out ql/src/test/results/clientpositive/ppd_udf_case.q.out index b791a9f510..716d9afdfb 100644 --- ql/src/test/results/clientpositive/ppd_udf_case.q.out +++ ql/src/test/results/clientpositive/ppd_udf_case.q.out @@ -1,4 +1,3 @@ -Warning: Shuffle Join JOIN[8][tables = [$hdt$_0, $hdt$_1]] in Stage 'Stage-1:MAPRED' is a cross product PREHOOK: query: EXPLAIN SELECT * FROM srcpart a JOIN srcpart b @@ -44,43 +43,47 @@ STAGE PLANS: Map Operator Tree: TableScan alias: a - filterExpr: ((ds = '2008-04-08') and (key = '27')) (type: boolean) + filterExpr: (((key = '27') is true or (null and (key = '27') is not true and (key = '38') is not true)) and key is not null) (type: boolean) Statistics: Num rows: 1000 Data size: 10624 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((ds = '2008-04-08') and (key = '27')) (type: boolean) - Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE + predicate: (((key = '27') is true or (null and (key = '27') is not true and (key = '38') is not true)) and (ds = '2008-04-08') and key is not null) (type: boolean) + Statistics: Num rows: 750 Data size: 7968 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: value (type: string), hr (type: string) - outputColumnNames: _col0, _col1 - Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE + expressions: key (type: string), value (type: string), hr (type: string) + outputColumnNames: _col0, _col1, _col2 + Statistics: Num rows: 750 Data size: 7968 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator - sort order: - Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE - value expressions: _col0 (type: string), _col1 (type: string) + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 750 Data size: 7968 Basic stats: COMPLETE Column stats: NONE + value expressions: _col1 (type: string), _col2 (type: string) TableScan alias: b - filterExpr: ((ds = '2008-04-08') and (key = '27')) (type: boolean) + filterExpr: (((key = '27') is true or (null and (key = '27') is not true and (key = '38') is not true)) and key is not null) (type: boolean) Statistics: Num rows: 1000 Data size: 10624 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((ds = '2008-04-08') and (key = '27')) (type: boolean) - Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE + predicate: (((key = '27') is true or (null and (key = '27') is not true and (key = '38') is not true)) and (ds = '2008-04-08') and key is not null) (type: boolean) + Statistics: Num rows: 750 Data size: 7968 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: value (type: string), hr (type: string) - outputColumnNames: _col0, _col1 - Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE + expressions: key (type: string), value (type: string), hr (type: string) + outputColumnNames: _col0, _col1, _col2 + Statistics: Num rows: 750 Data size: 7968 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator - sort order: - Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE - value expressions: _col0 (type: string), _col1 (type: string) + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 750 Data size: 7968 Basic stats: COMPLETE Column stats: NONE + value expressions: _col1 (type: string), _col2 (type: string) Reduce Operator Tree: Join Operator condition map: Inner Join 0 to 1 keys: - 0 - 1 - outputColumnNames: _col0, _col1, _col2, _col3 - Statistics: Num rows: 250000 Data size: 5562000 Basic stats: COMPLETE Column stats: NONE + 0 _col0 (type: string) + 1 _col0 (type: string) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 + Statistics: Num rows: 825 Data size: 8764 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false table: @@ -93,18 +96,18 @@ STAGE PLANS: Map Operator Tree: TableScan Reduce Output Operator - key expressions: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string) - sort order: ++++ - Statistics: Num rows: 250000 Data size: 5562000 Basic stats: COMPLETE Column stats: NONE + key expressions: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string) + sort order: ++++++ + Statistics: Num rows: 825 Data size: 8764 Basic stats: COMPLETE Column stats: NONE Execution mode: vectorized Reduce Operator Tree: Select Operator - expressions: '27' (type: string), KEY.reducesinkkey0 (type: string), '2008-04-08' (type: string), KEY.reducesinkkey1 (type: string), '27' (type: string), KEY.reducesinkkey2 (type: string), '2008-04-08' (type: string), KEY.reducesinkkey3 (type: string) + expressions: KEY.reducesinkkey0 (type: string), KEY.reducesinkkey1 (type: string), '2008-04-08' (type: string), KEY.reducesinkkey2 (type: string), KEY.reducesinkkey3 (type: string), KEY.reducesinkkey4 (type: string), '2008-04-08' (type: string), KEY.reducesinkkey5 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7 - Statistics: Num rows: 250000 Data size: 5562000 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 825 Data size: 8764 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 250000 Data size: 5562000 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 825 Data size: 8764 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -116,7 +119,6 @@ STAGE PLANS: Processor Tree: ListSink -Warning: Shuffle Join JOIN[8][tables = [$hdt$_0, $hdt$_1]] in Stage 'Stage-1:MAPRED' is a cross product PREHOOK: query: SELECT * FROM srcpart a JOIN srcpart b ON a.key = b.key @@ -153,7 +155,6 @@ POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 27 val_27 2008-04-08 11 27 val_27 2008-04-08 12 27 val_27 2008-04-08 12 27 val_27 2008-04-08 11 27 val_27 2008-04-08 12 27 val_27 2008-04-08 12 -Warning: Shuffle Join JOIN[8][tables = [$hdt$_0, $hdt$_1]] in Stage 'Stage-1:MAPRED' is a cross product PREHOOK: query: EXPLAIN SELECT * FROM srcpart a JOIN srcpart b @@ -199,43 +200,47 @@ STAGE PLANS: Map Operator Tree: TableScan alias: a - filterExpr: ((ds = '2008-04-08') and (key = '27')) (type: boolean) + filterExpr: (((key = '27') is true or (null and (key = '27') is not true and (key = '38') is not true)) and key is not null) (type: boolean) Statistics: Num rows: 1000 Data size: 10624 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (key = '27') (type: boolean) - Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE + predicate: (((key = '27') is true or (null and (key = '27') is not true and (key = '38') is not true)) and key is not null) (type: boolean) + Statistics: Num rows: 750 Data size: 7968 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: value (type: string), hr (type: string) - outputColumnNames: _col0, _col1 - Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE + expressions: key (type: string), value (type: string), hr (type: string) + outputColumnNames: _col0, _col1, _col2 + Statistics: Num rows: 750 Data size: 7968 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator - sort order: - Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE - value expressions: _col0 (type: string), _col1 (type: string) + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 750 Data size: 7968 Basic stats: COMPLETE Column stats: NONE + value expressions: _col1 (type: string), _col2 (type: string) TableScan alias: b - filterExpr: ((ds = '2008-04-08') and (key = '27')) (type: boolean) + filterExpr: (((key = '27') is true or (null and (key = '27') is not true and (key = '38') is not true)) and key is not null) (type: boolean) Statistics: Num rows: 1000 Data size: 10624 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (key = '27') (type: boolean) - Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE + predicate: (((key = '27') is true or (null and (key = '27') is not true and (key = '38') is not true)) and key is not null) (type: boolean) + Statistics: Num rows: 750 Data size: 7968 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: value (type: string), hr (type: string) - outputColumnNames: _col0, _col1 - Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE + expressions: key (type: string), value (type: string), hr (type: string) + outputColumnNames: _col0, _col1, _col2 + Statistics: Num rows: 750 Data size: 7968 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator - sort order: - Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE - value expressions: _col0 (type: string), _col1 (type: string) + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 750 Data size: 7968 Basic stats: COMPLETE Column stats: NONE + value expressions: _col1 (type: string), _col2 (type: string) Reduce Operator Tree: Join Operator condition map: Inner Join 0 to 1 keys: - 0 - 1 - outputColumnNames: _col0, _col1, _col2, _col3 - Statistics: Num rows: 250000 Data size: 5562000 Basic stats: COMPLETE Column stats: NONE + 0 _col0 (type: string) + 1 _col0 (type: string) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 + Statistics: Num rows: 825 Data size: 8764 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false table: @@ -248,18 +253,18 @@ STAGE PLANS: Map Operator Tree: TableScan Reduce Output Operator - key expressions: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string) - sort order: ++++ - Statistics: Num rows: 250000 Data size: 5562000 Basic stats: COMPLETE Column stats: NONE + key expressions: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string) + sort order: ++++++ + Statistics: Num rows: 825 Data size: 8764 Basic stats: COMPLETE Column stats: NONE Execution mode: vectorized Reduce Operator Tree: Select Operator - expressions: '27' (type: string), KEY.reducesinkkey0 (type: string), '2008-04-08' (type: string), KEY.reducesinkkey1 (type: string), '27' (type: string), KEY.reducesinkkey2 (type: string), '2008-04-08' (type: string), KEY.reducesinkkey3 (type: string) + expressions: KEY.reducesinkkey0 (type: string), KEY.reducesinkkey1 (type: string), '2008-04-08' (type: string), KEY.reducesinkkey2 (type: string), KEY.reducesinkkey3 (type: string), KEY.reducesinkkey4 (type: string), '2008-04-08' (type: string), KEY.reducesinkkey5 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7 - Statistics: Num rows: 250000 Data size: 5562000 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 825 Data size: 8764 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 250000 Data size: 5562000 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 825 Data size: 8764 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -271,7 +276,6 @@ STAGE PLANS: Processor Tree: ListSink -Warning: Shuffle Join JOIN[8][tables = [$hdt$_0, $hdt$_1]] in Stage 'Stage-1:MAPRED' is a cross product PREHOOK: query: SELECT * FROM srcpart a JOIN srcpart b ON a.key = b.key diff --git ql/src/test/results/clientpositive/ppr_allchildsarenull.q.out ql/src/test/results/clientpositive/ppr_allchildsarenull.q.out index 26612905f2..38d3f2ea18 100644 --- ql/src/test/results/clientpositive/ppr_allchildsarenull.q.out +++ ql/src/test/results/clientpositive/ppr_allchildsarenull.q.out @@ -26,7 +26,7 @@ POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 #### A masked pattern was here #### OPTIMIZED SQL: SELECT CAST(`key` AS INTEGER) AS `user_id`, `value` FROM `default`.`srcpart` -WHERE `ds` = '2008-04-08' AND (`value` LIKE 'aaa%' OR `value` LIKE 'vvv%') +WHERE `ds` = '2008-04-08' AND (`value` LIKE 'aaa%' OR `value` LIKE 'vvv%') IS TRUE STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -37,23 +37,23 @@ STAGE PLANS: Map Operator Tree: TableScan alias: srcpart - filterExpr: ((ds = '2008-04-08') and ((value like 'aaa%') or (value like 'vvv%'))) (type: boolean) + filterExpr: ((ds = '2008-04-08') and ((value like 'aaa%') or (value like 'vvv%')) is true) (type: boolean) Statistics: Num rows: 1000 Data size: 10624 Basic stats: COMPLETE Column stats: NONE GatherStats: false Filter Operator isSamplingPred: false - predicate: ((value like 'aaa%') or (value like 'vvv%')) (type: boolean) - Statistics: Num rows: 1000 Data size: 10624 Basic stats: COMPLETE Column stats: NONE + predicate: ((value like 'aaa%') or (value like 'vvv%')) is true (type: boolean) + Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: UDFToInteger(key) (type: int), value (type: string) outputColumnNames: _col0, _col1 - Statistics: Num rows: 1000 Data size: 10624 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false GlobalTableId: 0 #### A masked pattern was here #### NumFilesPerFileSink: 1 - Statistics: Num rows: 1000 Data size: 10624 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE #### A masked pattern was here #### table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat @@ -238,7 +238,7 @@ POSTHOOK: Input: default@srcpart@ds=2008-04-09/hr=12 #### A masked pattern was here #### OPTIMIZED SQL: SELECT CAST(`key` AS INTEGER) AS `user_id`, `value` FROM `default`.`srcpart` -WHERE `ds` = '2008-04-08' AND (`value` LIKE 'aaa%' OR `value` LIKE 'vvv%') +WHERE `ds` = '2008-04-08' AND (`value` LIKE 'aaa%' OR `value` LIKE 'vvv%') IS TRUE STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -253,18 +253,18 @@ STAGE PLANS: GatherStats: false Filter Operator isSamplingPred: false - predicate: (((value like 'aaa%') or (value like 'vvv%')) and (ds = '2008-04-08')) (type: boolean) - Statistics: Num rows: 2000 Data size: 21248 Basic stats: COMPLETE Column stats: NONE + predicate: (((value like 'aaa%') or (value like 'vvv%')) is true and (ds = '2008-04-08')) (type: boolean) + Statistics: Num rows: 1000 Data size: 10624 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: UDFToInteger(key) (type: int), value (type: string) outputColumnNames: _col0, _col1 - Statistics: Num rows: 2000 Data size: 21248 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1000 Data size: 10624 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false GlobalTableId: 0 #### A masked pattern was here #### NumFilesPerFileSink: 1 - Statistics: Num rows: 2000 Data size: 21248 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1000 Data size: 10624 Basic stats: COMPLETE Column stats: NONE #### A masked pattern was here #### table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat diff --git ql/src/test/results/clientpositive/rand_partitionpruner2.q.out ql/src/test/results/clientpositive/rand_partitionpruner2.q.out index 692d861dab..518a44fe7f 100644 --- ql/src/test/results/clientpositive/rand_partitionpruner2.q.out +++ ql/src/test/results/clientpositive/rand_partitionpruner2.q.out @@ -22,7 +22,7 @@ POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=11 POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 POSTHOOK: Output: default@tmptable_n1 -OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS STRING) AS `ds`, `hr` +OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds`, `hr` FROM `default`.`srcpart` WHERE RAND(1) < 0.1 AND `ds` = '2008-04-08' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/rand_partitionpruner3.q.out ql/src/test/results/clientpositive/rand_partitionpruner3.q.out index db7441ffc7..5b66c136d8 100644 --- ql/src/test/results/clientpositive/rand_partitionpruner3.q.out +++ ql/src/test/results/clientpositive/rand_partitionpruner3.q.out @@ -8,9 +8,9 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS STRING) AS `ds`, `hr` +OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds`, `hr` FROM `default`.`srcpart` -WHERE RAND(1) < 0.1 AND `ds` = '2008-04-08' AND `key` <= 50 AND `key` >= 10 AND `hr` LIKE '%2' +WHERE RAND(1) < 0.1 AND `ds` = '2008-04-08' AND `hr` LIKE '%2' AND `key` <= 50 AND `key` >= 10 STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -140,9 +140,9 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS STRING) AS `ds`, `hr` +OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds`, `hr` FROM `default`.`srcpart` -WHERE `ds` = '2008-04-08' AND `key` <= 50 AND `key` >= 10 AND `hr` LIKE '%2' +WHERE `ds` = '2008-04-08' AND `hr` LIKE '%2' AND `key` <= 50 AND `key` >= 10 STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 diff --git ql/src/test/results/clientpositive/spark/auto_sortmerge_join_12.q.out ql/src/test/results/clientpositive/spark/auto_sortmerge_join_12.q.out index bae6c2ab82..9d254d2808 100644 --- ql/src/test/results/clientpositive/spark/auto_sortmerge_join_12.q.out +++ ql/src/test/results/clientpositive/spark/auto_sortmerge_join_12.q.out @@ -134,7 +134,7 @@ POSTHOOK: query: load data local inpath '../../data/files/auto_sortmerge_join/sm POSTHOOK: type: LOAD #### A masked pattern was here #### POSTHOOK: Output: default@bucket_medium@ds=2008-04-08 -Warning: Shuffle Join JOIN[17][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3]] in Work 'Reducer 3' is a cross product +Warning: Shuffle Join JOIN[20][tables = [$hdt$_0, $hdt$_1]] in Work 'Reducer 2' is a cross product PREHOOK: query: explain extended select count(*) FROM bucket_small_n15 a JOIN bucket_medium b ON a.key = b.key JOIN bucket_big_n15 c ON c.key = b.key JOIN bucket_medium d ON c.key = b.key PREHOOK: type: QUERY PREHOOK: Input: default@bucket_big_n15 @@ -156,17 +156,20 @@ POSTHOOK: Input: default@bucket_small_n15 POSTHOOK: Input: default@bucket_small_n15@ds=2008-04-08 #### A masked pattern was here #### OPTIMIZED SQL: SELECT COUNT(*) AS `$f0` +FROM (SELECT 0 AS `DUMMY` +FROM `default`.`bucket_medium`) AS `t`, +(SELECT 0 AS `DUMMY` +FROM (SELECT `t5`.`key`, `t3`.`key` AS `key0`, `t1`.`key` AS `key1` FROM (SELECT `key` FROM `default`.`bucket_big_n15` -WHERE `key` IS NOT NULL) AS `t0` +WHERE `key` IS NOT NULL) AS `t1` INNER JOIN (SELECT `key` FROM `default`.`bucket_medium` -WHERE `key` IS NOT NULL) AS `t2` ON `t0`.`key` = `t2`.`key` +WHERE `key` IS NOT NULL) AS `t3` ON `t1`.`key` = `t3`.`key` INNER JOIN (SELECT `key` FROM `default`.`bucket_small_n15` -WHERE `key` IS NOT NULL) AS `t4` ON `t2`.`key` = `t4`.`key`, -(SELECT 0 AS `DUMMY` -FROM `default`.`bucket_medium`) AS `t5` +WHERE `key` IS NOT NULL) AS `t5` ON `t3`.`key` = `t5`.`key`) AS `t6` +WHERE `t6`.`key1` = `t6`.`key0`) AS `t8` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -175,14 +178,84 @@ STAGE PLANS: Stage: Stage-1 Spark Edges: - Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 2), Map 5 (PARTITION-LEVEL SORT, 2), Map 6 (PARTITION-LEVEL SORT, 2) - Reducer 3 <- Map 7 (PARTITION-LEVEL SORT, 1), Reducer 2 (PARTITION-LEVEL SORT, 1) - Reducer 4 <- Reducer 3 (GROUP, 1) + Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 1), Reducer 5 (PARTITION-LEVEL SORT, 1) + Reducer 3 <- Reducer 2 (GROUP, 1) + Reducer 5 <- Map 4 (PARTITION-LEVEL SORT, 2), Map 6 (PARTITION-LEVEL SORT, 2), Map 7 (PARTITION-LEVEL SORT, 2) #### A masked pattern was here #### Vertices: Map 1 Map Operator Tree: TableScan + alias: d + Statistics: Num rows: 3 Data size: 1700 Basic stats: PARTIAL Column stats: NONE + GatherStats: false + Select Operator + Statistics: Num rows: 3 Data size: 1700 Basic stats: PARTIAL Column stats: NONE + Reduce Output Operator + null sort order: + sort order: + Statistics: Num rows: 3 Data size: 1700 Basic stats: PARTIAL Column stats: NONE + tag: 0 + auto parallelism: false + Execution mode: vectorized + Path -> Alias: +#### A masked pattern was here #### + Path -> Partition: +#### A masked pattern was here #### + Partition + base file name: ds=2008-04-08 + input format: org.apache.hadoop.mapred.TextInputFormat + output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat + partition values: + ds 2008-04-08 + properties: + bucket_count 3 + bucket_field_name key + column.name.delimiter , + columns key,value + columns.comments + columns.types string:string +#### A masked pattern was here #### + name default.bucket_medium + numFiles 3 + numRows 0 + partition_columns ds + partition_columns.types string + rawDataSize 0 + serialization.ddl struct bucket_medium { string key, string value} + serialization.format 1 + serialization.lib org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + totalSize 170 +#### A masked pattern was here #### + serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + + input format: org.apache.hadoop.mapred.TextInputFormat + output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat + properties: + SORTBUCKETCOLSPREFIX TRUE + bucket_count 3 + bucket_field_name key + bucketing_version 2 + column.name.delimiter , + columns key,value + columns.comments + columns.types string:string +#### A masked pattern was here #### + name default.bucket_medium + partition_columns ds + partition_columns.types string + serialization.ddl struct bucket_medium { string key, string value} + serialization.format 1 + serialization.lib org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe +#### A masked pattern was here #### + serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + name: default.bucket_medium + name: default.bucket_medium + Truncated Path -> Alias: + /bucket_medium/ds=2008-04-08 [$hdt$_0:d] + Map 4 + Map Operator Tree: + TableScan alias: c filterExpr: key is not null (type: boolean) Statistics: Num rows: 240 Data size: 116240 Basic stats: PARTIAL Column stats: NONE @@ -308,9 +381,9 @@ STAGE PLANS: name: default.bucket_big_n15 name: default.bucket_big_n15 Truncated Path -> Alias: - /bucket_big_n15/ds=2008-04-08 [$hdt$_0:c] - /bucket_big_n15/ds=2008-04-09 [$hdt$_0:c] - Map 5 + /bucket_big_n15/ds=2008-04-08 [$hdt$_1:$hdt$_1:$hdt$_1:c] + /bucket_big_n15/ds=2008-04-09 [$hdt$_1:$hdt$_1:$hdt$_1:c] + Map 6 Map Operator Tree: TableScan alias: b @@ -388,8 +461,8 @@ STAGE PLANS: name: default.bucket_medium name: default.bucket_medium Truncated Path -> Alias: - /bucket_medium/ds=2008-04-08 [$hdt$_1:b] - Map 6 + /bucket_medium/ds=2008-04-08 [$hdt$_1:$hdt$_1:$hdt$_2:b] + Map 7 Map Operator Tree: TableScan alias: a @@ -467,105 +540,17 @@ STAGE PLANS: name: default.bucket_small_n15 name: default.bucket_small_n15 Truncated Path -> Alias: - /bucket_small_n15/ds=2008-04-08 [$hdt$_2:a] - Map 7 - Map Operator Tree: - TableScan - alias: d - Statistics: Num rows: 3 Data size: 1700 Basic stats: PARTIAL Column stats: NONE - GatherStats: false - Select Operator - Statistics: Num rows: 3 Data size: 1700 Basic stats: PARTIAL Column stats: NONE - Reduce Output Operator - null sort order: - sort order: - Statistics: Num rows: 3 Data size: 1700 Basic stats: PARTIAL Column stats: NONE - tag: 1 - auto parallelism: false - Execution mode: vectorized - Path -> Alias: -#### A masked pattern was here #### - Path -> Partition: -#### A masked pattern was here #### - Partition - base file name: ds=2008-04-08 - input format: org.apache.hadoop.mapred.TextInputFormat - output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat - partition values: - ds 2008-04-08 - properties: - bucket_count 3 - bucket_field_name key - column.name.delimiter , - columns key,value - columns.comments - columns.types string:string -#### A masked pattern was here #### - name default.bucket_medium - numFiles 3 - numRows 0 - partition_columns ds - partition_columns.types string - rawDataSize 0 - serialization.ddl struct bucket_medium { string key, string value} - serialization.format 1 - serialization.lib org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe - totalSize 170 -#### A masked pattern was here #### - serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe - - input format: org.apache.hadoop.mapred.TextInputFormat - output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat - properties: - SORTBUCKETCOLSPREFIX TRUE - bucket_count 3 - bucket_field_name key - bucketing_version 2 - column.name.delimiter , - columns key,value - columns.comments - columns.types string:string -#### A masked pattern was here #### - name default.bucket_medium - partition_columns ds - partition_columns.types string - serialization.ddl struct bucket_medium { string key, string value} - serialization.format 1 - serialization.lib org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe -#### A masked pattern was here #### - serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe - name: default.bucket_medium - name: default.bucket_medium - Truncated Path -> Alias: - /bucket_medium/ds=2008-04-08 [$hdt$_3:d] + /bucket_small_n15/ds=2008-04-08 [$hdt$_1:$hdt$_1:$hdt$_3:a] Reducer 2 Needs Tagging: true Reduce Operator Tree: Join Operator condition map: Inner Join 0 to 1 - Inner Join 1 to 2 - keys: - 0 _col0 (type: string) - 1 _col0 (type: string) - 2 _col0 (type: string) - Statistics: Num rows: 528 Data size: 255728 Basic stats: PARTIAL Column stats: NONE - Reduce Output Operator - null sort order: - sort order: - Statistics: Num rows: 528 Data size: 255728 Basic stats: PARTIAL Column stats: NONE - tag: 0 - auto parallelism: false - Reducer 3 - Needs Tagging: true - Reduce Operator Tree: - Join Operator - condition map: - Inner Join 0 to 1 keys: 0 1 - Statistics: Num rows: 1584 Data size: 1666368 Basic stats: PARTIAL Column stats: NONE + Statistics: Num rows: 792 Data size: 833184 Basic stats: PARTIAL Column stats: NONE Group By Operator aggregations: count() mode: hash @@ -578,7 +563,7 @@ STAGE PLANS: tag: -1 value expressions: _col0 (type: bigint) auto parallelism: false - Reducer 4 + Reducer 3 Execution mode: vectorized Needs Tagging: false Reduce Operator Tree: @@ -609,6 +594,35 @@ STAGE PLANS: TotalFiles: 1 GatherStats: false MultiFileSpray: false + Reducer 5 + Needs Tagging: true + Reduce Operator Tree: + Join Operator + condition map: + Inner Join 0 to 1 + Inner Join 1 to 2 + keys: + 0 _col0 (type: string) + 1 _col0 (type: string) + 2 _col0 (type: string) + outputColumnNames: _col0, _col1 + Statistics: Num rows: 528 Data size: 255728 Basic stats: PARTIAL Column stats: NONE + Select Operator + expressions: _col1 (type: string), _col0 (type: string) + outputColumnNames: _col1, _col2 + Statistics: Num rows: 528 Data size: 255728 Basic stats: PARTIAL Column stats: NONE + Filter Operator + isSamplingPred: false + predicate: (_col2 = _col1) (type: boolean) + Statistics: Num rows: 264 Data size: 127864 Basic stats: PARTIAL Column stats: NONE + Select Operator + Statistics: Num rows: 264 Data size: 127864 Basic stats: PARTIAL Column stats: NONE + Reduce Output Operator + null sort order: + sort order: + Statistics: Num rows: 264 Data size: 127864 Basic stats: PARTIAL Column stats: NONE + tag: 1 + auto parallelism: false Stage: Stage-0 Fetch Operator @@ -616,7 +630,7 @@ STAGE PLANS: Processor Tree: ListSink -Warning: Shuffle Join JOIN[17][tables = [$hdt$_0, $hdt$_1, $hdt$_2, $hdt$_3]] in Work 'Reducer 3' is a cross product +Warning: Shuffle Join JOIN[20][tables = [$hdt$_0, $hdt$_1]] in Work 'Reducer 2' is a cross product PREHOOK: query: select count(*) FROM bucket_small_n15 a JOIN bucket_medium b ON a.key = b.key JOIN bucket_big_n15 c ON c.key = b.key JOIN bucket_medium d ON c.key = b.key PREHOOK: type: QUERY PREHOOK: Input: default@bucket_big_n15 diff --git ql/src/test/results/clientpositive/spark/auto_sortmerge_join_16.q.out ql/src/test/results/clientpositive/spark/auto_sortmerge_join_16.q.out index 24cf07b9a3..f03929b6fd 100644 --- ql/src/test/results/clientpositive/spark/auto_sortmerge_join_16.q.out +++ ql/src/test/results/clientpositive/spark/auto_sortmerge_join_16.q.out @@ -220,7 +220,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: bucket_small_n17 - filterExpr: pri BETWEEN 1 AND 2 (type: boolean) + filterExpr: pri BETWEEN 1L AND 2L (type: boolean) Statistics: Num rows: 236 Data size: 2244 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: key (type: bigint), value (type: string) diff --git ql/src/test/results/clientpositive/spark/bucket_map_join_tez2.q.out ql/src/test/results/clientpositive/spark/bucket_map_join_tez2.q.out index aecb230178..c9c7c5bf1e 100644 --- ql/src/test/results/clientpositive/spark/bucket_map_join_tez2.q.out +++ ql/src/test/results/clientpositive/spark/bucket_map_join_tez2.q.out @@ -2371,6 +2371,13 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@my_dim POSTHOOK: Input: default@my_fact #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `t0`.`bucket_col`, `t2`.`join_col` AS `account1`, `t0`.`accounting_period` +FROM (SELECT `bucket_col`, `join_col`, `accounting_period` +FROM `default`.`my_fact` +WHERE `fiscal_year` = '2015' AND `accounting_period` = 10 AND `join_col` IS NOT NULL) AS `t0` +INNER JOIN (SELECT `join_col` +FROM `default`.`my_dim` +WHERE `filter_col` IN ('VAL1', 'VAL2') AND `join_col` IS NOT NULL) AS `t2` ON `t0`.`join_col` = `t2`.`join_col` STAGE DEPENDENCIES: Stage-2 is a root stage Stage-1 depends on stages: Stage-2 diff --git ql/src/test/results/clientpositive/spark/cbo_simple_select.q.out ql/src/test/results/clientpositive/spark/cbo_simple_select.q.out index acf91bf178..3aa929d13c 100644 --- ql/src/test/results/clientpositive/spark/cbo_simple_select.q.out +++ ql/src/test/results/clientpositive/spark/cbo_simple_select.q.out @@ -761,9 +761,9 @@ STAGE PLANS: Processor Tree: TableScan alias: cbo_t2 - filterExpr: (c_int = c_int) (type: boolean) + filterExpr: c_int is not null (type: boolean) Filter Operator - predicate: (c_int = c_int) (type: boolean) + predicate: c_int is not null (type: boolean) Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 @@ -821,9 +821,9 @@ STAGE PLANS: Processor Tree: TableScan alias: cbo_t2 - filterExpr: (c_int = c_int) (type: boolean) + filterExpr: c_int is not null (type: boolean) Filter Operator - predicate: (c_int = c_int) (type: boolean) + predicate: c_int is not null (type: boolean) Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 @@ -833,13 +833,11 @@ PREHOOK: query: -- c_int is not null EXPLAIN select * from cbo_t2 where (cbo_t2.c_int) IN (NULL) PREHOOK: type: QUERY PREHOOK: Input: default@cbo_t2 -PREHOOK: Input: default@cbo_t2@dt=2014 #### A masked pattern was here #### POSTHOOK: query: -- c_int is not null EXPLAIN select * from cbo_t2 where (cbo_t2.c_int) IN (NULL) POSTHOOK: type: QUERY POSTHOOK: Input: default@cbo_t2 -POSTHOOK: Input: default@cbo_t2@dt=2014 #### A masked pattern was here #### STAGE DEPENDENCIES: Stage-0 is a root stage @@ -851,11 +849,10 @@ STAGE PLANS: Processor Tree: TableScan alias: cbo_t2 - filterExpr: (c_int = null) (type: boolean) Filter Operator - predicate: (c_int = null) (type: boolean) + predicate: false (type: boolean) Select Operator - expressions: key (type: string), value (type: string), null (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) + expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 ListSink @@ -881,9 +878,9 @@ STAGE PLANS: Processor Tree: TableScan alias: cbo_t2 - filterExpr: ((c_int = c_int) or (c_int = (2 * c_int))) (type: boolean) + filterExpr: (c_int is not null or (c_int = (2 * c_int))) (type: boolean) Filter Operator - predicate: ((c_int = (2 * c_int)) or (c_int = c_int)) (type: boolean) + predicate: ((c_int = (2 * c_int)) or c_int is not null) (type: boolean) Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 @@ -911,9 +908,9 @@ STAGE PLANS: Processor Tree: TableScan alias: cbo_t2 - filterExpr: ((c_int = c_int) or (c_int = 0)) (type: boolean) + filterExpr: (c_int is not null or (c_int = 0)) (type: boolean) Filter Operator - predicate: ((c_int = 0) or (c_int = c_int)) (type: boolean) + predicate: ((c_int = 0) or c_int is not null) (type: boolean) Select Operator expressions: key (type: string), value (type: string), c_int (type: int), c_float (type: float), c_boolean (type: boolean), dt (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5 diff --git ql/src/test/results/clientpositive/spark/count.q.out ql/src/test/results/clientpositive/spark/count.q.out index d5a4c6146a..4c869fb2f6 100644 --- ql/src/test/results/clientpositive/spark/count.q.out +++ ql/src/test/results/clientpositive/spark/count.q.out @@ -360,7 +360,7 @@ STAGE PLANS: Statistics: Num rows: 1 Data size: 320 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: $f0 (type: bigint), $f0 (type: bigint), $f1 (type: bigint), $f2 (type: bigint), $f3 (type: bigint), $f4 (type: bigint), $f5 (type: bigint), $f6 (type: bigint), $f7 (type: bigint), $f8 (type: bigint), $f9 (type: bigint), $f10 (type: bigint), $f11 (type: bigint), $f12 (type: bigint), $f13 (type: bigint), $f14 (type: bigint), $f15 (type: bigint), $f16 (type: bigint), $f17 (type: bigint), $f18 (type: bigint), $f19 (type: bigint) - outputColumnNames: $f0, $f00, $f1, $f2, $f3, $f4, $f5, $f6, $f7, $f8, $f9, $f10, $f11, $f12, $f13, $f14, $f15, $f16, $f17, $f18, $f19 + outputColumnNames: _o__c0, _o__c1, _o__c2, _o__c3, _o__c4, _o__c5, _o__c6, _o__c7, _o__c8, _o__c9, _o__c10, _o__c11, _o__c12, _o__c13, _o__c14, _o__c15, _o__c16, _o__c17, _o__c18, _o__c19, _o__c20 Statistics: Num rows: 1 Data size: 320 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false @@ -907,7 +907,7 @@ STAGE PLANS: Statistics: Num rows: 1 Data size: 160 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: $f0 (type: bigint), $f0 (type: bigint), $f1 (type: bigint), $f2 (type: bigint), $f3 (type: bigint), $f4 (type: bigint), $f5 (type: bigint), $f6 (type: bigint), $f7 (type: bigint), $f8 (type: bigint), $f9 (type: bigint), $f10 (type: bigint), $f11 (type: bigint), $f12 (type: bigint), $f13 (type: bigint), $f14 (type: bigint), $f15 (type: bigint), $f16 (type: bigint), $f17 (type: bigint), $f18 (type: bigint), $f19 (type: bigint) - outputColumnNames: $f0, $f00, $f1, $f2, $f3, $f4, $f5, $f6, $f7, $f8, $f9, $f10, $f11, $f12, $f13, $f14, $f15, $f16, $f17, $f18, $f19 + outputColumnNames: _o__c0, _o__c1, _o__c2, _o__c3, _o__c4, _o__c5, _o__c6, _o__c7, _o__c8, _o__c9, _o__c10, _o__c11, _o__c12, _o__c13, _o__c14, _o__c15, _o__c16, _o__c17, _o__c18, _o__c19, _o__c20 Statistics: Num rows: 1 Data size: 160 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false diff --git ql/src/test/results/clientpositive/spark/groupby_sort_1_23.q.out ql/src/test/results/clientpositive/spark/groupby_sort_1_23.q.out index 0bd26cb7cb..3d8bf78538 100644 --- ql/src/test/results/clientpositive/spark/groupby_sort_1_23.q.out +++ ql/src/test/results/clientpositive/spark/groupby_sort_1_23.q.out @@ -2091,7 +2091,7 @@ OPTIMIZED SQL: SELECT `key`, COUNT(*) AS `$f1` FROM `default`.`t1_n80` GROUP BY `key` UNION ALL -SELECT CAST(CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) AS STRING) AS `key`, COUNT(*) AS `_o__c1` +SELECT CAST(CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) AS VARCHAR(65536)) AS `key`, COUNT(*) AS `_o__c1` FROM `default`.`t1_n80` GROUP BY CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/spark/groupby_sort_skew_1_23.q.out ql/src/test/results/clientpositive/spark/groupby_sort_skew_1_23.q.out index 62c8f16a12..a083ccbdd5 100644 --- ql/src/test/results/clientpositive/spark/groupby_sort_skew_1_23.q.out +++ ql/src/test/results/clientpositive/spark/groupby_sort_skew_1_23.q.out @@ -1576,7 +1576,7 @@ group by key + key POSTHOOK: type: QUERY POSTHOOK: Input: default@t1_n56 POSTHOOK: Output: default@outputtbl1_n13 -OPTIMIZED SQL: SELECT CAST(CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) AS STRING) AS `_o__c0`, SUM(COUNT(*)) AS `_o__c1` +OPTIMIZED SQL: SELECT CAST(CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) AS VARCHAR(65536)) AS `_o__c0`, SUM(COUNT(*)) AS `_o__c1` FROM `default`.`t1_n56` GROUP BY CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) STAGE DEPENDENCIES: @@ -2171,7 +2171,7 @@ OPTIMIZED SQL: SELECT `key`, COUNT(*) AS `$f1` FROM `default`.`t1_n56` GROUP BY `key` UNION ALL -SELECT CAST(CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) AS STRING) AS `key`, COUNT(*) AS `_o__c1` +SELECT CAST(CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) AS VARCHAR(65536)) AS `key`, COUNT(*) AS `_o__c1` FROM `default`.`t1_n56` GROUP BY CAST(`key` AS DOUBLE) + CAST(`key` AS DOUBLE) STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/spark/join_filters_overlap.q.out ql/src/test/results/clientpositive/spark/join_filters_overlap.q.out index 49226b2622..936cfd0143 100644 --- ql/src/test/results/clientpositive/spark/join_filters_overlap.q.out +++ ql/src/test/results/clientpositive/spark/join_filters_overlap.q.out @@ -18,6 +18,15 @@ POSTHOOK: query: explain extended select * from a_n4 left outer join a_n4 b on ( POSTHOOK: type: QUERY POSTHOOK: Input: default@a_n4 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `t`.`key`, `t`.`value`, `t1`.`key` AS `key1`, `t1`.`value` AS `value1`, `t3`.`key` AS `key2`, `t3`.`value` AS `value2` +FROM (SELECT `key`, `value`, `value` = 60 AS `=`, `value` = 50 AS `=3` +FROM `default`.`a_n4`) AS `t` +LEFT JOIN (SELECT `key`, CAST(50 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 50) AS `t1` ON `t`.`key` = `t1`.`key` AND `t`.`=3` +LEFT JOIN (SELECT `key`, CAST(60 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 60) AS `t3` ON `t`.`key` = `t3`.`key` AND `t`.`=` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -340,6 +349,15 @@ POSTHOOK: query: explain extended select * from a_n4 right outer join a_n4 b on POSTHOOK: type: QUERY POSTHOOK: Input: default@a_n4 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `t0`.`key`, `t0`.`value`, `t1`.`key` AS `key1`, `t1`.`value` AS `value1`, `t3`.`key` AS `key2`, `t3`.`value` AS `value2` +FROM (SELECT `key`, CAST(50 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 50) AS `t0` +RIGHT JOIN (SELECT `key`, `value`, `value` = 60 AS `=`, `value` = 50 AS `=3` +FROM `default`.`a_n4`) AS `t1` ON `t0`.`key` = `t1`.`key` AND `t1`.`=3` +LEFT JOIN (SELECT `key`, CAST(60 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 60) AS `t3` ON `t1`.`key` = `t3`.`key` AND `t1`.`=` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -662,6 +680,15 @@ POSTHOOK: query: explain extended select * from a_n4 right outer join a_n4 b on POSTHOOK: type: QUERY POSTHOOK: Input: default@a_n4 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `t0`.`key`, `t0`.`value`, `t1`.`key` AS `key1`, `t1`.`value` AS `value1`, `t3`.`key` AS `key2`, `t3`.`value` AS `value2` +FROM (SELECT `key`, CAST(50 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 50) AS `t0` +RIGHT JOIN (SELECT `key`, `value`, `value` = 60 AS `=`, `value` = 50 AS `=3` +FROM `default`.`a_n4`) AS `t1` ON `t0`.`key` = `t1`.`key` AND `t1`.`=3` +LEFT JOIN (SELECT `key`, CAST(60 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 60) AS `t3` ON `t1`.`key` = `t3`.`key` AND `t1`.`=` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -984,6 +1011,17 @@ POSTHOOK: query: explain extended select * from a_n4 full outer join a_n4 b on ( POSTHOOK: type: QUERY POSTHOOK: Input: default@a_n4 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `t`.`key`, `t`.`value`, `t0`.`key` AS `key1`, `t0`.`value` AS `value1`, `t2`.`key` AS `key2`, `t2`.`value` AS `value2`, `t4`.`key` AS `key3`, `t4`.`value` AS `value3` +FROM (SELECT `key`, `value`, `value` = 40 AS `=`, `value` = 50 AS `=3` +FROM `default`.`a_n4`) AS `t` +FULL JOIN (SELECT `key`, `value`, `value` = 60 AS `=`, `value` = 50 AS `=3` +FROM `default`.`a_n4`) AS `t0` ON `t`.`key` = `t0`.`key` AND `t`.`=3` AND `t0`.`=3` +LEFT JOIN (SELECT `key`, CAST(60 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 60) AS `t2` ON `t0`.`key` = `t2`.`key` AND `t0`.`=` +LEFT JOIN (SELECT `key`, CAST(40 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 40) AS `t4` ON `t`.`key` = `t4`.`key` AND `t`.`=` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1374,6 +1412,18 @@ POSTHOOK: query: explain extended select * from a_n4 left outer join a_n4 b on ( POSTHOOK: type: QUERY POSTHOOK: Input: default@a_n4 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `t`.`key`, `t`.`value`, `t1`.`key` AS `key1`, `t1`.`value` AS `value1`, `t3`.`key` AS `key2`, `t3`.`value` AS `value2`, `t5`.`key` AS `key3`, `t5`.`value` AS `value3` +FROM (SELECT `key`, `value`, `value` = 40 AS `=`, `value` = 60 AS `=3`, `value` = 50 AS `=4` +FROM `default`.`a_n4`) AS `t` +LEFT JOIN (SELECT `key`, CAST(50 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 50) AS `t1` ON `t`.`key` = `t1`.`key` AND `t`.`=4` +LEFT JOIN (SELECT `key`, CAST(60 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 60) AS `t3` ON `t`.`key` = `t3`.`key` AND `t`.`=3` +LEFT JOIN (SELECT `key`, CAST(40 AS INTEGER) AS `value` +FROM `default`.`a_n4` +WHERE `value` = 40) AS `t5` ON `t`.`key` = `t5`.`key` AND `t`.`=` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 diff --git ql/src/test/results/clientpositive/spark/list_bucket_dml_2.q.out ql/src/test/results/clientpositive/spark/list_bucket_dml_2.q.out index 212b16327a..84281098f0 100644 --- ql/src/test/results/clientpositive/spark/list_bucket_dml_2.q.out +++ ql/src/test/results/clientpositive/spark/list_bucket_dml_2.q.out @@ -321,7 +321,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@list_bucketing_static_part_n4 POSTHOOK: Input: default@list_bucketing_static_part_n4@ds=2008-04-08/hr=11 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('484' AS STRING) AS `$f0`, CAST('val_484' AS STRING) AS `$f1`, CAST('2008-04-08' AS STRING) AS `$f2`, CAST('11' AS STRING) AS `$f3` +OPTIMIZED SQL: SELECT CAST('484' AS VARCHAR(65536)) AS `$f0`, CAST('val_484' AS VARCHAR(65536)) AS `$f1`, CAST('2008-04-08' AS VARCHAR(65536)) AS `$f2`, CAST('11' AS VARCHAR(65536)) AS `$f3` FROM `default`.`list_bucketing_static_part_n4` WHERE `ds` = '2008-04-08' AND `hr` = '11' AND `key` = '484' AND `value` = 'val_484' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/spark/parquet_vectorization_0.q.out ql/src/test/results/clientpositive/spark/parquet_vectorization_0.q.out index 1232957610..c950e5b73f 100644 --- ql/src/test/results/clientpositive/spark/parquet_vectorization_0.q.out +++ ql/src/test/results/clientpositive/spark/parquet_vectorization_0.q.out @@ -30593,6 +30593,9 @@ POSTHOOK: query: explain extended select * from alltypesparquet where POSTHOOK: type: QUERY POSTHOOK: Input: default@alltypesparquet #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `ctinyint`, `csmallint`, `cint`, `cbigint`, `cfloat`, `cdouble`, `cstring1`, `cstring2`, `ctimestamp1`, `ctimestamp2`, `cboolean1`, `cboolean2` +FROM `default`.`alltypesparquet` +WHERE ROW(`cint`, `cfloat`) IN (ROW(49, 3.5), ROW(47, 2.09), ROW(45, 3.02)) STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -30835,6 +30838,11 @@ POSTHOOK: query: explain extended select count(*),cstring1 from alltypesparquet POSTHOOK: type: QUERY POSTHOOK: Input: default@alltypesparquet #### A masked pattern was here #### +OPTIMIZED SQL: SELECT COUNT(*) AS `_o__c0`, `cstring1` +FROM `default`.`alltypesparquet` +WHERE `cstring1` IN ('biology', 'history', 'topology') +GROUP BY `cstring1` +ORDER BY `cstring1` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 diff --git ql/src/test/results/clientpositive/spark/parquet_vectorization_5.q.out ql/src/test/results/clientpositive/spark/parquet_vectorization_5.q.out index d40baf56a6..1f2db4e58c 100644 --- ql/src/test/results/clientpositive/spark/parquet_vectorization_5.q.out +++ ql/src/test/results/clientpositive/spark/parquet_vectorization_5.q.out @@ -61,7 +61,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesparquet - filterExpr: ((cboolean2 is not null and (cstring1 like '%b%')) or ((UDFToDouble(ctinyint) = cdouble) and ctimestamp2 is not null and (cstring2 like 'a'))) (type: boolean) + filterExpr: (((cstring1 like '%b%') and cboolean2 is not null) or ((UDFToDouble(ctinyint) = cdouble) and (cstring2 like 'a') and ctimestamp2 is not null)) (type: boolean) Statistics: Num rows: 12288 Data size: 147456 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -69,8 +69,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: SelectColumnIsNotNull(col 11:boolean), FilterStringColLikeStringScalar(col 6:string, pattern %b%)), FilterExprAndExpr(children: FilterDoubleColEqualDoubleColumn(col 13:double, col 5:double)(children: CastLongToDouble(col 0:tinyint) -> 13:double), SelectColumnIsNotNull(col 9:timestamp), FilterStringColLikeStringScalar(col 7:string, pattern a))) - predicate: (((UDFToDouble(ctinyint) = cdouble) and ctimestamp2 is not null and (cstring2 like 'a')) or (cboolean2 is not null and (cstring1 like '%b%'))) (type: boolean) + predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: FilterStringColLikeStringScalar(col 6:string, pattern %b%), SelectColumnIsNotNull(col 11:boolean)), FilterExprAndExpr(children: FilterDoubleColEqualDoubleColumn(col 13:double, col 5:double)(children: CastLongToDouble(col 0:tinyint) -> 13:double), FilterStringColLikeStringScalar(col 7:string, pattern a), SelectColumnIsNotNull(col 9:timestamp))) + predicate: (((UDFToDouble(ctinyint) = cdouble) and (cstring2 like 'a') and ctimestamp2 is not null) or ((cstring1 like '%b%') and cboolean2 is not null)) (type: boolean) Statistics: Num rows: 9216 Data size: 110592 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: ctinyint (type: tinyint), csmallint (type: smallint), cint (type: int) diff --git ql/src/test/results/clientpositive/spark/parquet_vectorization_8.q.out ql/src/test/results/clientpositive/spark/parquet_vectorization_8.q.out index 31f1d4943e..617aeb5950 100644 --- ql/src/test/results/clientpositive/spark/parquet_vectorization_8.q.out +++ ql/src/test/results/clientpositive/spark/parquet_vectorization_8.q.out @@ -71,7 +71,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesparquet - filterExpr: ((cstring2 is not null and (UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D)) or (cfloat < -6432.0) or (cboolean1 is not null and (cdouble = 988888.0D))) (type: boolean) + filterExpr: (((UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D) and cstring2 is not null) or (cfloat < -6432.0) or ((cdouble = 988888.0D) and cboolean1 is not null)) (type: boolean) Statistics: Num rows: 12288 Data size: 147456 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -79,8 +79,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: SelectColumnIsNotNull(col 7:string), FilterDoubleColLessEqualDoubleScalar(col 13:double, val 10.0)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 16.0)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: SelectColumnIsNotNull(col 10:boolean), FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0))) - predicate: ((cboolean1 is not null and (cdouble = 988888.0D)) or (cfloat < -6432.0) or (cstring2 is not null and (UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D))) (type: boolean) + predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: FilterDoubleColLessEqualDoubleScalar(col 13:double, val 10.0)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 16.0)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double), SelectColumnIsNotNull(col 7:string)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0), SelectColumnIsNotNull(col 10:boolean))) + predicate: (((UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D) and cstring2 is not null) or ((cdouble = 988888.0D) and cboolean1 is not null) or (cfloat < -6432.0)) (type: boolean) Statistics: Num rows: 12288 Data size: 147456 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: ctimestamp1 (type: timestamp), cdouble (type: double), cboolean1 (type: boolean), cstring1 (type: string), cfloat (type: float), (- cdouble) (type: double), (-5638.15D - cdouble) (type: double), (cdouble * -257.0D) (type: double), (UDFToFloat(cint) + cfloat) (type: float), ((- cdouble) + UDFToDouble(cbigint)) (type: double), (- cdouble) (type: double), (-1.389 - cfloat) (type: float), (- cfloat) (type: float), ((-5638.15D - cdouble) + UDFToDouble((UDFToFloat(cint) + cfloat))) (type: double) @@ -295,7 +295,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesparquet - filterExpr: ((cstring2 is not null and (UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D)) or (cfloat < -6432.0) or (cboolean1 is not null and (cdouble = 988888.0D))) (type: boolean) + filterExpr: (((UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D) and cstring2 is not null) or (cfloat < -6432.0) or ((cdouble = 988888.0D) and cboolean1 is not null)) (type: boolean) Statistics: Num rows: 12288 Data size: 147456 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -303,8 +303,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: SelectColumnIsNotNull(col 7:string), FilterDoubleColLessEqualDoubleScalar(col 13:double, val 12.503)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 11.998)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: SelectColumnIsNotNull(col 10:boolean), FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0))) - predicate: ((cboolean1 is not null and (cdouble = 988888.0D)) or (cfloat < -6432.0) or (cstring2 is not null and (UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D))) (type: boolean) + predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: FilterDoubleColLessEqualDoubleScalar(col 13:double, val 12.503)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 11.998)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double), SelectColumnIsNotNull(col 7:string)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0), SelectColumnIsNotNull(col 10:boolean))) + predicate: (((UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D) and cstring2 is not null) or ((cdouble = 988888.0D) and cboolean1 is not null) or (cfloat < -6432.0)) (type: boolean) Statistics: Num rows: 12288 Data size: 147456 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: ctimestamp1 (type: timestamp), cdouble (type: double), cboolean1 (type: boolean), cstring1 (type: string), cfloat (type: float), (- cdouble) (type: double), (-5638.15D - cdouble) (type: double), (cdouble * -257.0D) (type: double), (UDFToFloat(cint) + cfloat) (type: float), ((- cdouble) + UDFToDouble(cbigint)) (type: double), (- cdouble) (type: double), (-1.389 - cfloat) (type: float), (- cfloat) (type: float), ((-5638.15D - cdouble) + UDFToDouble((UDFToFloat(cint) + cfloat))) (type: double) diff --git ql/src/test/results/clientpositive/spark/pcr.q.out ql/src/test/results/clientpositive/spark/pcr.q.out index 270f55ad9b..ddfa2cf3c9 100644 --- ql/src/test/results/clientpositive/spark/pcr.q.out +++ ql/src/test/results/clientpositive/spark/pcr.q.out @@ -1564,6 +1564,11 @@ POSTHOOK: Input: default@pcr_t1 POSTHOOK: Input: default@pcr_t1@ds=2000-04-08 POSTHOOK: Input: default@pcr_t1@ds=2000-04-09 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT CAST(14 AS INTEGER) AS `key`, `value` +FROM (SELECT `value` +FROM `default`.`pcr_t1` +WHERE `ds` IN ('2000-04-08', '2000-04-09') AND `key` = 14 +ORDER BY `value`) AS `t1` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1761,6 +1766,10 @@ POSTHOOK: Input: default@pcr_t1 POSTHOOK: Input: default@pcr_t1@ds=2000-04-08 POSTHOOK: Input: default@pcr_t1@ds=2000-04-09 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value` +FROM `default`.`pcr_t1` +WHERE `ds` IN ('2000-04-08', '2000-04-09') +ORDER BY `key`, `value` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -1998,7 +2007,7 @@ POSTHOOK: Input: default@pcr_t1@ds=2000-04-10 #### A masked pattern was here #### OPTIMIZED SQL: SELECT `key`, `value` FROM `default`.`pcr_t1` -WHERE `ds` >= '2000-04-08' OR `ds` IS NOT NULL +WHERE `ds` >= '2000-04-08' OR `ds` < '2000-04-10' ORDER BY `key`, `value` STAGE DEPENDENCIES: Stage-1 is a root stage @@ -2015,7 +2024,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: pcr_t1 - filterExpr: ((ds >= '2000-04-08') or ds is not null) (type: boolean) + filterExpr: ((ds >= '2000-04-08') or (ds < '2000-04-10')) (type: boolean) Statistics: Num rows: 60 Data size: 480 Basic stats: COMPLETE Column stats: NONE GatherStats: false Select Operator @@ -2304,6 +2313,10 @@ POSTHOOK: Input: default@pcr_t1 POSTHOOK: Input: default@pcr_t1@ds=2000-04-08 POSTHOOK: Input: default@pcr_t1@ds=2000-04-09 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, `ds` +FROM `default`.`pcr_t1` +WHERE ROW(`key`, `ds`) IN (ROW(1, '2000-04-08'), ROW(2, '2000-04-09')) +ORDER BY `key`, `value`, `ds` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -2500,7 +2513,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@pcr_t1 POSTHOOK: Input: default@pcr_t1@ds=2000-04-08 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS STRING) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-08' AS STRING) AS `ds1` +OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds1` FROM (SELECT * FROM (SELECT `key`, `value` FROM `default`.`pcr_t1` @@ -2793,7 +2806,7 @@ POSTHOOK: Input: default@pcr_t1 POSTHOOK: Input: default@pcr_t1@ds=2000-04-08 POSTHOOK: Input: default@pcr_t1@ds=2000-04-09 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS STRING) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-09' AS STRING) AS `ds1` +OPTIMIZED SQL: SELECT `t3`.`key`, `t3`.`value`, CAST('2000-04-08' AS VARCHAR(65536)) AS `ds`, `t3`.`key0` AS `key1`, `t3`.`value0` AS `value1`, CAST('2000-04-09' AS VARCHAR(65536)) AS `ds1` FROM (SELECT * FROM (SELECT `key`, `value` FROM `default`.`pcr_t1` @@ -4422,6 +4435,11 @@ POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=11 POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=12 #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `key`, `value`, CAST('2008-04-08' AS VARCHAR(65536)) AS `ds`, `hr` +FROM (SELECT `key`, `value`, `hr` +FROM `default`.`srcpart` +WHERE `hr` IN ('11', '12') AND `ds` = '2008-04-08' AND `key` = 11 +ORDER BY `key`, `hr`) AS `t1` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -4624,7 +4642,7 @@ POSTHOOK: Input: default@srcpart POSTHOOK: Input: default@srcpart@ds=2008-04-08/hr=11 POSTHOOK: Input: default@srcpart@ds=2008-04-09/hr=11 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT `key`, `value`, `ds`, CAST('11' AS STRING) AS `hr` +OPTIMIZED SQL: SELECT `key`, `value`, `ds`, CAST('11' AS VARCHAR(65536)) AS `hr` FROM (SELECT `key`, `value`, `ds` FROM `default`.`srcpart` WHERE `hr` = '11' AND `key` = 11 diff --git ql/src/test/results/clientpositive/spark/ppd_join_filter.q.out ql/src/test/results/clientpositive/spark/ppd_join_filter.q.out index c3bc6f4cb0..d5dd730e3b 100644 --- ql/src/test/results/clientpositive/spark/ppd_join_filter.q.out +++ ql/src/test/results/clientpositive/spark/ppd_join_filter.q.out @@ -36,7 +36,7 @@ INNER JOIN (SELECT `key`, CAST(MIN(`key`) AS DOUBLE) + CAST(2 AS DOUBLE) AS `k2` FROM `default`.`src` WHERE `key` IS NOT NULL GROUP BY `key` -HAVING CAST(MIN(`key`) AS DOUBLE) + 1 < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` +HAVING CAST(MIN(`key`) AS DOUBLE) + CAST(1 AS DOUBLE) < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -349,7 +349,7 @@ INNER JOIN (SELECT `key`, CAST(MIN(`key`) AS DOUBLE) + CAST(2 AS DOUBLE) AS `k2` FROM `default`.`src` WHERE `key` IS NOT NULL GROUP BY `key` -HAVING CAST(MIN(`key`) AS DOUBLE) + 1 < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` +HAVING CAST(MIN(`key`) AS DOUBLE) + CAST(1 AS DOUBLE) < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -662,7 +662,7 @@ INNER JOIN (SELECT `key`, CAST(MIN(`key`) AS DOUBLE) + CAST(2 AS DOUBLE) AS `k2` FROM `default`.`src` WHERE `key` IS NOT NULL GROUP BY `key` -HAVING CAST(MIN(`key`) AS DOUBLE) + 1 < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` +HAVING CAST(MIN(`key`) AS DOUBLE) + CAST(1 AS DOUBLE) < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -973,7 +973,7 @@ INNER JOIN (SELECT `key`, CAST(MIN(`key`) AS DOUBLE) + CAST(2 AS DOUBLE) AS `k2` FROM `default`.`src` WHERE `key` IS NOT NULL GROUP BY `key` -HAVING CAST(MIN(`key`) AS DOUBLE) + 1 < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` +HAVING CAST(MIN(`key`) AS DOUBLE) + CAST(1 AS DOUBLE) < 5.0) AS `t4` ON `t0`.`key` = `t4`.`key` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 diff --git ql/src/test/results/clientpositive/spark/spark_dynamic_partition_pruning.q.out ql/src/test/results/clientpositive/spark/spark_dynamic_partition_pruning.q.out index 5f06e4e832..3588a9a380 100644 --- ql/src/test/results/clientpositive/spark/spark_dynamic_partition_pruning.q.out +++ ql/src/test/results/clientpositive/spark/spark_dynamic_partition_pruning.q.out @@ -792,13 +792,13 @@ STAGE PLANS: Map Operator Tree: TableScan alias: srcpart_date_n4 - filterExpr: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) is not null) (type: boolean) + filterExpr: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) is not null) (type: boolean) Statistics: Num rows: 2 Data size: 42 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) is not null) (type: boolean) + predicate: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) is not null) (type: boolean) Statistics: Num rows: 1 Data size: 21 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) (type: bigint) + expressions: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) (type: bigint) outputColumnNames: _col0 Statistics: Num rows: 1 Data size: 21 Basic stats: COMPLETE Column stats: NONE Select Operator @@ -811,7 +811,7 @@ STAGE PLANS: outputColumnNames: _col0 Statistics: Num rows: 1 Data size: 21 Basic stats: COMPLETE Column stats: NONE Spark Partition Pruning Sink Operator - Target Columns: [Map 1 -> [ds:string (abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)))]] + Target Columns: [Map 1 -> [ds:string (abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)))]] Statistics: Num rows: 1 Data size: 21 Basic stats: COMPLETE Column stats: NONE Stage: Stage-1 @@ -825,13 +825,13 @@ STAGE PLANS: Map Operator Tree: TableScan alias: srcpart - filterExpr: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) is not null (type: boolean) + filterExpr: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) is not null (type: boolean) Statistics: Num rows: 2000 Data size: 21248 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) is not null (type: boolean) + predicate: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) is not null (type: boolean) Statistics: Num rows: 2000 Data size: 21248 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) (type: bigint) + expressions: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) (type: bigint) outputColumnNames: _col0 Statistics: Num rows: 2000 Data size: 21248 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator @@ -843,13 +843,13 @@ STAGE PLANS: Map Operator Tree: TableScan alias: srcpart_date_n4 - filterExpr: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) is not null) (type: boolean) + filterExpr: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) is not null) (type: boolean) Statistics: Num rows: 2 Data size: 42 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) is not null) (type: boolean) + predicate: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) is not null) (type: boolean) Statistics: Num rows: 1 Data size: 21 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) (type: bigint) + expressions: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) (type: bigint) outputColumnNames: _col0 Statistics: Num rows: 1 Data size: 21 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator diff --git ql/src/test/results/clientpositive/spark/spark_explainuser_1.q.out ql/src/test/results/clientpositive/spark/spark_explainuser_1.q.out index 0422dc21f4..70ee23744c 100644 --- ql/src/test/results/clientpositive/spark/spark_explainuser_1.q.out +++ ql/src/test/results/clientpositive/spark/spark_explainuser_1.q.out @@ -1807,7 +1807,7 @@ Stage-0 Group By Operator [GBY_3] (rows=1 width=101) Output:["_col0","_col1","_col2","_col3"],aggregations:["sum(c_int)"],keys:key, c_int, c_float Filter Operator [FIL_35] (rows=1 width=93) - predicate:((((c_int + 1) + 1) >= 0) and (((c_int + 1) > 0) or (UDFToDouble(key) >= 0.0D)) and ((UDFToFloat(c_int) + c_float) >= 0) and ((c_int + 1) >= 0) and ((c_int > 0) or c_float is not null) and ((c_int >= 1) or (c_float >= 1.0)) and (UDFToDouble(key) > 0.0D) and (c_float > 0.0)) + predicate:((((c_int + 1) + 1) >= 0) and ((UDFToFloat(c_int) + c_float) >= 0) and ((c_int + 1) >= 0) and ((c_int > 0) or c_float is not null) and ((c_int >= 1) or (c_float >= 1.0)) and (UDFToDouble(key) > 0.0D) and (c_float > 0.0)) TableScan [TS_0] (rows=20 width=88) default@cbo_t1,cbo_t1,Tbl:COMPLETE,Col:COMPLETE,Output:["key","c_int","c_float"] <-Reducer 7 [PARTITION-LEVEL SORT] @@ -2511,7 +2511,7 @@ Stage-0 Select Operator [SEL_24] (rows=631 width=178) Output:["_col0","_col1"] Filter Operator [FIL_23] (rows=631 width=194) - predicate:((_col2 = 0L) or (_col5 is null and _col0 is not null and (_col3 >= _col2))) + predicate:(((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col0 is null) and (_col0 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) Select Operator [SEL_22] (rows=631 width=194) Output:["_col0","_col1","_col2","_col3","_col5"] Join Operator [JOIN_21] (rows=631 width=194) @@ -2590,10 +2590,10 @@ Stage-0 Stage-1 Reducer 3 File Output Operator [FS_24] - Select Operator [SEL_23] (rows=20 width=223) + Select Operator [SEL_23] (rows=41 width=223) Output:["_col0","_col1","_col2"] - Filter Operator [FIL_22] (rows=20 width=230) - predicate:CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END + Filter Operator [FIL_22] (rows=41 width=229) + predicate:(((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col0 is null) and (_col0 is not null or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) Join Operator [JOIN_21] (rows=41 width=229) Output:["_col0","_col1","_col2","_col4","_col5","_col8"],condition map:[{"":"{\"type\":\"Left Outer\",\"left\":0,\"right\":1}"}],keys:{"0":"_col0, _col1","1":"_col0, _col1"} <-Reducer 2 [PARTITION-LEVEL SORT] @@ -2685,7 +2685,7 @@ Stage-0 Select Operator [SEL_29] (rows=27 width=125) Output:["_col0","_col1"] Filter Operator [FIL_28] (rows=27 width=141) - predicate:((_col2 = 0L) or (_col5 is null and _col1 is not null and (_col3 >= _col2))) + predicate:(((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col1 is null) and (_col1 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) Select Operator [SEL_27] (rows=27 width=141) Output:["_col0","_col1","_col2","_col3","_col5"] Join Operator [JOIN_26] (rows=27 width=141) @@ -2767,14 +2767,14 @@ Stage-0 Stage-1 Reducer 5 File Output Operator [FS_36] - Select Operator [SEL_35] (rows=3 width=106) + Select Operator [SEL_35] (rows=7 width=106) Output:["_col0","_col1"] <-Reducer 4 [SORT] SORT [RS_34] - Select Operator [SEL_33] (rows=3 width=106) + Select Operator [SEL_33] (rows=7 width=106) Output:["_col0","_col1"] - Filter Operator [FIL_32] (rows=3 width=118) - predicate:CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END + Filter Operator [FIL_32] (rows=7 width=114) + predicate:(((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col0 is null) and (_col0 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) Join Operator [JOIN_31] (rows=7 width=114) Output:["_col0","_col1","_col3","_col4","_col7"],condition map:[{"":"{\"type\":\"Left Outer\",\"left\":0,\"right\":1}"}],keys:{"0":"_col0, _col1","1":"_col0, _col1"} <-Reducer 10 [PARTITION-LEVEL SORT] diff --git ql/src/test/results/clientpositive/spark/spark_vectorized_dynamic_partition_pruning.q.out ql/src/test/results/clientpositive/spark/spark_vectorized_dynamic_partition_pruning.q.out index 6fbab4641d..07575be56a 100644 --- ql/src/test/results/clientpositive/spark/spark_vectorized_dynamic_partition_pruning.q.out +++ ql/src/test/results/clientpositive/spark/spark_vectorized_dynamic_partition_pruning.q.out @@ -1321,7 +1321,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: srcpart_date_n0 - filterExpr: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) is not null) (type: boolean) + filterExpr: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) is not null) (type: boolean) Statistics: Num rows: 2 Data size: 376 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -1331,10 +1331,10 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: FilterExprAndExpr(children: FilterStringGroupColEqualStringScalar(col 1:string, val 2008-04-08), SelectColumnIsNotNull(col 10:bigint)(children: FuncAbsLongToLong(col 9:bigint)(children: LongColAddLongScalar(col 8:bigint, val 10)(children: LongColUnaryMinus(col 7:bigint)(children: CastStringToLong(col 6:string)(children: StringGroupColConcatStringScalar(col 5:string, val 0)(children: CastLongToString(col 4:int)(children: VectorUDFDayOfMonthDate(col 3, field DAY_OF_MONTH)(children: CastStringToDate(col 0:string) -> 3:date) -> 4:int) -> 5:string) -> 6:string) -> 7:bigint) -> 8:bigint) -> 9:bigint) -> 10:bigint)) - predicate: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) is not null) (type: boolean) + predicate: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) is not null) (type: boolean) Statistics: Num rows: 1 Data size: 188 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) (type: bigint) + expressions: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) (type: bigint) outputColumnNames: _col0 Select Vectorization: className: VectorSelectOperator @@ -1363,7 +1363,7 @@ STAGE PLANS: outputColumnNames: _col0 Statistics: Num rows: 1 Data size: 188 Basic stats: COMPLETE Column stats: NONE Spark Partition Pruning Sink Operator - Target Columns: [Map 1 -> [ds:string (abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)))]] + Target Columns: [Map 1 -> [ds:string (abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)))]] Statistics: Num rows: 1 Data size: 188 Basic stats: COMPLETE Column stats: NONE Execution mode: vectorized Map Vectorization: @@ -1393,7 +1393,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: srcpart - filterExpr: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) is not null (type: boolean) + filterExpr: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) is not null (type: boolean) Statistics: Num rows: 2000 Data size: 21248 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -1403,10 +1403,10 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: SelectColumnIsNotNull(col 12:bigint)(children: FuncAbsLongToLong(col 11:bigint)(children: LongColAddLongScalar(col 10:bigint, val 10)(children: LongColUnaryMinus(col 9:bigint)(children: CastStringToLong(col 8:string)(children: StringGroupColConcatStringScalar(col 7:string, val 0)(children: CastLongToString(col 6:int)(children: VectorUDFDayOfMonthDate(col 5, field DAY_OF_MONTH)(children: CastStringToDate(col 2:string) -> 5:date) -> 6:int) -> 7:string) -> 8:string) -> 9:bigint) -> 10:bigint) -> 11:bigint) -> 12:bigint) - predicate: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) is not null (type: boolean) + predicate: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) is not null (type: boolean) Statistics: Num rows: 2000 Data size: 21248 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) (type: bigint) + expressions: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) (type: bigint) outputColumnNames: _col0 Select Vectorization: className: VectorSelectOperator @@ -1445,7 +1445,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: srcpart_date_n0 - filterExpr: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) is not null) (type: boolean) + filterExpr: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) is not null) (type: boolean) Statistics: Num rows: 2 Data size: 376 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -1455,10 +1455,10 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: FilterExprAndExpr(children: FilterStringGroupColEqualStringScalar(col 1:string, val 2008-04-08), SelectColumnIsNotNull(col 10:bigint)(children: FuncAbsLongToLong(col 9:bigint)(children: LongColAddLongScalar(col 8:bigint, val 10)(children: LongColUnaryMinus(col 7:bigint)(children: CastStringToLong(col 6:string)(children: StringGroupColConcatStringScalar(col 5:string, val 0)(children: CastLongToString(col 4:int)(children: VectorUDFDayOfMonthDate(col 3, field DAY_OF_MONTH)(children: CastStringToDate(col 0:string) -> 3:date) -> 4:int) -> 5:string) -> 6:string) -> 7:bigint) -> 8:bigint) -> 9:bigint) -> 10:bigint)) - predicate: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) is not null) (type: boolean) + predicate: ((date = '2008-04-08') and abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) is not null) (type: boolean) Statistics: Num rows: 1 Data size: 188 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10)) (type: bigint) + expressions: abs(((- UDFToLong(concat(CAST( day(CAST( ds AS DATE)) AS STRING), '0'))) + 10L)) (type: bigint) outputColumnNames: _col0 Select Vectorization: className: VectorSelectOperator diff --git ql/src/test/results/clientpositive/spark/subquery_in.q.out ql/src/test/results/clientpositive/spark/subquery_in.q.out index 09cd9d8550..3d0da817bf 100644 --- ql/src/test/results/clientpositive/spark/subquery_in.q.out +++ ql/src/test/results/clientpositive/spark/subquery_in.q.out @@ -2075,9 +2075,7 @@ STAGE PLANS: Stage: Stage-1 Spark Edges: - Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 2), Reducer 4 (PARTITION-LEVEL SORT, 2) - Reducer 4 <- Map 3 (PARTITION-LEVEL SORT, 2), Reducer 6 (PARTITION-LEVEL SORT, 2) - Reducer 6 <- Map 5 (GROUP, 2) + Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 2), Map 3 (PARTITION-LEVEL SORT, 2) #### A masked pattern was here #### Vertices: Map 1 @@ -2104,41 +2102,25 @@ STAGE PLANS: Map Operator Tree: TableScan alias: p - filterExpr: (p_size is not null and p_partkey is not null and p_name is not null) (type: boolean) + filterExpr: (((p_size + 121150) = p_partkey) and p_size is not null and p_name is not null) (type: boolean) Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (p_name is not null and p_partkey is not null and p_size is not null) (type: boolean) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + predicate: (((p_size + 121150) = p_partkey) and p_name is not null and p_size is not null) (type: boolean) + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: p_partkey (type: int), p_name (type: string), p_size (type: int) - outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col2 (type: int), _col0 (type: int) - sort order: ++ - Map-reduce partition columns: _col2 (type: int), _col0 (type: int) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - value expressions: _col1 (type: string) - Execution mode: vectorized - Map 5 - Map Operator Tree: - TableScan - alias: part - filterExpr: p_size is not null (type: boolean) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Filter Operator - predicate: p_size is not null (type: boolean) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Group By Operator - keys: p_size (type: int) - mode: hash - outputColumnNames: _col0 - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: int) - sort order: + - Map-reduce partition columns: _col0 (type: int) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + expressions: p_name (type: string), p_size (type: int) + outputColumnNames: _col0, _col1 + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + Group By Operator + keys: _col0 (type: string), _col1 (type: int) + mode: hash + outputColumnNames: _col0, _col1 + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: int) + sort order: ++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: int) + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE Execution mode: vectorized Reducer 2 Reduce Operator Tree: @@ -2149,55 +2131,14 @@ STAGE PLANS: 0 _col1 (type: string), _col5 (type: int) 1 _col0 (type: string), _col1 (type: int) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe - Reducer 4 - Reduce Operator Tree: - Join Operator - condition map: - Inner Join 0 to 1 - keys: - 0 _col2 (type: int), _col0 (type: int) - 1 _col0 (type: int), _col1 (type: int) - outputColumnNames: _col1, _col3 - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE - Select Operator - expressions: _col1 (type: string), _col3 (type: int) - outputColumnNames: _col0, _col1 - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE - Group By Operator - keys: _col0 (type: string), _col1 (type: int) - mode: hash - outputColumnNames: _col0, _col1 - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: string), _col1 (type: int) - sort order: ++ - Map-reduce partition columns: _col0 (type: string), _col1 (type: int) - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE - Reducer 6 - Execution mode: vectorized - Reduce Operator Tree: - Group By Operator - keys: KEY._col0 (type: int) - mode: mergepartial - outputColumnNames: _col0 - Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE - Select Operator - expressions: _col0 (type: int), (_col0 + 121150) (type: int) - outputColumnNames: _col0, _col1 - Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: int), _col1 (type: int) - sort order: ++ - Map-reduce partition columns: _col0 (type: int), _col1 (type: int) - Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE Stage: Stage-0 Fetch Operator @@ -4905,15 +4846,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col14 Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col10 = 0L)) THEN (true) WHEN (_col10 is null) THEN (true) WHEN (_col14 is not null) THEN (false) WHEN (_col5 is null) THEN (null) WHEN ((_col11 < _col10)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 7 Data size: 865 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col11 < _col10) is not true or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null or _col5 is null) and (_col14 is null or ((_col10 = 0L) or _col10 is null) is true) and (_col5 is not null or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null)) (type: boolean) + Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 7 Data size: 865 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 7 Data size: 865 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -5151,15 +5092,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col14 Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col10 = 0L)) THEN (true) WHEN (_col10 is null) THEN (true) WHEN (_col14 is not null) THEN (false) WHEN (_col5 is null) THEN (null) WHEN ((_col11 < _col10)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 7 Data size: 865 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col11 < _col10) is not true or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null or _col5 is null) and (_col14 is null or ((_col10 = 0L) or _col10 is null) is true) and (_col5 is not null or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null)) (type: boolean) + Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 7 Data size: 865 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 7 Data size: 865 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat diff --git ql/src/test/results/clientpositive/spark/subquery_multi.q.out ql/src/test/results/clientpositive/spark/subquery_multi.q.out index 5bf5459b56..4854e520c7 100644 --- ql/src/test/results/clientpositive/spark/subquery_multi.q.out +++ ql/src/test/results/clientpositive/spark/subquery_multi.q.out @@ -399,7 +399,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col13 Statistics: Num rows: 1 Data size: 39397 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col10 = 0L) or (_col13 is null and _col3 is not null and (_col11 >= _col10))) (type: boolean) + predicate: (((_col11 >= _col10) or (_col10 = 0L) or _col13 is not null or _col3 is null) and (_col13 is null or (_col10 = 0L)) and (_col3 is not null or (_col10 = 0L) or _col13 is not null)) (type: boolean) Statistics: Num rows: 1 Data size: 39397 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) @@ -621,7 +621,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col13 Statistics: Num rows: 1 Data size: 39397 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col10 = 0L) or (_col13 is null and _col3 is not null and (_col11 >= _col10))) (type: boolean) + predicate: (((_col11 >= _col10) or (_col10 = 0L) or _col13 is not null or _col3 is null) and (_col13 is null or (_col10 = 0L)) and (_col3 is not null or (_col10 = 0L) or _col13 is not null)) (type: boolean) Statistics: Num rows: 1 Data size: 39397 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) @@ -722,7 +722,7 @@ POSTHOOK: Input: default@part_null 85768 almond antique chartreuse lavender yellow Manufacturer#1 Brand#12 LARGE BRUSHED STEEL 34 SM BAG 1753.76 refull 86428 almond aquamarine burnished black steel Manufacturer#1 Brand#12 STANDARD ANODIZED STEEL 28 WRAP BAG 1414.42 arefully 90681 almond antique chartreuse khaki white Manufacturer#3 Brand#31 MEDIUM BURNISHED TIN 17 SM CASE 1671.68 are slyly after the sl -Warning: Shuffle Join JOIN[25][tables = [$hdt$_2, $hdt$_3]] in Work 'Reducer 7' is a cross product +Warning: Shuffle Join JOIN[26][tables = [$hdt$_2, $hdt$_3]] in Work 'Reducer 7' is a cross product PREHOOK: query: explain select * from part_null where p_brand IN (select p_brand from part_null) AND p_brand NOT IN (select p_name from part_null) PREHOOK: type: QUERY PREHOOK: Input: default@part_null @@ -770,21 +770,24 @@ STAGE PLANS: Map Operator Tree: TableScan alias: part_null - filterExpr: p_name is not null (type: boolean) Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: NONE - Filter Operator - predicate: p_name is not null (type: boolean) + Select Operator + expressions: p_name (type: string) + outputColumnNames: _col0 Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: NONE - Group By Operator - keys: p_name (type: string) - mode: hash - outputColumnNames: _col0 + Filter Operator + predicate: _col0 is not null (type: boolean) Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: string) - sort order: + - Map-reduce partition columns: _col0 (type: string) + Group By Operator + keys: _col0 (type: string) + mode: hash + outputColumnNames: _col0 Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: NONE Execution mode: vectorized Map 5 Map Operator Tree: @@ -842,15 +845,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col13 Statistics: Num rows: 2 Data size: 71632 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col10 = 0L) or (_col13 is null and (_col11 >= _col10))) (type: boolean) - Statistics: Num rows: 1 Data size: 35816 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col11 >= _col10) or (_col10 = 0L) or _col13 is not null or _col3 is null) and (_col13 is null or (_col10 = 0L))) (type: boolean) + Statistics: Num rows: 2 Data size: 71632 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 1 Data size: 35816 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 71632 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 35816 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 71632 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -920,7 +923,7 @@ STAGE PLANS: Processor Tree: ListSink -Warning: Shuffle Join JOIN[25][tables = [$hdt$_2, $hdt$_3]] in Work 'Reducer 7' is a cross product +Warning: Shuffle Join JOIN[26][tables = [$hdt$_2, $hdt$_3]] in Work 'Reducer 7' is a cross product PREHOOK: query: select * from part_null where p_brand IN (select p_brand from part_null) AND p_brand NOT IN (select p_name from part_null) PREHOOK: type: QUERY PREHOOK: Input: default@part_null @@ -1067,7 +1070,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 1 Data size: 35833 Basic stats: PARTIAL Column stats: NONE Filter Operator - predicate: ((_col12 is null and _col1 is not null and (_col10 >= _col9)) or (_col9 = 0L)) (type: boolean) + predicate: (((_col10 >= _col9) or (_col9 = 0L) or _col12 is not null or _col1 is null) and (_col1 is not null or (_col9 = 0L) or _col12 is not null) and (_col12 is null or (_col9 = 0L))) (type: boolean) Statistics: Num rows: 1 Data size: 35833 Basic stats: PARTIAL Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) @@ -1725,12 +1728,16 @@ STAGE PLANS: Stage: Stage-1 Spark Edges: - Reducer 11 <- Map 10 (PARTITION-LEVEL SORT, 2), Map 13 (PARTITION-LEVEL SORT, 2) - Reducer 12 <- Reducer 11 (GROUP, 2) + Reducer 10 <- Map 9 (PARTITION-LEVEL SORT, 2), Reducer 12 (PARTITION-LEVEL SORT, 2) + Reducer 12 <- Map 11 (GROUP, 2) + Reducer 14 <- Map 13 (PARTITION-LEVEL SORT, 2), Reducer 17 (PARTITION-LEVEL SORT, 2) + Reducer 15 <- Reducer 14 (GROUP, 2) + Reducer 17 <- Map 16 (PARTITION-LEVEL SORT, 2), Reducer 19 (PARTITION-LEVEL SORT, 2) + Reducer 19 <- Map 11 (GROUP, 2) Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 2), Map 5 (PARTITION-LEVEL SORT, 2) Reducer 3 <- Reducer 2 (PARTITION-LEVEL SORT, 2), Reducer 8 (PARTITION-LEVEL SORT, 2) - Reducer 4 <- Reducer 12 (PARTITION-LEVEL SORT, 2), Reducer 3 (PARTITION-LEVEL SORT, 2) - Reducer 7 <- Map 6 (PARTITION-LEVEL SORT, 2), Map 9 (PARTITION-LEVEL SORT, 2) + Reducer 4 <- Reducer 15 (PARTITION-LEVEL SORT, 2), Reducer 3 (PARTITION-LEVEL SORT, 2) + Reducer 7 <- Map 6 (PARTITION-LEVEL SORT, 2), Reducer 10 (PARTITION-LEVEL SORT, 2) Reducer 8 <- Reducer 7 (GROUP, 2) #### A masked pattern was here #### Vertices: @@ -1754,7 +1761,27 @@ STAGE PLANS: Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: NONE value expressions: _col0 (type: int), _col2 (type: string), _col3 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) Execution mode: vectorized - Map 10 + Map 11 + Map Operator Tree: + TableScan + alias: part + filterExpr: p_type is not null (type: boolean) + Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + Filter Operator + predicate: p_type is not null (type: boolean) + Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + Group By Operator + keys: p_type (type: string) + mode: hash + outputColumnNames: _col0 + Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + Execution mode: vectorized + Map 13 Map Operator Tree: TableScan alias: part @@ -1774,7 +1801,7 @@ STAGE PLANS: Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE value expressions: _col2 (type: string) Execution mode: vectorized - Map 13 + Map 16 Map Operator Tree: TableScan alias: pp @@ -1784,19 +1811,15 @@ STAGE PLANS: predicate: (p_brand is not null and p_type is not null) (type: boolean) Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: p_type (type: string), p_brand (type: string) + expressions: p_brand (type: string), p_type (type: string) outputColumnNames: _col0, _col1 Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Group By Operator - keys: _col0 (type: string), _col1 (type: string) - mode: hash - outputColumnNames: _col0, _col1 + Reduce Output Operator + key expressions: _col1 (type: string) + sort order: + + Map-reduce partition columns: _col1 (type: string) Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: string), _col1 (type: string) - sort order: ++ - Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + value expressions: _col0 (type: string) Execution mode: vectorized Map 5 Map Operator Tree: @@ -1852,21 +1875,54 @@ STAGE PLANS: predicate: (p_brand is not null and p_type is not null) (type: boolean) Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: p_type (type: string), p_brand (type: string) + expressions: p_brand (type: string), p_type (type: string) outputColumnNames: _col0, _col1 Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Group By Operator - keys: _col0 (type: string), _col1 (type: string) - mode: hash - outputColumnNames: _col0, _col1 + Reduce Output Operator + key expressions: _col1 (type: string) + sort order: + + Map-reduce partition columns: _col1 (type: string) Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: string), _col1 (type: string) - sort order: ++ - Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + value expressions: _col0 (type: string) Execution mode: vectorized - Reducer 11 + Reducer 10 + Reduce Operator Tree: + Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col1 (type: string) + 1 _col0 (type: string) + outputColumnNames: _col0, _col2 + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: _col2 (type: string), _col0 (type: string) + outputColumnNames: _col0, _col1 + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Group By Operator + keys: _col0 (type: string), _col1 (type: string) + mode: hash + outputColumnNames: _col0, _col1 + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: string) + sort order: ++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: string) + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Reducer 12 + Execution mode: vectorized + Reduce Operator Tree: + Group By Operator + keys: KEY._col0 (type: string) + mode: mergepartial + outputColumnNames: _col0 + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + Reducer 14 Reduce Operator Tree: Join Operator condition map: @@ -1875,35 +1931,72 @@ STAGE PLANS: 0 _col1 (type: string), _col0 (type: string) 1 _col0 (type: string), _col1 (type: string) outputColumnNames: _col1, _col2 - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Group By Operator keys: _col2 (type: string), _col1 (type: string) mode: hash outputColumnNames: _col0, _col1 - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string), _col1 (type: string) sort order: ++ Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE - Reducer 12 + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE + Reducer 15 Execution mode: vectorized Reduce Operator Tree: Group By Operator keys: KEY._col0 (type: string), KEY._col1 (type: string) mode: mergepartial outputColumnNames: _col0, _col1 - Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: string), true (type: boolean) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string), _col1 (type: string) sort order: ++ Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE value expressions: _col2 (type: boolean) + Reducer 17 + Reduce Operator Tree: + Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col1 (type: string) + 1 _col0 (type: string) + outputColumnNames: _col0, _col2 + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: _col2 (type: string), _col0 (type: string) + outputColumnNames: _col0, _col1 + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Group By Operator + keys: _col0 (type: string), _col1 (type: string) + mode: hash + outputColumnNames: _col0, _col1 + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: string) + sort order: ++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: string) + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Reducer 19 + Execution mode: vectorized + Reduce Operator Tree: + Group By Operator + keys: KEY._col0 (type: string) + mode: mergepartial + outputColumnNames: _col0 + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE Reducer 2 Reduce Operator Tree: Join Operator @@ -1947,15 +2040,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col14 Statistics: Num rows: 33 Data size: 4187 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col10 = 0L)) THEN (true) WHEN (_col10 is null) THEN (true) WHEN (_col14 is not null) THEN (false) WHEN (_col3 is null) THEN (null) WHEN ((_col11 < _col10)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 16 Data size: 2030 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col11 < _col10) is not true or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null or _col3 is null) and (_col14 is null or ((_col10 = 0L) or _col10 is null) is true) and (_col3 is not null or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null)) (type: boolean) + Statistics: Num rows: 32 Data size: 4060 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 16 Data size: 2030 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 32 Data size: 4060 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 16 Data size: 2030 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 32 Data size: 4060 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -1969,18 +2062,18 @@ STAGE PLANS: 0 _col1 (type: string), _col0 (type: string) 1 _col0 (type: string), _col1 (type: string) outputColumnNames: _col1, _col2 - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Group By Operator aggregations: count(), count(_col2) keys: _col1 (type: string) mode: hash outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE value expressions: _col1 (type: bigint), _col2 (type: bigint) Reducer 8 Execution mode: vectorized @@ -1990,12 +2083,12 @@ STAGE PLANS: keys: KEY._col0 (type: string) mode: mergepartial outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE value expressions: _col1 (type: bigint), _col2 (type: bigint) Stage: Stage-0 @@ -2238,12 +2331,16 @@ STAGE PLANS: Stage: Stage-1 Spark Edges: - Reducer 11 <- Map 10 (PARTITION-LEVEL SORT, 2), Map 13 (PARTITION-LEVEL SORT, 2) - Reducer 12 <- Reducer 11 (GROUP, 2) + Reducer 10 <- Map 9 (PARTITION-LEVEL SORT, 2), Reducer 12 (PARTITION-LEVEL SORT, 2) + Reducer 12 <- Map 11 (GROUP, 2) + Reducer 14 <- Map 13 (PARTITION-LEVEL SORT, 2), Reducer 17 (PARTITION-LEVEL SORT, 2) + Reducer 15 <- Reducer 14 (GROUP, 2) + Reducer 17 <- Map 16 (PARTITION-LEVEL SORT, 2), Reducer 19 (PARTITION-LEVEL SORT, 2) + Reducer 19 <- Map 11 (GROUP, 2) Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 2), Map 5 (PARTITION-LEVEL SORT, 2) Reducer 3 <- Reducer 2 (PARTITION-LEVEL SORT, 2), Reducer 8 (PARTITION-LEVEL SORT, 2) - Reducer 4 <- Reducer 12 (PARTITION-LEVEL SORT, 2), Reducer 3 (PARTITION-LEVEL SORT, 2) - Reducer 7 <- Map 6 (PARTITION-LEVEL SORT, 2), Map 9 (PARTITION-LEVEL SORT, 2) + Reducer 4 <- Reducer 15 (PARTITION-LEVEL SORT, 2), Reducer 3 (PARTITION-LEVEL SORT, 2) + Reducer 7 <- Map 6 (PARTITION-LEVEL SORT, 2), Reducer 10 (PARTITION-LEVEL SORT, 2) Reducer 8 <- Reducer 7 (GROUP, 2) #### A masked pattern was here #### Vertices: @@ -2267,7 +2364,27 @@ STAGE PLANS: Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: NONE value expressions: _col0 (type: int), _col2 (type: string), _col3 (type: string), _col5 (type: int), _col7 (type: double), _col8 (type: string) Execution mode: vectorized - Map 10 + Map 11 + Map Operator Tree: + TableScan + alias: part + filterExpr: p_type is not null (type: boolean) + Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + Filter Operator + predicate: p_type is not null (type: boolean) + Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + Group By Operator + keys: p_type (type: string) + mode: hash + outputColumnNames: _col0 + Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + Execution mode: vectorized + Map 13 Map Operator Tree: TableScan alias: part @@ -2287,7 +2404,7 @@ STAGE PLANS: Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE value expressions: _col2 (type: string) Execution mode: vectorized - Map 13 + Map 16 Map Operator Tree: TableScan alias: pp @@ -2297,19 +2414,15 @@ STAGE PLANS: predicate: (p_brand is not null and p_type is not null) (type: boolean) Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: p_type (type: string), p_brand (type: string) + expressions: p_brand (type: string), p_type (type: string) outputColumnNames: _col0, _col1 Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Group By Operator - keys: _col0 (type: string), _col1 (type: string) - mode: hash - outputColumnNames: _col0, _col1 + Reduce Output Operator + key expressions: _col1 (type: string) + sort order: + + Map-reduce partition columns: _col1 (type: string) Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: string), _col1 (type: string) - sort order: ++ - Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + value expressions: _col0 (type: string) Execution mode: vectorized Map 5 Map Operator Tree: @@ -2365,21 +2478,54 @@ STAGE PLANS: predicate: (p_brand is not null and p_type is not null) (type: boolean) Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: p_type (type: string), p_brand (type: string) + expressions: p_brand (type: string), p_type (type: string) outputColumnNames: _col0, _col1 Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Group By Operator - keys: _col0 (type: string), _col1 (type: string) - mode: hash - outputColumnNames: _col0, _col1 + Reduce Output Operator + key expressions: _col1 (type: string) + sort order: + + Map-reduce partition columns: _col1 (type: string) Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: string), _col1 (type: string) - sort order: ++ - Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + value expressions: _col0 (type: string) Execution mode: vectorized - Reducer 11 + Reducer 10 + Reduce Operator Tree: + Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col1 (type: string) + 1 _col0 (type: string) + outputColumnNames: _col0, _col2 + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: _col2 (type: string), _col0 (type: string) + outputColumnNames: _col0, _col1 + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Group By Operator + keys: _col0 (type: string), _col1 (type: string) + mode: hash + outputColumnNames: _col0, _col1 + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: string) + sort order: ++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: string) + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Reducer 12 + Execution mode: vectorized + Reduce Operator Tree: + Group By Operator + keys: KEY._col0 (type: string) + mode: mergepartial + outputColumnNames: _col0 + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + Reducer 14 Reduce Operator Tree: Join Operator condition map: @@ -2388,35 +2534,72 @@ STAGE PLANS: 0 _col1 (type: string), _col0 (type: string) 1 _col0 (type: string), _col1 (type: string) outputColumnNames: _col1, _col2 - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Group By Operator keys: _col2 (type: string), _col1 (type: string) mode: hash outputColumnNames: _col0, _col1 - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string), _col1 (type: string) sort order: ++ Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE - Reducer 12 + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE + Reducer 15 Execution mode: vectorized Reduce Operator Tree: Group By Operator keys: KEY._col0 (type: string), KEY._col1 (type: string) mode: mergepartial outputColumnNames: _col0, _col1 - Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: string), true (type: boolean) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string), _col1 (type: string) sort order: ++ Map-reduce partition columns: _col0 (type: string), _col1 (type: string) - Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE value expressions: _col2 (type: boolean) + Reducer 17 + Reduce Operator Tree: + Join Operator + condition map: + Inner Join 0 to 1 + keys: + 0 _col1 (type: string) + 1 _col0 (type: string) + outputColumnNames: _col0, _col2 + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Select Operator + expressions: _col2 (type: string), _col0 (type: string) + outputColumnNames: _col0, _col1 + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Group By Operator + keys: _col0 (type: string), _col1 (type: string) + mode: hash + outputColumnNames: _col0, _col1 + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: string) + sort order: ++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: string) + Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Reducer 19 + Execution mode: vectorized + Reduce Operator Tree: + Group By Operator + keys: KEY._col0 (type: string) + mode: mergepartial + outputColumnNames: _col0 + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string) + sort order: + + Map-reduce partition columns: _col0 (type: string) + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE Reducer 2 Reduce Operator Tree: Join Operator @@ -2460,15 +2643,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col14 Statistics: Num rows: 33 Data size: 4187 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col10 = 0L)) THEN (true) WHEN (_col10 is null) THEN (true) WHEN (_col14 is not null) THEN (false) WHEN (_col3 is null) THEN (null) WHEN ((_col11 < _col10)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 16 Data size: 2030 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col11 < _col10) is not true or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null or _col3 is null) and (_col14 is null or ((_col10 = 0L) or _col10 is null) is true) and (_col3 is not null or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null)) (type: boolean) + Statistics: Num rows: 32 Data size: 4060 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 16 Data size: 2030 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 32 Data size: 4060 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 16 Data size: 2030 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 32 Data size: 4060 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -2482,18 +2665,18 @@ STAGE PLANS: 0 _col1 (type: string), _col0 (type: string) 1 _col0 (type: string), _col1 (type: string) outputColumnNames: _col1, _col2 - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Group By Operator aggregations: count(), count(_col2) keys: _col1 (type: string) mode: hash outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE value expressions: _col1 (type: bigint), _col2 (type: bigint) Reducer 8 Execution mode: vectorized @@ -2503,12 +2686,12 @@ STAGE PLANS: keys: KEY._col0 (type: string) mode: mergepartial outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE value expressions: _col1 (type: bigint), _col2 (type: bigint) Stage: Stage-0 @@ -2707,15 +2890,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col14 Statistics: Num rows: 33 Data size: 4187 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col10 = 0L)) THEN (true) WHEN (_col10 is null) THEN (true) WHEN (_col14 is not null) THEN (false) WHEN (_col3 is null) THEN (null) WHEN ((_col11 < _col10)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 16 Data size: 2030 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col11 < _col10) is not true or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null or _col3 is null) and (_col14 is null or ((_col10 = 0L) or _col10 is null) is true) and (_col3 is not null or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null)) (type: boolean) + Statistics: Num rows: 32 Data size: 4060 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 16 Data size: 2030 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 32 Data size: 4060 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 16 Data size: 2030 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 32 Data size: 4060 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -3171,22 +3354,22 @@ STAGE PLANS: outputColumnNames: _col0, _col2, _col4, _col5, _col7 Statistics: Num rows: 27 Data size: 3757 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col4 = 0L) or (_col7 is null and _col2 is not null and (_col5 >= _col4))) (type: boolean) - Statistics: Num rows: 17 Data size: 2365 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col5 >= _col4) or (_col4 = 0L) or _col7 is not null or _col2 is null) and (_col2 is not null or (_col4 = 0L) or _col7 is not null) and (_col7 is null or (_col4 = 0L))) (type: boolean) + Statistics: Num rows: 26 Data size: 3617 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), 1 (type: int) outputColumnNames: _col0, _col1 - Statistics: Num rows: 17 Data size: 2365 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 26 Data size: 3617 Basic stats: COMPLETE Column stats: NONE Group By Operator keys: _col0 (type: int), _col1 (type: int) mode: hash outputColumnNames: _col0, _col1 - Statistics: Num rows: 17 Data size: 2365 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 26 Data size: 3617 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: int), _col1 (type: int) sort order: ++ Map-reduce partition columns: _col0 (type: int), _col1 (type: int) - Statistics: Num rows: 17 Data size: 2365 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 26 Data size: 3617 Basic stats: COMPLETE Column stats: NONE Reducer 9 Execution mode: vectorized Reduce Operator Tree: @@ -4070,7 +4253,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col0 = 3) or CASE WHEN ((_col9 = 0L)) THEN (true) WHEN (_col12 is not null) THEN (false) WHEN (_col5 is null) THEN (null) WHEN ((_col10 < _col9)) THEN (null) ELSE (true) END) (type: boolean) + predicate: (((_col9 <> 0L) and _col12 is null and (_col10 >= _col9) and _col5 is not null) or (_col0 = 3) or (_col9 = 0L)) (type: boolean) Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) @@ -4290,7 +4473,7 @@ STAGE PLANS: outputColumnNames: _col1, _col2, _col4, _col5 Statistics: Num rows: 550 Data size: 13543 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col4 is not null and (_col2 <> 0L)) or _col1 is not null or _col5 is not null) (type: boolean) + predicate: (((_col2 <> 0L) and _col4 is not null) or _col1 is not null or _col5 is not null) (type: boolean) Statistics: Num rows: 550 Data size: 13543 Basic stats: COMPLETE Column stats: NONE Select Operator Statistics: Num rows: 550 Data size: 13543 Basic stats: COMPLETE Column stats: NONE diff --git ql/src/test/results/clientpositive/spark/subquery_notin.q.out ql/src/test/results/clientpositive/spark/subquery_notin.q.out index 89d032f8c3..150e34b116 100644 --- ql/src/test/results/clientpositive/spark/subquery_notin.q.out +++ ql/src/test/results/clientpositive/spark/subquery_notin.q.out @@ -117,15 +117,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col5 Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col2 = 0L) or (_col5 is null and _col0 is not null and (_col3 >= _col2))) (type: boolean) - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col0 is null) and (_col0 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: string) outputColumnNames: _col0, _col1 - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -399,15 +399,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col4, _col5, _col8 Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col0 is null) and (_col0 is not null or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) (type: boolean) + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col1 (type: string), _col0 (type: string), _col2 (type: int) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -678,15 +678,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col5 Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col2 = 0L) or (_col5 is null and _col1 is not null and (_col3 >= _col2))) (type: boolean) - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col1 is null) and (_col1 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: int) outputColumnNames: _col0, _col1 - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -1083,15 +1083,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col4, _col5, _col8 Statistics: Num rows: 9 Data size: 1345 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN (_col2 is null) THEN (null) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 4 Data size: 597 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col2 is null) and (_col2 is not null or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) (type: boolean) + Statistics: Num rows: 8 Data size: 1195 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col1 (type: string), _col0 (type: string), _col2 (type: int) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 4 Data size: 597 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 8 Data size: 1195 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 4 Data size: 597 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 8 Data size: 1195 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -1504,27 +1504,27 @@ STAGE PLANS: Map Operator Tree: TableScan alias: src - filterExpr: ((key < '11') and CASE WHEN ((key > '104')) THEN (null) ELSE ((key < '11')) END) (type: boolean) + filterExpr: ((key < '11') and (((key > '104') is true and null) or (key is not null and (key > '104') is not true))) (type: boolean) properties: insideView TRUE Statistics: Num rows: 500 Data size: 5312 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((key < '11') and CASE WHEN ((key > '104')) THEN (null) ELSE ((key < '11')) END) (type: boolean) - Statistics: Num rows: 83 Data size: 881 Basic stats: COMPLETE Column stats: NONE + predicate: ((((key > '104') is true and null) or (key is not null and (key > '104') is not true)) and (key < '11')) (type: boolean) + Statistics: Num rows: 166 Data size: 1763 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: CASE WHEN ((key > '104')) THEN (null) ELSE (key) END (type: string) outputColumnNames: _col0 - Statistics: Num rows: 83 Data size: 881 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 166 Data size: 1763 Basic stats: COMPLETE Column stats: NONE Group By Operator keys: _col0 (type: string) mode: hash outputColumnNames: _col0 - Statistics: Num rows: 83 Data size: 881 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 166 Data size: 1763 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 83 Data size: 881 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 166 Data size: 1763 Basic stats: COMPLETE Column stats: NONE Execution mode: vectorized Map 6 Map Operator Tree: @@ -1580,15 +1580,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col4 Statistics: Num rows: 182 Data size: 5033 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col1 = 0L) or (_col4 is null and _col0 is not null and (_col2 >= _col1))) (type: boolean) - Statistics: Num rows: 121 Data size: 3346 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col2 >= _col1) or (_col1 = 0L) or _col4 is not null or _col0 is null) and (_col0 is not null or (_col1 = 0L) or _col4 is not null) and (_col4 is null or (_col1 = 0L))) (type: boolean) + Statistics: Num rows: 182 Data size: 5033 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string) outputColumnNames: _col0 - Statistics: Num rows: 121 Data size: 3346 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 182 Data size: 5033 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 121 Data size: 3346 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 182 Data size: 5033 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -1600,16 +1600,16 @@ STAGE PLANS: keys: KEY._col0 (type: string) mode: mergepartial outputColumnNames: _col0 - Statistics: Num rows: 41 Data size: 435 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 83 Data size: 881 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), true (type: boolean) outputColumnNames: _col0, _col1 - Statistics: Num rows: 41 Data size: 435 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 83 Data size: 881 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 41 Data size: 435 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 83 Data size: 881 Basic stats: COMPLETE Column stats: NONE value expressions: _col1 (type: boolean) Reducer 7 Execution mode: vectorized @@ -1764,15 +1764,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col14 Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col10 = 0L)) THEN (true) WHEN (_col10 is null) THEN (true) WHEN (_col14 is not null) THEN (false) WHEN (_col5 is null) THEN (null) WHEN ((_col11 < _col10)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col11 < _col10) is not true or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null or _col5 is null) and (_col14 is null or ((_col10 = 0L) or _col10 is null) is true) and (_col5 is not null or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null)) (type: boolean) + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -1953,16 +1953,16 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col12 is null and _col5 is not null and (_col10 >= _col9)) or (_col9 = 0L)) (type: boolean) - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col10 >= _col9) or (_col9 = 0L) or _col12 is not null or _col5 is null) and (_col12 is null or (_col9 = 0L)) and (_col5 is not null or (_col9 = 0L) or _col12 is not null)) (type: boolean) + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: int) sort order: + - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE value expressions: _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) Reducer 4 Execution mode: vectorized @@ -1970,10 +1970,10 @@ STAGE PLANS: Select Operator expressions: KEY.reducesinkkey0 (type: int), VALUE._col0 (type: string), VALUE._col1 (type: string), VALUE._col2 (type: string), VALUE._col3 (type: string), VALUE._col4 (type: int), VALUE._col5 (type: string), VALUE._col6 (type: double), VALUE._col7 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -2165,15 +2165,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col12 is null and _col0 is not null and _col5 is not null and (_col10 >= _col9)) or (_col9 = 0L)) (type: boolean) - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col0 is not null and _col5 is not null) or (_col9 = 0L) or _col12 is not null) and ((_col10 >= _col9) or (_col9 = 0L) or _col12 is not null or _col0 is null or _col5 is null) and (_col12 is null or (_col9 = 0L))) (type: boolean) + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -2438,10 +2438,10 @@ STAGE PLANS: outputColumnNames: _col1, _col3, _col4, _col7 Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN ((_col1 + 100) is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col1 is null) and (_col1 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Select Operator - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Group By Operator aggregations: count() mode: hash @@ -2623,15 +2623,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col12 is null and _col7 is not null and (_col10 >= _col9)) or (_col9 = 0L)) (type: boolean) - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col10 >= _col9) or (_col9 = 0L) or _col12 is not null or _col7 is null) and (_col12 is null or (_col9 = 0L)) and (_col7 is not null or (_col9 = 0L) or _col12 is not null)) (type: boolean) + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -2744,14 +2744,10 @@ STAGE PLANS: Stage: Stage-1 Spark Edges: - Reducer 10 <- Map 9 (PARTITION-LEVEL SORT, 2), Reducer 13 (PARTITION-LEVEL SORT, 2) - Reducer 11 <- Reducer 10 (GROUP, 2) - Reducer 13 <- Map 12 (GROUP, 2) - Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 2), Reducer 6 (PARTITION-LEVEL SORT, 2) - Reducer 3 <- Reducer 11 (PARTITION-LEVEL SORT, 2), Reducer 2 (PARTITION-LEVEL SORT, 2) - Reducer 5 <- Map 4 (PARTITION-LEVEL SORT, 2), Reducer 8 (PARTITION-LEVEL SORT, 2) - Reducer 6 <- Reducer 5 (GROUP, 2) - Reducer 8 <- Map 12 (GROUP, 2) + Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 2), Reducer 5 (PARTITION-LEVEL SORT, 2) + Reducer 3 <- Reducer 2 (PARTITION-LEVEL SORT, 2), Reducer 7 (PARTITION-LEVEL SORT, 2) + Reducer 5 <- Map 4 (GROUP, 2) + Reducer 7 <- Map 6 (GROUP, 2) #### A masked pattern was here #### Vertices: Map 1 @@ -2770,121 +2766,56 @@ STAGE PLANS: Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE value expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col6 (type: string), _col7 (type: double), _col8 (type: string) Execution mode: vectorized - Map 12 - Map Operator Tree: - TableScan - alias: part - filterExpr: p_size is not null (type: boolean) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Filter Operator - predicate: p_size is not null (type: boolean) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Group By Operator - keys: p_size (type: int) - mode: hash - outputColumnNames: _col0 - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: int) - sort order: + - Map-reduce partition columns: _col0 (type: int) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Execution mode: vectorized Map 4 Map Operator Tree: TableScan alias: p - filterExpr: (p_size is not null and p_partkey is not null) (type: boolean) + filterExpr: (((p_size + 121150) = p_partkey) and p_size is not null) (type: boolean) Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (p_partkey is not null and p_size is not null) (type: boolean) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + predicate: (((p_size + 121150) = p_partkey) and p_size is not null) (type: boolean) + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: p_partkey (type: int), p_name (type: string), p_size (type: int) - outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col2 (type: int), _col0 (type: int) - sort order: ++ - Map-reduce partition columns: _col2 (type: int), _col0 (type: int) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - value expressions: _col1 (type: string) + expressions: p_name (type: string), p_size (type: int) + outputColumnNames: p_name, p_size + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + Group By Operator + aggregations: count(), count(p_name) + keys: p_size (type: int) + mode: hash + outputColumnNames: _col0, _col1, _col2 + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: int) + sort order: + + Map-reduce partition columns: _col0 (type: int) + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + value expressions: _col1 (type: bigint), _col2 (type: bigint) Execution mode: vectorized - Map 9 + Map 6 Map Operator Tree: TableScan alias: p - filterExpr: (p_size is not null and p_partkey is not null and p_name is not null) (type: boolean) + filterExpr: (((p_size + 121150) = p_partkey) and p_size is not null and p_name is not null) (type: boolean) Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (p_name is not null and p_partkey is not null and p_size is not null) (type: boolean) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE + predicate: (((p_size + 121150) = p_partkey) and p_name is not null and p_size is not null) (type: boolean) + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: p_partkey (type: int), p_name (type: string), p_size (type: int) - outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col2 (type: int), _col0 (type: int) - sort order: ++ - Map-reduce partition columns: _col2 (type: int), _col0 (type: int) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - value expressions: _col1 (type: string) - Execution mode: vectorized - Reducer 10 - Reduce Operator Tree: - Join Operator - condition map: - Inner Join 0 to 1 - keys: - 0 _col2 (type: int), _col0 (type: int) - 1 _col0 (type: int), _col1 (type: int) - outputColumnNames: _col1, _col3 - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE - Group By Operator - keys: _col1 (type: string), _col3 (type: int) - mode: hash - outputColumnNames: _col0, _col1 - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: string), _col1 (type: int) - sort order: ++ - Map-reduce partition columns: _col0 (type: string), _col1 (type: int) - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE - Reducer 11 - Execution mode: vectorized - Reduce Operator Tree: - Group By Operator - keys: KEY._col0 (type: string), KEY._col1 (type: int) - mode: mergepartial - outputColumnNames: _col0, _col1 - Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE - Select Operator - expressions: _col0 (type: string), _col1 (type: int), true (type: boolean) - outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: string), _col1 (type: int) - sort order: ++ - Map-reduce partition columns: _col0 (type: string), _col1 (type: int) - Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE - value expressions: _col2 (type: boolean) - Reducer 13 + expressions: p_name (type: string), p_size (type: int) + outputColumnNames: p_name, p_size + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + Group By Operator + keys: p_name (type: string), p_size (type: int) + mode: hash + outputColumnNames: _col0, _col1 + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + key expressions: _col0 (type: string), _col1 (type: int) + sort order: ++ + Map-reduce partition columns: _col0 (type: string), _col1 (type: int) + Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE Execution mode: vectorized - Reduce Operator Tree: - Group By Operator - keys: KEY._col0 (type: int) - mode: mergepartial - outputColumnNames: _col0 - Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE - Select Operator - expressions: _col0 (type: int), (_col0 + 121150) (type: int) - outputColumnNames: _col0, _col1 - Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: int), _col1 (type: int) - sort order: ++ - Map-reduce partition columns: _col0 (type: int), _col1 (type: int) - Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE Reducer 2 Reduce Operator Tree: Join Operator @@ -2912,42 +2843,20 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col14 Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col10 = 0L)) THEN (true) WHEN (_col10 is null) THEN (true) WHEN (_col14 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col11 < _col10)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col11 < _col10) is not true or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null or _col1 is null) and (_col1 is not null or ((_col10 = 0L) or _col10 is null) is true or _col14 is not null) and (_col14 is null or ((_col10 = 0L) or _col10 is null) is true)) (type: boolean) + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe Reducer 5 - Reduce Operator Tree: - Join Operator - condition map: - Inner Join 0 to 1 - keys: - 0 _col2 (type: int), _col0 (type: int) - 1 _col0 (type: int), _col1 (type: int) - outputColumnNames: _col1, _col3 - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE - Group By Operator - aggregations: count(), count(_col1) - keys: _col3 (type: int) - mode: hash - outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - key expressions: _col0 (type: int) - sort order: + - Map-reduce partition columns: _col0 (type: int) - Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE - value expressions: _col1 (type: bigint), _col2 (type: bigint) - Reducer 6 Execution mode: vectorized Reduce Operator Tree: Group By Operator @@ -2955,30 +2864,31 @@ STAGE PLANS: keys: KEY._col0 (type: int) mode: mergepartial outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 6 Data size: 726 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: int) sort order: + Map-reduce partition columns: _col0 (type: int) - Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 6 Data size: 726 Basic stats: COMPLETE Column stats: NONE value expressions: _col1 (type: bigint), _col2 (type: bigint) - Reducer 8 + Reducer 7 Execution mode: vectorized Reduce Operator Tree: Group By Operator - keys: KEY._col0 (type: int) + keys: KEY._col0 (type: string), KEY._col1 (type: int) mode: mergepartial - outputColumnNames: _col0 - Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + outputColumnNames: _col0, _col1 + Statistics: Num rows: 6 Data size: 726 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: _col0 (type: int), (_col0 + 121150) (type: int) - outputColumnNames: _col0, _col1 - Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + expressions: _col0 (type: string), _col1 (type: int), true (type: boolean) + outputColumnNames: _col0, _col1, _col2 + Statistics: Num rows: 6 Data size: 726 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator - key expressions: _col0 (type: int), _col1 (type: int) + key expressions: _col0 (type: string), _col1 (type: int) sort order: ++ - Map-reduce partition columns: _col0 (type: int), _col1 (type: int) - Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + Map-reduce partition columns: _col0 (type: string), _col1 (type: int) + Statistics: Num rows: 6 Data size: 726 Basic stats: COMPLETE Column stats: NONE + value expressions: _col2 (type: boolean) Stage: Stage-0 Fetch Operator @@ -3125,15 +3035,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col11, _col12, _col16 Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col11 = 0L)) THEN (true) WHEN (_col11 is null) THEN (true) WHEN (_col16 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col12 < _col11)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col12 < _col11) is not true or ((_col11 = 0L) or _col11 is null) is true or _col16 is not null or _col1 is null) and (_col1 is not null or ((_col11 = 0L) or _col11 is null) is true or _col16 is not null) and (_col16 is null or ((_col11 = 0L) or _col11 is null) is true)) (type: boolean) + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -3301,15 +3211,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col4, _col5, _col8 Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col1 is null) and (_col1 is not null or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) (type: boolean) + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string) outputColumnNames: _col0 - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -3546,15 +3456,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col4, _col5, _col8 Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col1 is null) and (_col1 is not null or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) (type: boolean) + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string) outputColumnNames: _col0 - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -3814,23 +3724,23 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col5 Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col2 = 0L) or (_col5 is null and _col1 is not null and (_col3 >= _col2))) (type: boolean) - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col1 is null) and (_col1 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string) outputColumnNames: _col0 - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE Group By Operator aggregations: count() keys: _col0 (type: string) mode: hash outputColumnNames: _col0, _col1 - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE value expressions: _col1 (type: bigint) Reducer 4 Execution mode: vectorized @@ -3840,15 +3750,15 @@ STAGE PLANS: keys: KEY._col0 (type: string) mode: mergepartial outputColumnNames: _col0, _col1 - Statistics: Num rows: 183 Data size: 5055 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 275 Data size: 7596 Basic stats: COMPLETE Column stats: NONE Filter Operator predicate: _col1 is not null (type: boolean) - Statistics: Num rows: 183 Data size: 5055 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 275 Data size: 7596 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col1 (type: bigint) sort order: + Map-reduce partition columns: _col1 (type: bigint) - Statistics: Num rows: 183 Data size: 5055 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 275 Data size: 7596 Basic stats: COMPLETE Column stats: NONE value expressions: _col0 (type: string) Reducer 5 Reduce Operator Tree: @@ -3859,10 +3769,10 @@ STAGE PLANS: 0 _col1 (type: bigint) 1 _col0 (type: bigint) outputColumnNames: _col0, _col1 - Statistics: Num rows: 201 Data size: 5560 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 302 Data size: 8355 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 201 Data size: 5560 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 302 Data size: 8355 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -4116,23 +4026,23 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col3, _col4, _col7 Statistics: Num rows: 605 Data size: 6427 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 302 Data size: 3208 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col1 is null) and (_col1 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 604 Data size: 6416 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string) outputColumnNames: _col0 - Statistics: Num rows: 302 Data size: 3208 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 604 Data size: 6416 Basic stats: COMPLETE Column stats: NONE Group By Operator aggregations: count() keys: _col0 (type: string) mode: hash outputColumnNames: _col0, _col1 - Statistics: Num rows: 302 Data size: 3208 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 604 Data size: 6416 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 302 Data size: 3208 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 604 Data size: 6416 Basic stats: COMPLETE Column stats: NONE value expressions: _col1 (type: bigint) Reducer 4 Execution mode: vectorized @@ -4142,15 +4052,15 @@ STAGE PLANS: keys: KEY._col0 (type: string) mode: mergepartial outputColumnNames: _col0, _col1 - Statistics: Num rows: 151 Data size: 1604 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 302 Data size: 3208 Basic stats: COMPLETE Column stats: NONE Filter Operator predicate: _col1 is not null (type: boolean) - Statistics: Num rows: 151 Data size: 1604 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 302 Data size: 3208 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col1 (type: bigint) sort order: + Map-reduce partition columns: _col1 (type: bigint) - Statistics: Num rows: 151 Data size: 1604 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 302 Data size: 3208 Basic stats: COMPLETE Column stats: NONE value expressions: _col0 (type: string) Reducer 5 Reduce Operator Tree: @@ -4161,10 +4071,10 @@ STAGE PLANS: 0 _col1 (type: bigint) 1 _col0 (type: bigint) outputColumnNames: _col0, _col1 - Statistics: Num rows: 166 Data size: 1764 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 332 Data size: 3528 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 166 Data size: 1764 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 332 Data size: 3528 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -4353,16 +4263,16 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col12 is null and _col5 is not null and (_col10 >= _col9)) or (_col9 = 0L)) (type: boolean) - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col10 >= _col9) or (_col9 = 0L) or _col12 is not null or _col5 is null) and (_col12 is null or (_col9 = 0L)) and (_col5 is not null or (_col9 = 0L) or _col12 is not null)) (type: boolean) + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col3 (type: string) sort order: + - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE value expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) Reducer 4 Execution mode: vectorized @@ -4370,10 +4280,10 @@ STAGE PLANS: Select Operator expressions: VALUE._col0 (type: int), VALUE._col1 (type: string), VALUE._col2 (type: string), KEY.reducesinkkey0 (type: string), VALUE._col3 (type: string), VALUE._col4 (type: int), VALUE._col5 (type: string), VALUE._col6 (type: double), VALUE._col7 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -4578,16 +4488,16 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col12 is null and _col5 is not null and (_col10 >= _col9)) or (_col9 = 0L)) (type: boolean) - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col10 >= _col9) or (_col9 = 0L) or _col12 is not null or _col5 is null) and (_col12 is null or (_col9 = 0L)) and (_col5 is not null or (_col9 = 0L) or _col12 is not null)) (type: boolean) + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col3 (type: string), _col0 (type: int) sort order: ++ - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE TopN Hash Memory Usage: 0.1 value expressions: _col1 (type: string), _col2 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) Reducer 4 @@ -4596,7 +4506,7 @@ STAGE PLANS: Select Operator expressions: KEY.reducesinkkey1 (type: int), VALUE._col0 (type: string), VALUE._col1 (type: string), KEY.reducesinkkey0 (type: string), VALUE._col2 (type: string), VALUE._col3 (type: int), VALUE._col4 (type: string), VALUE._col5 (type: double), VALUE._col6 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 18 Data size: 2530 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Limit Number of rows: 4 Statistics: Num rows: 4 Data size: 560 Basic stats: COMPLETE Column stats: NONE @@ -4838,15 +4748,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col5 Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col2 = 0L) or (_col5 is null and _col0 is not null and (_col3 >= _col2))) (type: boolean) - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col0 is null) and (_col0 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: string) outputColumnNames: _col0, _col1 - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -5543,10 +5453,10 @@ STAGE PLANS: outputColumnNames: _col1, _col3, _col4, _col7 Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN ((_col1 + 100) is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col1 is null) and (_col1 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Select Operator - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Group By Operator aggregations: count() mode: hash @@ -5779,15 +5689,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col4 Statistics: Num rows: 4 Data size: 412 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col1 = 0L) or (_col4 is null and _col0 is not null and (_col2 >= _col1))) (type: boolean) - Statistics: Num rows: 2 Data size: 206 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col2 >= _col1) or (_col1 = 0L) or _col4 is not null or _col0 is null) and (_col0 is not null or (_col1 = 0L) or _col4 is not null) and (_col4 is null or (_col1 = 0L))) (type: boolean) + Statistics: Num rows: 4 Data size: 412 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int) outputColumnNames: _col0 - Statistics: Num rows: 2 Data size: 206 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 4 Data size: 412 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 2 Data size: 206 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 4 Data size: 412 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -6027,15 +5937,15 @@ STAGE PLANS: outputColumnNames: _col0, _col3, _col4, _col7 Statistics: Num rows: 4 Data size: 378 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 2 Data size: 189 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col0 is null) and (_col0 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 4 Data size: 378 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int) outputColumnNames: _col0 - Statistics: Num rows: 2 Data size: 189 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 4 Data size: 378 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 2 Data size: 189 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 4 Data size: 378 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -6277,15 +6187,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col3, _col4, _col7 Statistics: Num rows: 3 Data size: 9 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col1 is null) and (_col1 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 2 Data size: 6 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int) outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 6 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 6 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -6508,15 +6418,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col3, _col4, _col6 Statistics: Num rows: 4 Data size: 19 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col6 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 2 Data size: 9 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col6 is not null or _col1 is null) and (_col1 is not null or ((_col3 = 0L) or _col3 is null) is true or _col6 is not null) and (_col6 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 4 Data size: 19 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: int) outputColumnNames: _col0, _col1 - Statistics: Num rows: 2 Data size: 9 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 4 Data size: 19 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 2 Data size: 9 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 4 Data size: 19 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -6749,15 +6659,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col3, _col4, _col6 Statistics: Num rows: 6 Data size: 22 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col6 is not null) THEN (false) WHEN (_col1 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 3 Data size: 11 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col6 is not null or _col1 is null) and (_col1 is not null or ((_col3 = 0L) or _col3 is null) is true or _col6 is not null) and (_col6 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 6 Data size: 22 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int) outputColumnNames: _col0 - Statistics: Num rows: 3 Data size: 11 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 6 Data size: 22 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 3 Data size: 11 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 6 Data size: 22 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -6949,15 +6859,15 @@ STAGE PLANS: outputColumnNames: _col0, _col3, _col4, _col7 Statistics: Num rows: 3 Data size: 12 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col0 is null) and (_col0 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 2 Data size: 8 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int) outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 8 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 8 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -7118,15 +7028,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col5 Statistics: Num rows: 3 Data size: 62 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col2 = 0L) or (_col5 is null and _col1 is not null and (_col3 >= _col2))) (type: boolean) - Statistics: Num rows: 1 Data size: 20 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col1 is null) and (_col1 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) + Statistics: Num rows: 2 Data size: 41 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int) outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 20 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 41 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 20 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 41 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -7285,15 +7195,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col4 Statistics: Num rows: 3 Data size: 62 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col1 = 0L) or (_col4 is null and _col0 is not null and (_col2 >= _col1))) (type: boolean) - Statistics: Num rows: 1 Data size: 20 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col2 >= _col1) or (_col1 = 0L) or _col4 is not null or _col0 is null) and (_col0 is not null or (_col1 = 0L) or _col4 is not null) and (_col4 is null or (_col1 = 0L))) (type: boolean) + Statistics: Num rows: 2 Data size: 41 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int) outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 20 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 41 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 20 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 41 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -7505,15 +7415,15 @@ STAGE PLANS: residual filter predicates: {(_col1 > _col6)} Statistics: Num rows: 8367 Data size: 186148 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 4183 Data size: 93062 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col0 is null) and (_col0 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 8366 Data size: 186125 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: string) outputColumnNames: _col0, _col1 - Statistics: Num rows: 4183 Data size: 93062 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 8366 Data size: 186125 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 4183 Data size: 93062 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 8366 Data size: 186125 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat diff --git ql/src/test/results/clientpositive/spark/subquery_null_agg.q.out ql/src/test/results/clientpositive/spark/subquery_null_agg.q.out index 4223d6dc99..aa079cc18a 100644 --- ql/src/test/results/clientpositive/spark/subquery_null_agg.q.out +++ ql/src/test/results/clientpositive/spark/subquery_null_agg.q.out @@ -6,8 +6,8 @@ POSTHOOK: query: CREATE TABLE table_7 (int_col INT) POSTHOOK: type: CREATETABLE POSTHOOK: Output: database:default POSTHOOK: Output: default@table_7 -Warning: Shuffle Join JOIN[21][tables = [$hdt$_0, $hdt$_1]] in Work 'Reducer 2' is a cross product -Warning: Shuffle Join JOIN[24][tables = [$hdt$_0, $hdt$_1, $hdt$_2]] in Work 'Reducer 3' is a cross product +Warning: Shuffle Join JOIN[16][tables = [$hdt$_0, $hdt$_1]] in Work 'Reducer 2' is a cross product +Warning: Shuffle Join JOIN[19][tables = [$hdt$_0, $hdt$_1, $hdt$_2]] in Work 'Reducer 3' is a cross product PREHOOK: query: explain SELECT (t1.int_col) * (t1.int_col) AS int_col @@ -58,10 +58,9 @@ STAGE PLANS: Stage: Stage-1 Spark Edges: - Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 1), Reducer 5 (PARTITION-LEVEL SORT, 1) - Reducer 3 <- Reducer 2 (PARTITION-LEVEL SORT, 1), Reducer 7 (PARTITION-LEVEL SORT, 1) - Reducer 5 <- Map 4 (GROUP, 2) - Reducer 7 <- Map 6 (GROUP, 1) + Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 1), Map 4 (PARTITION-LEVEL SORT, 1) + Reducer 3 <- Reducer 2 (PARTITION-LEVEL SORT, 1), Reducer 6 (PARTITION-LEVEL SORT, 1) + Reducer 6 <- Map 5 (GROUP, 1) #### A masked pattern was here #### Vertices: Map 1 @@ -85,18 +84,16 @@ STAGE PLANS: Filter Operator predicate: false (type: boolean) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE - Group By Operator - keys: true (type: boolean) - mode: hash + Select Operator + expressions: true (type: boolean) outputColumnNames: _col0 Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE Reduce Output Operator - key expressions: _col0 (type: boolean) - sort order: + - Map-reduce partition columns: _col0 (type: boolean) + sort order: Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE + value expressions: _col0 (type: boolean) Execution mode: vectorized - Map 6 + Map 5 Map Operator Tree: TableScan alias: table_7 @@ -138,14 +135,14 @@ STAGE PLANS: keys: 0 1 - outputColumnNames: _col1, _col2 + outputColumnNames: _col1, _col2, _col3 Statistics: Num rows: 1 Data size: 10 Basic stats: PARTIAL Column stats: NONE Select Operator - expressions: _col2 (type: bigint), _col1 (type: boolean) - outputColumnNames: _col1, _col2 + expressions: _col2 (type: bigint), _col3 (type: bigint), _col1 (type: boolean) + outputColumnNames: _col1, _col2, _col3 Statistics: Num rows: 1 Data size: 10 Basic stats: PARTIAL Column stats: NONE Filter Operator - predicate: ((_col1 = 0L) or _col2 is null) (type: boolean) + predicate: ((_col1 = 0L) or (_col3 is null and (_col2 >= _col1))) (type: boolean) Statistics: Num rows: 1 Data size: 10 Basic stats: PARTIAL Column stats: NONE Select Operator expressions: null (type: void) @@ -158,23 +155,7 @@ STAGE PLANS: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe - Reducer 5 - Execution mode: vectorized - Reduce Operator Tree: - Group By Operator - keys: KEY._col0 (type: boolean) - mode: mergepartial - outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE - Select Operator - expressions: true (type: boolean) - outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE - Reduce Output Operator - sort order: - Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: COMPLETE - value expressions: _col0 (type: boolean) - Reducer 7 + Reducer 6 Execution mode: vectorized Reduce Operator Tree: Group By Operator @@ -182,10 +163,14 @@ STAGE PLANS: mode: mergepartial outputColumnNames: _col0 Statistics: Num rows: 1 Data size: 8 Basic stats: PARTIAL Column stats: COMPLETE - Reduce Output Operator - sort order: + Select Operator + expressions: _col0 (type: bigint), _col0 (type: bigint) + outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 8 Basic stats: PARTIAL Column stats: COMPLETE - value expressions: _col0 (type: bigint) + Reduce Output Operator + sort order: + Statistics: Num rows: 1 Data size: 8 Basic stats: PARTIAL Column stats: COMPLETE + value expressions: _col0 (type: bigint), _col1 (type: bigint) Stage: Stage-0 Fetch Operator diff --git ql/src/test/results/clientpositive/spark/subquery_scalar.q.out ql/src/test/results/clientpositive/spark/subquery_scalar.q.out index d7d652f34c..975f6010c1 100644 --- ql/src/test/results/clientpositive/spark/subquery_scalar.q.out +++ ql/src/test/results/clientpositive/spark/subquery_scalar.q.out @@ -332,7 +332,7 @@ STAGE PLANS: Processor Tree: ListSink -Warning: Shuffle Join JOIN[18][tables = [$hdt$_1, $hdt$_2, $hdt$_0]] in Work 'Reducer 3' is a cross product +Warning: Shuffle Join JOIN[19][tables = [$hdt$_0, $hdt$_1, $hdt$_2]] in Work 'Reducer 2' is a cross product PREHOOK: query: explain select * from part where p_name = (select p_name from part_null_n0 where p_name is null) PREHOOK: type: QUERY PREHOOK: Input: default@part @@ -351,81 +351,62 @@ STAGE PLANS: Stage: Stage-1 Spark Edges: - Reducer 2 <- Map 1 (GROUP, 1) - Reducer 3 <- Map 4 (PARTITION-LEVEL SORT, 1), Map 5 (PARTITION-LEVEL SORT, 1), Reducer 2 (PARTITION-LEVEL SORT, 1) + Reducer 2 <- Map 1 (PARTITION-LEVEL SORT, 1), Map 5 (PARTITION-LEVEL SORT, 1), Reducer 4 (PARTITION-LEVEL SORT, 1) + Reducer 4 <- Map 3 (GROUP, 1) #### A masked pattern was here #### Vertices: Map 1 Map Operator Tree: TableScan - alias: part_null_n0 - filterExpr: p_name is null (type: boolean) - Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: NONE + alias: part + Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: p_name is null (type: boolean) - Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: NONE + predicate: false (type: boolean) + Statistics: Num rows: 1 Data size: 121 Basic stats: COMPLETE Column stats: NONE Select Operator - Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: NONE + expressions: p_partkey (type: int), p_name (type: string), p_mfgr (type: string), p_brand (type: string), p_type (type: string), p_size (type: int), p_container (type: string), p_retailprice (type: double), p_comment (type: string) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 + Statistics: Num rows: 1 Data size: 121 Basic stats: COMPLETE Column stats: NONE + Reduce Output Operator + sort order: + Statistics: Num rows: 1 Data size: 121 Basic stats: COMPLETE Column stats: NONE + value expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) + Execution mode: vectorized + Map 3 + Map Operator Tree: + TableScan + alias: part_null_n0 + Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: COMPLETE + Select Operator + Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: COMPLETE + Filter Operator + predicate: false (type: boolean) + Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: COMPLETE Group By Operator - aggregations: count() + aggregations: count(0) mode: hash outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator sort order: - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE value expressions: _col0 (type: bigint) Execution mode: vectorized - Map 4 - Map Operator Tree: - TableScan - alias: part_null_n0 - filterExpr: p_name is null (type: boolean) - Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: NONE - Filter Operator - predicate: p_name is null (type: boolean) - Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: NONE - Select Operator - Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - sort order: - Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: NONE - Execution mode: vectorized Map 5 Map Operator Tree: TableScan - alias: part - filterExpr: (p_name = null) (type: boolean) - Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - Filter Operator - predicate: (p_name = null) (type: boolean) - Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE - Select Operator - expressions: p_partkey (type: int), p_mfgr (type: string), p_brand (type: string), p_type (type: string), p_size (type: int), p_container (type: string), p_retailprice (type: double), p_comment (type: string) - outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7 - Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE + alias: part_null_n0 + Statistics: Num rows: 1 Data size: 32560 Basic stats: COMPLETE Column stats: COMPLETE + Select Operator + Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: COMPLETE + Filter Operator + predicate: false (type: boolean) + Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: COMPLETE Reduce Output Operator sort order: - Statistics: Num rows: 13 Data size: 1573 Basic stats: COMPLETE Column stats: NONE - value expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: string), _col6 (type: double), _col7 (type: string) + Statistics: Num rows: 1 Data size: 4 Basic stats: COMPLETE Column stats: COMPLETE Execution mode: vectorized Reducer 2 - Execution mode: vectorized - Reduce Operator Tree: - Group By Operator - aggregations: count(VALUE._col0) - mode: mergepartial - outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE - Filter Operator - predicate: (sq_count_check(_col0) <= 1) (type: boolean) - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE - Select Operator - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE - Reduce Output Operator - sort order: - Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: NONE - Reducer 3 Reduce Operator Tree: Join Operator condition map: @@ -435,19 +416,28 @@ STAGE PLANS: 0 1 2 - outputColumnNames: _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9 - Statistics: Num rows: 13 Data size: 424970 Basic stats: COMPLETE Column stats: NONE + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 + Statistics: Num rows: 1 Data size: 134 Basic stats: COMPLETE Column stats: NONE + File Output Operator + compressed: false + Statistics: Num rows: 1 Data size: 134 Basic stats: COMPLETE Column stats: NONE + table: + input format: org.apache.hadoop.mapred.SequenceFileInputFormat + output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat + serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + Reducer 4 + Execution mode: vectorized + Reduce Operator Tree: + Group By Operator + aggregations: count(VALUE._col0) + mode: mergepartial + outputColumnNames: _col0 + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE Select Operator - expressions: _col2 (type: int), null (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: string), _col6 (type: int), _col7 (type: string), _col8 (type: double), _col9 (type: string) - outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 13 Data size: 424970 Basic stats: COMPLETE Column stats: NONE - File Output Operator - compressed: false - Statistics: Num rows: 13 Data size: 424970 Basic stats: COMPLETE Column stats: NONE - table: - input format: org.apache.hadoop.mapred.SequenceFileInputFormat - output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat - serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE + Reduce Output Operator + sort order: + Statistics: Num rows: 1 Data size: 8 Basic stats: COMPLETE Column stats: COMPLETE Stage: Stage-0 Fetch Operator @@ -455,7 +445,7 @@ STAGE PLANS: Processor Tree: ListSink -Warning: Shuffle Join JOIN[18][tables = [$hdt$_1, $hdt$_2, $hdt$_0]] in Work 'Reducer 3' is a cross product +Warning: Shuffle Join JOIN[19][tables = [$hdt$_0, $hdt$_1, $hdt$_2]] in Work 'Reducer 2' is a cross product PREHOOK: query: select * from part where p_name = (select p_name from part_null_n0 where p_name is null) PREHOOK: type: QUERY PREHOOK: Input: default@part @@ -3413,15 +3403,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col10, _col11, _col13 Statistics: Num rows: 7 Data size: 2279 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col10 = 0L) or (_col13 is null and _col3 is not null and (_col11 >= _col10))) (type: boolean) - Statistics: Num rows: 4 Data size: 1302 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col11 >= _col10) or (_col10 = 0L) or _col13 is not null or _col3 is null) and (_col13 is null or (_col10 = 0L)) and (_col3 is not null or (_col10 = 0L) or _col13 is not null)) (type: boolean) + Statistics: Num rows: 6 Data size: 1953 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 4 Data size: 1302 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 6 Data size: 1953 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 4 Data size: 1302 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 6 Data size: 1953 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -3670,17 +3660,17 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col12 Statistics: Num rows: 14 Data size: 1968 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col12 is null and _col3 is not null and (_col10 >= _col9)) or (_col9 = 0L)) (type: boolean) - Statistics: Num rows: 9 Data size: 1265 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col10 >= _col9) or (_col9 = 0L) or _col12 is not null or _col3 is null) and (_col12 is null or (_col9 = 0L)) and (_col3 is not null or (_col9 = 0L) or _col12 is not null)) (type: boolean) + Statistics: Num rows: 14 Data size: 1968 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 9 Data size: 1265 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 14 Data size: 1968 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col4 (type: string) sort order: + Map-reduce partition columns: _col4 (type: string) - Statistics: Num rows: 9 Data size: 1265 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 14 Data size: 1968 Basic stats: COMPLETE Column stats: NONE value expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) Reducer 5 Reduce Operator Tree: @@ -3691,17 +3681,17 @@ STAGE PLANS: 0 _col4 (type: string) 1 _col1 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9 - Statistics: Num rows: 9 Data size: 1391 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 15 Data size: 2164 Basic stats: COMPLETE Column stats: NONE Filter Operator predicate: (not (_col1 like _col9)) (type: boolean) - Statistics: Num rows: 5 Data size: 772 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 8 Data size: 1154 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: string), _col5 (type: int), _col6 (type: string), _col7 (type: double), _col8 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 5 Data size: 772 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 8 Data size: 1154 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 5 Data size: 772 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 8 Data size: 1154 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -6269,15 +6259,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3 Statistics: Num rows: 2 Data size: 6 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN (_col3 is null) THEN (true) ELSE ((_col2 = 0L)) END (type: boolean) - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + predicate: ((_col2 = 0L) or _col3 is null) (type: boolean) + Statistics: Num rows: 2 Data size: 6 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: int) outputColumnNames: _col0, _col1 - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 6 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 3 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 6 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -6610,15 +6600,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3 Statistics: Num rows: 2 Data size: 6 Basic stats: PARTIAL Column stats: NONE Filter Operator - predicate: CASE WHEN (_col3 is null) THEN (true) ELSE ((_col2 = 0L)) END (type: boolean) - Statistics: Num rows: 1 Data size: 3 Basic stats: PARTIAL Column stats: NONE + predicate: ((_col2 = 0L) or _col3 is null) (type: boolean) + Statistics: Num rows: 2 Data size: 6 Basic stats: PARTIAL Column stats: NONE Select Operator expressions: _col0 (type: int), _col1 (type: int) outputColumnNames: _col0, _col1 - Statistics: Num rows: 1 Data size: 3 Basic stats: PARTIAL Column stats: NONE + Statistics: Num rows: 2 Data size: 6 Basic stats: PARTIAL Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 3 Basic stats: PARTIAL Column stats: NONE + Statistics: Num rows: 2 Data size: 6 Basic stats: PARTIAL Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -7112,7 +7102,7 @@ HiveProject(ss_sold_date_sk=[$0], ss_quantity=[$1], ss_list_price=[$2]) HiveJoin(condition=[>($2, $3)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(ss_sold_date_sk=[$0], ss_quantity=[$1], ss_list_price=[$2]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject($f0=[/($0, $1)]) + HiveProject(average_sales=[/($0, $1)]) HiveAggregate(group=[{}], agg#0=[sum($0)], agg#1=[count($0)]) HiveProject($f0=[*(CAST($1):DECIMAL(10, 0), $2)]) HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) @@ -7156,7 +7146,7 @@ HiveProject(ss_sold_date_sk=[$0], ss_quantity=[$1], ss_list_price=[$2]) HiveJoin(condition=[>($2, $3)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(ss_sold_date_sk=[$0], ss_quantity=[$1], ss_list_price=[$2]) HiveTableScan(table=[[default, store_sales]], table:alias=[store_sales]) - HiveProject(avg_window_0=[avg(*(CAST($1):DECIMAL(10, 0), $2)) OVER (PARTITION BY $2 ORDER BY $2 NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)]) + HiveProject(average_sales=[avg(*(CAST($1):DECIMAL(10, 0), $2)) OVER (PARTITION BY $2 ORDER BY $2 NULLS FIRST ROWS BETWEEN 2147483647 FOLLOWING AND 2147483647 PRECEDING)]) HiveJoin(condition=[=($0, $3)], joinType=[inner], algorithm=[none], cost=[not available]) HiveProject(ss_sold_date_sk=[$0], ss_quantity=[$1], ss_list_price=[$2]) HiveFilter(condition=[IS NOT NULL($0)]) diff --git ql/src/test/results/clientpositive/spark/subquery_select.q.out ql/src/test/results/clientpositive/spark/subquery_select.q.out index ead76b42b0..04056382fa 100644 --- ql/src/test/results/clientpositive/spark/subquery_select.q.out +++ ql/src/test/results/clientpositive/spark/subquery_select.q.out @@ -85,7 +85,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col3, _col4, _col5 Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: _col0 (type: int), CASE WHEN (_col4) THEN (false) WHEN (_col3 is not null) THEN (true) WHEN (_col1) THEN (null) WHEN (_col5) THEN (null) ELSE (false) END (type: boolean) + expressions: _col0 (type: int), ((_col3 is not null and _col4) or ((_col1 or _col5) and null and _col4 and _col3 is null)) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -127,7 +127,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: (_col0 = 0L) (type: boolean), (_col1 < _col0) (type: boolean) + expressions: (_col0 <> 0L) (type: boolean), (_col1 < _col0) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator @@ -271,7 +271,7 @@ STAGE PLANS: outputColumnNames: _col1, _col2, _col4, _col5, _col6, _col9 Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: _col1 (type: int), CASE WHEN (_col5) THEN (false) WHEN (_col4 is null) THEN (false) WHEN (_col9 is not null) THEN (true) WHEN (_col2) THEN (null) WHEN (_col6) THEN (null) ELSE (false) END (type: boolean) + expressions: _col1 (type: int), ((_col9 is not null and (_col5 or _col4 is null) is not true) or ((_col2 or _col6) is true and null and (_col5 or _col4 is null) is not true and _col9 is null)) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -406,15 +406,15 @@ STAGE PLANS: alias: part Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: p_size (type: int), p_size is null (type: boolean) - outputColumnNames: _col0, _col1 + expressions: p_size (type: int), p_size is null (type: boolean), p_size is not null (type: boolean) + outputColumnNames: _col0, _col1, _col2 Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: int) sort order: + Map-reduce partition columns: _col0 (type: int) Statistics: Num rows: 26 Data size: 3147 Basic stats: COMPLETE Column stats: NONE - value expressions: _col1 (type: boolean) + value expressions: _col1 (type: boolean), _col2 (type: boolean) Execution mode: vectorized Map 4 Map Operator Tree: @@ -443,12 +443,12 @@ STAGE PLANS: keys: 0 _col0 (type: int) 1 _col0 (type: int) - outputColumnNames: _col0, _col1, _col3 + outputColumnNames: _col0, _col1, _col2, _col4 Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator sort order: Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE - value expressions: _col0 (type: int), _col1 (type: boolean), _col3 (type: boolean) + value expressions: _col0 (type: int), _col1 (type: boolean), _col2 (type: boolean), _col4 (type: boolean) Reducer 3 Reduce Operator Tree: Join Operator @@ -457,10 +457,10 @@ STAGE PLANS: keys: 0 1 - outputColumnNames: _col0, _col1, _col3, _col4, _col5 + outputColumnNames: _col0, _col1, _col2, _col4, _col5, _col6, _col7, _col8 Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: _col0 (type: int), CASE WHEN (_col4) THEN (true) WHEN (_col3 is not null) THEN (false) WHEN (_col1) THEN (null) WHEN (_col5) THEN (null) ELSE (true) END (type: boolean) + expressions: _col0 (type: int), (_col5 or ((_col1 or _col6) and null and _col7 and _col4 is null) or (_col7 and _col4 is null and _col2 and _col8)) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -502,13 +502,13 @@ STAGE PLANS: outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: (_col0 = 0L) (type: boolean), (_col1 < _col0) (type: boolean) - outputColumnNames: _col0, _col1 + expressions: (_col0 = 0L) (type: boolean), (_col1 < _col0) (type: boolean), (_col0 <> 0L) (type: boolean), (_col1 >= _col0) (type: boolean) + outputColumnNames: _col0, _col1, _col2, _col3 Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator sort order: Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: NONE - value expressions: _col0 (type: boolean), _col1 (type: boolean) + value expressions: _col0 (type: boolean), _col1 (type: boolean), _col2 (type: boolean), _col3 (type: boolean) Stage: Stage-0 Fetch Operator @@ -713,7 +713,7 @@ STAGE PLANS: outputColumnNames: _col1, _col2, _col4, _col5, _col6, _col9 Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: _col1 (type: int), CASE WHEN (_col5) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col9 is not null) THEN (false) WHEN (_col2) THEN (null) WHEN (_col6) THEN (null) ELSE (true) END (type: boolean) + expressions: _col1 (type: int), ((_col5 or _col4 is null) is true or ((_col2 or _col6) is true and null and (_col5 or _col4 is null) is not true and _col9 is null) or ((_col5 or _col4 is null) is not true and _col9 is null and (_col2 or _col6) is not true)) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 14 Data size: 1730 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -2254,7 +2254,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col3, _col4, _col5 Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: _col0 (type: int), CASE WHEN (_col4) THEN (false) WHEN (_col3 is not null) THEN (true) WHEN (_col1) THEN (null) WHEN (_col5) THEN (null) ELSE (false) END (type: boolean) + expressions: _col0 (type: int), ((_col3 is not null and _col4) or ((_col1 or _col5) and null and _col4 and _col3 is null)) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -2291,7 +2291,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: (_col0 = 0L) (type: boolean), (_col1 < _col0) (type: boolean) + expressions: (_col0 <> 0L) (type: boolean), (_col1 < _col0) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator @@ -2836,7 +2836,7 @@ STAGE PLANS: outputColumnNames: _col1, _col2, _col3 Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: _col1 (type: int), CASE WHEN (_col3 is null) THEN (false) ELSE (_col2 is null) END (type: boolean) + expressions: _col1 (type: int), (_col2 is null and _col3 is not null) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 28 Data size: 3461 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -3226,7 +3226,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: (_col0 = 0L) (type: boolean), (_col1 < _col0) (type: boolean) + expressions: (_col0 <> 0L) (type: boolean), (_col1 < _col0) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 192 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator @@ -3290,7 +3290,7 @@ STAGE PLANS: outputColumnNames: _col2, _col3, _col4, _col6, _col7, _col8, _col11, _col13, _col14, _col15 Statistics: Num rows: 33 Data size: 10556 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: _col2 (type: int), (CASE WHEN (_col7) THEN (false) WHEN (_col6 is null) THEN (false) WHEN (_col11 is not null) THEN (true) WHEN (_col3) THEN (null) WHEN (_col8) THEN (null) ELSE (false) END and CASE WHEN (_col14) THEN (false) WHEN (_col13 is not null) THEN (true) WHEN (_col4) THEN (null) WHEN (_col15) THEN (null) ELSE (false) END) (type: boolean) + expressions: _col2 (type: int), (((_col11 is not null and (_col7 or _col6 is null) is not true) or ((_col3 or _col8) is true and null and (_col7 or _col6 is null) is not true and _col11 is null)) and ((_col13 is not null and _col14) or ((_col4 or _col15) and null and _col14 and _col13 is null))) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 33 Data size: 10556 Basic stats: COMPLETE Column stats: NONE File Output Operator @@ -3662,7 +3662,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: (_col0 = 0L) (type: boolean), (_col1 < _col0) (type: boolean) + expressions: (_col0 <> 0L) (type: boolean), (_col1 < _col0) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 1 Data size: 16 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator @@ -3706,7 +3706,7 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col3, _col4, _col5 Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: _col0 (type: int), CASE WHEN (_col4) THEN (false) WHEN (_col3 is not null) THEN (true) WHEN (_col1) THEN (null) WHEN (_col5) THEN (null) ELSE (false) END (type: boolean) + expressions: _col0 (type: int), ((_col3 is not null and _col4) or ((_col1 or _col5) and null and _col4 and _col3 is null)) (type: boolean) outputColumnNames: _col0, _col1 Statistics: Num rows: 28 Data size: 3937 Basic stats: COMPLETE Column stats: NONE File Output Operator diff --git ql/src/test/results/clientpositive/spark/subquery_views.q.out ql/src/test/results/clientpositive/spark/subquery_views.q.out index 30bcf4b43c..0d4408fb1c 100644 --- ql/src/test/results/clientpositive/spark/subquery_views.q.out +++ ql/src/test/results/clientpositive/spark/subquery_views.q.out @@ -256,22 +256,22 @@ STAGE PLANS: outputColumnNames: _col0, _col4, _col5, _col8 Statistics: Num rows: 365 Data size: 3878 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 182 Data size: 1933 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col0 is null) and (_col0 is not null or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) (type: boolean) + Statistics: Num rows: 364 Data size: 3867 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string) outputColumnNames: _col0 - Statistics: Num rows: 182 Data size: 1933 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 364 Data size: 3867 Basic stats: COMPLETE Column stats: NONE Group By Operator keys: _col0 (type: string) mode: hash outputColumnNames: _col0 - Statistics: Num rows: 182 Data size: 1933 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 364 Data size: 3867 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 182 Data size: 1933 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 364 Data size: 3867 Basic stats: COMPLETE Column stats: NONE Reducer 14 Execution mode: vectorized Reduce Operator Tree: @@ -347,17 +347,17 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col4, _col5, _col8 Statistics: Num rows: 365 Data size: 3878 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 182 Data size: 1933 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col0 is null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) (type: boolean) + Statistics: Num rows: 364 Data size: 3867 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: string) outputColumnNames: _col0, _col1 - Statistics: Num rows: 182 Data size: 1933 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 364 Data size: 3867 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: string) sort order: + Map-reduce partition columns: _col0 (type: string) - Statistics: Num rows: 182 Data size: 1933 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 364 Data size: 3867 Basic stats: COMPLETE Column stats: NONE value expressions: _col1 (type: string) Reducer 3 Reduce Operator Tree: @@ -368,10 +368,10 @@ STAGE PLANS: 0 _col0 (type: string) 1 _col0 (type: string) outputColumnNames: _col0, _col1 - Statistics: Num rows: 200 Data size: 2126 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 400 Data size: 4253 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 200 Data size: 2126 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 400 Data size: 4253 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat diff --git ql/src/test/results/clientpositive/spark/union22.q.out ql/src/test/results/clientpositive/spark/union22.q.out index 3798d87f7b..b587d62a7a 100644 --- ql/src/test/results/clientpositive/spark/union22.q.out +++ ql/src/test/results/clientpositive/spark/union22.q.out @@ -80,6 +80,17 @@ POSTHOOK: Input: default@dst_union22@ds=1 POSTHOOK: Input: default@dst_union22_delta POSTHOOK: Input: default@dst_union22_delta@ds=1 POSTHOOK: Output: default@dst_union22@ds=2 +OPTIMIZED SQL: SELECT `k1`, `k2`, `k3`, `k4` +FROM `default`.`dst_union22_delta` +WHERE `ds` = '1' AND `k0` <= 50 +UNION ALL +SELECT `t2`.`k1`, `t2`.`k2`, `t4`.`k3`, `t4`.`k4` +FROM (SELECT `k1`, `k2`, `ds` = '1' AS `=` +FROM `default`.`dst_union22` +WHERE `k1` > 20) AS `t2` +LEFT JOIN (SELECT `k1`, `k3`, `k4` +FROM `default`.`dst_union22_delta` +WHERE `ds` = '1' AND `k0` > 50 AND `k1` > 20) AS `t4` ON `t2`.`k1` = `t4`.`k1` AND `t2`.`=` STAGE DEPENDENCIES: Stage-3 is a root stage Stage-1 depends on stages: Stage-3 diff --git ql/src/test/results/clientpositive/spark/vectorization_0.q.out ql/src/test/results/clientpositive/spark/vectorization_0.q.out index ac8675cdf4..bd65620392 100644 --- ql/src/test/results/clientpositive/spark/vectorization_0.q.out +++ ql/src/test/results/clientpositive/spark/vectorization_0.q.out @@ -30749,6 +30749,9 @@ POSTHOOK: query: explain extended select * from alltypesorc where POSTHOOK: type: QUERY POSTHOOK: Input: default@alltypesorc #### A masked pattern was here #### +OPTIMIZED SQL: SELECT `ctinyint`, `csmallint`, `cint`, `cbigint`, `cfloat`, `cdouble`, `cstring1`, `cstring2`, `ctimestamp1`, `ctimestamp2`, `cboolean1`, `cboolean2` +FROM `default`.`alltypesorc` +WHERE ROW(`cint`, `cfloat`) IN (ROW(49, 3.5), ROW(47, 2.09), ROW(45, 3.02)) STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 @@ -30991,6 +30994,11 @@ POSTHOOK: query: explain extended select count(*),cstring1 from alltypesorc wher POSTHOOK: type: QUERY POSTHOOK: Input: default@alltypesorc #### A masked pattern was here #### +OPTIMIZED SQL: SELECT COUNT(*) AS `_o__c0`, `cstring1` +FROM `default`.`alltypesorc` +WHERE `cstring1` IN ('biology', 'history', 'topology') +GROUP BY `cstring1` +ORDER BY `cstring1` STAGE DEPENDENCIES: Stage-1 is a root stage Stage-0 depends on stages: Stage-1 diff --git ql/src/test/results/clientpositive/spark/vectorization_5.q.out ql/src/test/results/clientpositive/spark/vectorization_5.q.out index 1a0ac89661..bb4d6c31be 100644 --- ql/src/test/results/clientpositive/spark/vectorization_5.q.out +++ ql/src/test/results/clientpositive/spark/vectorization_5.q.out @@ -61,7 +61,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((cboolean2 is not null and (cstring1 like '%b%')) or ((UDFToDouble(ctinyint) = cdouble) and ctimestamp2 is not null and (cstring2 like 'a'))) (type: boolean) + filterExpr: (((cstring1 like '%b%') and cboolean2 is not null) or ((UDFToDouble(ctinyint) = cdouble) and (cstring2 like 'a') and ctimestamp2 is not null)) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -70,8 +70,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: SelectColumnIsNotNull(col 11:boolean), FilterStringColLikeStringScalar(col 6:string, pattern %b%)), FilterExprAndExpr(children: FilterDoubleColEqualDoubleColumn(col 13:double, col 5:double)(children: CastLongToDouble(col 0:tinyint) -> 13:double), SelectColumnIsNotNull(col 9:timestamp), FilterStringColLikeStringScalar(col 7:string, pattern a))) - predicate: (((UDFToDouble(ctinyint) = cdouble) and ctimestamp2 is not null and (cstring2 like 'a')) or (cboolean2 is not null and (cstring1 like '%b%'))) (type: boolean) + predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: FilterStringColLikeStringScalar(col 6:string, pattern %b%), SelectColumnIsNotNull(col 11:boolean)), FilterExprAndExpr(children: FilterDoubleColEqualDoubleColumn(col 13:double, col 5:double)(children: CastLongToDouble(col 0:tinyint) -> 13:double), FilterStringColLikeStringScalar(col 7:string, pattern a), SelectColumnIsNotNull(col 9:timestamp))) + predicate: (((UDFToDouble(ctinyint) = cdouble) and (cstring2 like 'a') and ctimestamp2 is not null) or ((cstring1 like '%b%') and cboolean2 is not null)) (type: boolean) Statistics: Num rows: 9216 Data size: 2180995 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: ctinyint (type: tinyint), csmallint (type: smallint), cint (type: int) diff --git ql/src/test/results/clientpositive/spark/vectorization_short_regress.q.out ql/src/test/results/clientpositive/spark/vectorization_short_regress.q.out index 96565305d3..e4a1746502 100644 --- ql/src/test/results/clientpositive/spark/vectorization_short_regress.q.out +++ ql/src/test/results/clientpositive/spark/vectorization_short_regress.q.out @@ -617,7 +617,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((ctimestamp1 = ctimestamp2) or (cfloat = 762.0) or (cstring1 = 'ss') or ((UDFToLong(csmallint) <= cbigint) and (cboolean2 = 1)) or (cboolean1 is not null and ctimestamp2 is not null and (cstring2 > 'a'))) (type: boolean) + filterExpr: ((ctimestamp1 = ctimestamp2) or (cfloat = 762.0) or (cstring1 = 'ss') or ((UDFToLong(csmallint) <= cbigint) and (cboolean2 = 1)) or ((cstring2 > 'a') and cboolean1 is not null and ctimestamp2 is not null)) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -625,8 +625,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterTimestampColEqualTimestampColumn(col 8:timestamp, col 9:timestamp), FilterDoubleColEqualDoubleScalar(col 4:float, val 762.0), FilterStringGroupColEqualStringScalar(col 6:string, val ss), FilterExprAndExpr(children: FilterLongColLessEqualLongColumn(col 1:bigint, col 3:bigint)(children: col 1:smallint), FilterLongColEqualLongScalar(col 11:boolean, val 1)), FilterExprAndExpr(children: SelectColumnIsNotNull(col 10:boolean), SelectColumnIsNotNull(col 9:timestamp), FilterStringGroupColGreaterStringScalar(col 7:string, val a))) - predicate: (((UDFToLong(csmallint) <= cbigint) and (cboolean2 = 1)) or (cboolean1 is not null and ctimestamp2 is not null and (cstring2 > 'a')) or (cfloat = 762.0) or (cstring1 = 'ss') or (ctimestamp1 = ctimestamp2)) (type: boolean) + predicateExpression: FilterExprOrExpr(children: FilterTimestampColEqualTimestampColumn(col 8:timestamp, col 9:timestamp), FilterDoubleColEqualDoubleScalar(col 4:float, val 762.0), FilterStringGroupColEqualStringScalar(col 6:string, val ss), FilterExprAndExpr(children: FilterLongColLessEqualLongColumn(col 1:bigint, col 3:bigint)(children: col 1:smallint), FilterLongColEqualLongScalar(col 11:boolean, val 1)), FilterExprAndExpr(children: FilterStringGroupColGreaterStringScalar(col 7:string, val a), SelectColumnIsNotNull(col 10:boolean), SelectColumnIsNotNull(col 9:timestamp))) + predicate: (((UDFToLong(csmallint) <= cbigint) and (cboolean2 = 1)) or ((cstring2 > 'a') and cboolean1 is not null and ctimestamp2 is not null) or (cfloat = 762.0) or (cstring1 = 'ss') or (ctimestamp1 = ctimestamp2)) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: cbigint (type: bigint), ctinyint (type: tinyint), csmallint (type: smallint), cint (type: int), cdouble (type: double), UDFToDouble(cbigint) (type: double), (UDFToDouble(cbigint) * UDFToDouble(cbigint)) (type: double), UDFToDouble(csmallint) (type: double), (UDFToDouble(csmallint) * UDFToDouble(csmallint)) (type: double), (cdouble * cdouble) (type: double) @@ -2202,7 +2202,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((UDFToInteger(csmallint) >= -257) and ((UDFToInteger(csmallint) = -6432) or ((UDFToDouble(cint) >= cdouble) and (UDFToInteger(ctinyint) <= cint)))) (type: boolean) + filterExpr: ((UDFToInteger(csmallint) >= -257) and (UDFToDouble(cint) >= cdouble) and (UDFToInteger(ctinyint) <= cint)) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -2210,9 +2210,9 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprAndExpr(children: FilterLongColGreaterEqualLongScalar(col 1:int, val -257)(children: col 1:smallint), FilterExprOrExpr(children: FilterLongColEqualLongScalar(col 1:int, val -6432)(children: col 1:smallint), FilterExprAndExpr(children: FilterDoubleColGreaterEqualDoubleColumn(col 13:double, col 5:double)(children: CastLongToDouble(col 2:int) -> 13:double), FilterLongColLessEqualLongColumn(col 0:int, col 2:int)(children: col 0:tinyint)))) - predicate: (((UDFToInteger(csmallint) = -6432) or ((UDFToDouble(cint) >= cdouble) and (UDFToInteger(ctinyint) <= cint))) and (UDFToInteger(csmallint) >= -257)) (type: boolean) - Statistics: Num rows: 2503 Data size: 592342 Basic stats: COMPLETE Column stats: NONE + predicateExpression: FilterExprAndExpr(children: FilterLongColGreaterEqualLongScalar(col 1:int, val -257)(children: col 1:smallint), FilterDoubleColGreaterEqualDoubleColumn(col 13:double, col 5:double)(children: CastLongToDouble(col 2:int) -> 13:double), FilterLongColLessEqualLongColumn(col 0:int, col 2:int)(children: col 0:tinyint)) + predicate: ((UDFToDouble(cint) >= cdouble) and (UDFToInteger(csmallint) >= -257) and (UDFToInteger(ctinyint) <= cint)) (type: boolean) + Statistics: Num rows: 455 Data size: 107677 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: csmallint (type: smallint), cbigint (type: bigint), ctinyint (type: tinyint), UDFToDouble(csmallint) (type: double), (UDFToDouble(csmallint) * UDFToDouble(csmallint)) (type: double), UDFToDouble(ctinyint) (type: double), (UDFToDouble(ctinyint) * UDFToDouble(ctinyint)) (type: double) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6 @@ -2221,7 +2221,7 @@ STAGE PLANS: native: true projectedOutputColumnNums: [1, 3, 0, 14, 17, 18, 21] selectExpressions: CastLongToDouble(col 1:smallint) -> 14:double, DoubleColMultiplyDoubleColumn(col 15:double, col 16:double)(children: CastLongToDouble(col 1:smallint) -> 15:double, CastLongToDouble(col 1:smallint) -> 16:double) -> 17:double, CastLongToDouble(col 0:tinyint) -> 18:double, DoubleColMultiplyDoubleColumn(col 19:double, col 20:double)(children: CastLongToDouble(col 0:tinyint) -> 19:double, CastLongToDouble(col 0:tinyint) -> 20:double) -> 21:double - Statistics: Num rows: 2503 Data size: 592342 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 455 Data size: 107677 Basic stats: COMPLETE Column stats: NONE Group By Operator aggregations: sum(_col4), sum(_col3), count(_col0), sum(_col1), sum(_col6), sum(_col5), count(_col2), count() Group By Vectorization: @@ -2235,7 +2235,7 @@ STAGE PLANS: keys: _col0 (type: smallint) mode: hash outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 2503 Data size: 592342 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 455 Data size: 107677 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: smallint) sort order: + @@ -2244,7 +2244,7 @@ STAGE PLANS: className: VectorReduceSinkLongOperator native: true nativeConditionsMet: hive.vectorized.execution.reducesink.new.enabled IS true, hive.execution.engine spark IN [tez, spark] IS true, No PTF TopN IS true, No DISTINCT columns IS true, BinarySortableSerDe for keys IS true, LazyBinarySerDe for values IS true - Statistics: Num rows: 2503 Data size: 592342 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 455 Data size: 107677 Basic stats: COMPLETE Column stats: NONE value expressions: _col1 (type: double), _col2 (type: double), _col3 (type: bigint), _col4 (type: bigint), _col5 (type: double), _col6 (type: double), _col7 (type: bigint), _col8 (type: bigint) Execution mode: vectorized Map Vectorization: @@ -2278,7 +2278,7 @@ STAGE PLANS: keys: KEY._col0 (type: smallint) mode: mergepartial outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 - Statistics: Num rows: 1251 Data size: 296052 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 227 Data size: 53720 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: smallint), (UDFToInteger(_col0) % -75) (type: int), power(((_col1 - ((_col2 * _col2) / _col3)) / CASE WHEN ((_col3 = 1L)) THEN (null) ELSE ((_col3 - 1)) END), 0.5) (type: double), (-1.389 / CAST( _col0 AS decimal(5,0))) (type: decimal(10,9)), _col4 (type: bigint), (UDFToDouble((UDFToInteger(_col0) % -75)) / UDFToDouble(_col4)) (type: double), (- (UDFToInteger(_col0) % -75)) (type: int), ((_col5 - ((_col6 * _col6) / _col7)) / _col7) (type: double), (- (- (UDFToInteger(_col0) % -75))) (type: int), _col8 (type: bigint), (_col8 - -89010L) (type: bigint) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10 @@ -2287,7 +2287,7 @@ STAGE PLANS: native: true projectedOutputColumnNums: [0, 9, 17, 19, 4, 23, 25, 29, 32, 8, 33] selectExpressions: LongColModuloLongScalar(col 0:int, val -75)(children: col 0:smallint) -> 9:int, FuncPowerDoubleToDouble(col 16:double)(children: DoubleColDivideLongColumn(col 12:double, col 15:bigint)(children: DoubleColSubtractDoubleColumn(col 1:double, col 11:double)(children: DoubleColDivideLongColumn(col 10:double, col 3:bigint)(children: DoubleColMultiplyDoubleColumn(col 2:double, col 2:double) -> 10:double) -> 11:double) -> 12:double, IfExprNullCondExpr(col 13:boolean, null, col 14:bigint)(children: LongColEqualLongScalar(col 3:bigint, val 1) -> 13:boolean, LongColSubtractLongScalar(col 3:bigint, val 1) -> 14:bigint) -> 15:bigint) -> 16:double) -> 17:double, DecimalScalarDivideDecimalColumn(val -1.389, col 18:decimal(5,0))(children: CastLongToDecimal(col 0:smallint) -> 18:decimal(5,0)) -> 19:decimal(10,9), DoubleColDivideDoubleColumn(col 21:double, col 22:double)(children: CastLongToDouble(col 20:int)(children: LongColModuloLongScalar(col 0:int, val -75)(children: col 0:smallint) -> 20:int) -> 21:double, CastLongToDouble(col 4:bigint) -> 22:double) -> 23:double, LongColUnaryMinus(col 24:int)(children: LongColModuloLongScalar(col 0:int, val -75)(children: col 0:smallint) -> 24:int) -> 25:int, DoubleColDivideLongColumn(col 28:double, col 7:bigint)(children: DoubleColSubtractDoubleColumn(col 5:double, col 27:double)(children: DoubleColDivideLongColumn(col 26:double, col 7:bigint)(children: DoubleColMultiplyDoubleColumn(col 6:double, col 6:double) -> 26:double) -> 27:double) -> 28:double) -> 29:double, LongColUnaryMinus(col 31:int)(children: LongColUnaryMinus(col 30:int)(children: LongColModuloLongScalar(col 0:int, val -75)(children: col 0:smallint) -> 30:int) -> 31:int) -> 32:int, LongColSubtractLongScalar(col 8:bigint, val -89010) -> 33:bigint - Statistics: Num rows: 1251 Data size: 296052 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 227 Data size: 53720 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: smallint), _col1 (type: int), _col2 (type: double), _col3 (type: decimal(10,9)), _col4 (type: bigint), _col5 (type: double), _col6 (type: int), _col7 (type: double), _col8 (type: int), _col9 (type: bigint), _col10 (type: bigint) sort order: +++++++++++ @@ -2295,7 +2295,7 @@ STAGE PLANS: className: VectorReduceSinkObjectHashOperator native: true nativeConditionsMet: hive.vectorized.execution.reducesink.new.enabled IS true, hive.execution.engine spark IN [tez, spark] IS true, No PTF TopN IS true, No DISTINCT columns IS true, BinarySortableSerDe for keys IS true, LazyBinarySerDe for values IS true - Statistics: Num rows: 1251 Data size: 296052 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 227 Data size: 53720 Basic stats: COMPLETE Column stats: NONE TopN Hash Memory Usage: 0.1 Reducer 3 Execution mode: vectorized @@ -2313,7 +2313,7 @@ STAGE PLANS: className: VectorSelectOperator native: true projectedOutputColumnNums: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] - Statistics: Num rows: 1251 Data size: 296052 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 227 Data size: 53720 Basic stats: COMPLETE Column stats: NONE Limit Number of rows: 20 Limit Vectorization: diff --git ql/src/test/results/clientpositive/spark/vectorized_math_funcs.q.out ql/src/test/results/clientpositive/spark/vectorized_math_funcs.q.out index 977725ca4c..d74264432d 100644 --- ql/src/test/results/clientpositive/spark/vectorized_math_funcs.q.out +++ ql/src/test/results/clientpositive/spark/vectorized_math_funcs.q.out @@ -123,7 +123,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: (((cbigint % 500) = 0) and (sin(cfloat) >= -1.0D)) (type: boolean) + filterExpr: (((cbigint % 500L) = 0) and (sin(cfloat) >= -1.0D)) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -132,7 +132,7 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: FilterExprAndExpr(children: FilterLongColEqualLongScalar(col 13:bigint, val 0)(children: LongColModuloLongScalar(col 3:bigint, val 500) -> 13:bigint), FilterDoubleColGreaterEqualDoubleScalar(col 14:double, val -1.0)(children: FuncSinDoubleToDouble(col 4:float) -> 14:double)) - predicate: (((cbigint % 500) = 0) and (sin(cfloat) >= -1.0D)) (type: boolean) + predicate: (((cbigint % 500L) = 0) and (sin(cfloat) >= -1.0D)) (type: boolean) Statistics: Num rows: 2048 Data size: 484665 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: cdouble (type: double), round(cdouble, 2) (type: double), floor(cdouble) (type: bigint), ceil(cdouble) (type: bigint), rand() (type: double), rand(98007) (type: double), exp(ln(cdouble)) (type: double), ln(cdouble) (type: double), ln(cfloat) (type: double), log10(cdouble) (type: double), log2(cdouble) (type: double), log2((cdouble - 15601.0D)) (type: double), log2(cfloat) (type: double), log2(cbigint) (type: double), log2(cint) (type: double), log2(csmallint) (type: double), log2(ctinyint) (type: double), log(2, cdouble) (type: double), power(log2(cdouble), 2) (type: double), power(log2(cdouble), 2) (type: double), sqrt(cdouble) (type: double), sqrt(cbigint) (type: double), bin(cbigint) (type: string), hex(cdouble) (type: string), conv(cbigint, 10, 16) (type: string), abs(cdouble) (type: double), abs(ctinyint) (type: int), (cint pmod 3) (type: int), sin(cdouble) (type: double), asin(cdouble) (type: double), cos(cdouble) (type: double), acos(cdouble) (type: double), atan(cdouble) (type: double), degrees(cdouble) (type: double), radians(cdouble) (type: double), cdouble (type: double), cbigint (type: bigint), (- cdouble) (type: double), sign(cdouble) (type: double), sign(cbigint) (type: double), cos(((- sin(log(cdouble))) + 3.14159D)) (type: double) diff --git ql/src/test/results/clientpositive/spark/vectorized_string_funcs.q.out ql/src/test/results/clientpositive/spark/vectorized_string_funcs.q.out index 79546c5a73..4e781071c4 100644 --- ql/src/test/results/clientpositive/spark/vectorized_string_funcs.q.out +++ ql/src/test/results/clientpositive/spark/vectorized_string_funcs.q.out @@ -63,10 +63,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: (((cbigint % 237) = 0) and (length(substr(cstring1, 1, 2)) <= 2) and (cstring1 like '%')) (type: boolean) + filterExpr: (((cbigint % 237L) = 0) and (length(substr(cstring1, 1, 2)) <= 2) and (cstring1 like '%')) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (((cbigint % 237) = 0) and (cstring1 like '%') and (length(substr(cstring1, 1, 2)) <= 2)) (type: boolean) + predicate: (((cbigint % 237L) = 0) and (cstring1 like '%') and (length(substr(cstring1, 1, 2)) <= 2)) (type: boolean) Statistics: Num rows: 1024 Data size: 242332 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: substr(cstring1, 1, 2) (type: string), substr(cstring1, 2) (type: string), lower(cstring1) (type: string), upper(cstring1) (type: string), upper(cstring1) (type: string), length(cstring1) (type: int), trim(cstring1) (type: string), ltrim(cstring1) (type: string), rtrim(cstring1) (type: string), concat(cstring1, cstring2) (type: string), concat('>', cstring1) (type: string), concat(cstring1, '<') (type: string), concat(substr(cstring1, 1, 2), substr(cstring2, 1, 2)) (type: string) diff --git ql/src/test/results/clientpositive/subquery_notin_having.q.out ql/src/test/results/clientpositive/subquery_notin_having.q.out index 30580ab549..9fb20f9ea0 100644 --- ql/src/test/results/clientpositive/subquery_notin_having.q.out +++ ql/src/test/results/clientpositive/subquery_notin_having.q.out @@ -127,15 +127,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col5 Statistics: Num rows: 275 Data size: 7596 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col2 = 0L) or (_col5 is null and _col0 is not null and (_col3 >= _col2))) (type: boolean) - Statistics: Num rows: 182 Data size: 5027 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col0 is null) and (_col0 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) + Statistics: Num rows: 274 Data size: 7568 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: bigint) outputColumnNames: _col0, _col1 - Statistics: Num rows: 182 Data size: 5027 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 274 Data size: 7568 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 182 Data size: 5027 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 274 Data size: 7568 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -349,15 +349,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col3, _col4, _col7 Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col3 = 0L)) THEN (true) WHEN (_col3 is null) THEN (true) WHEN (_col7 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col4 < _col3)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 7 Data size: 888 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col4 < _col3) is not true or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null or _col0 is null) and (_col0 is not null or ((_col3 = 0L) or _col3 is null) is true or _col7 is not null) and (_col7 is null or ((_col3 = 0L) or _col3 is null) is true)) (type: boolean) + Statistics: Num rows: 14 Data size: 1776 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: double) outputColumnNames: _col0, _col1 - Statistics: Num rows: 7 Data size: 888 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 14 Data size: 1776 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 7 Data size: 888 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 14 Data size: 1776 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -646,15 +646,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col5 Statistics: Num rows: 14 Data size: 2080 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col2 = 0L) or (_col5 is null and _col0 is not null and (_col3 >= _col2))) (type: boolean) - Statistics: Num rows: 9 Data size: 1337 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col0 is null) and (_col0 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) + Statistics: Num rows: 14 Data size: 2080 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: double) outputColumnNames: _col0, _col1 - Statistics: Num rows: 9 Data size: 1337 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 14 Data size: 2080 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 9 Data size: 1337 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 14 Data size: 2080 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -956,15 +956,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col4 Statistics: Num rows: 2 Data size: 205 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col1 = 0L) or (_col4 is null and _col0 is not null and (_col2 >= _col1))) (type: boolean) - Statistics: Num rows: 1 Data size: 102 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col2 >= _col1) or (_col1 = 0L) or _col4 is not null or _col0 is null) and (_col0 is not null or (_col1 = 0L) or _col4 is not null) and (_col4 is null or (_col1 = 0L))) (type: boolean) + Statistics: Num rows: 2 Data size: 205 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int) outputColumnNames: _col0 - Statistics: Num rows: 1 Data size: 102 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 205 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 1 Data size: 102 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 2 Data size: 205 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -1147,15 +1147,15 @@ STAGE PLANS: outputColumnNames: _col0, _col2, _col3, _col5 Statistics: Num rows: 4 Data size: 343 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col2 = 0L)) THEN (true) WHEN (_col2 is null) THEN (true) WHEN (_col5 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col3 < _col2)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 2 Data size: 171 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col3 < _col2) is not true or ((_col2 = 0L) or _col2 is null) is true or _col5 is not null or _col0 is null) and (_col0 is not null or ((_col2 = 0L) or _col2 is null) is true or _col5 is not null) and (_col5 is null or ((_col2 = 0L) or _col2 is null) is true)) (type: boolean) + Statistics: Num rows: 4 Data size: 343 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: int) outputColumnNames: _col0 - Statistics: Num rows: 2 Data size: 171 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 4 Data size: 343 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 2 Data size: 171 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 4 Data size: 343 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat diff --git ql/src/test/results/clientpositive/subquery_unqualcolumnrefs.q.out ql/src/test/results/clientpositive/subquery_unqualcolumnrefs.q.out index 7cbbaa7b01..0312c2decc 100644 --- ql/src/test/results/clientpositive/subquery_unqualcolumnrefs.q.out +++ ql/src/test/results/clientpositive/subquery_unqualcolumnrefs.q.out @@ -465,15 +465,15 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col4, _col5, _col8 Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: CASE WHEN ((_col4 = 0L)) THEN (true) WHEN (_col4 is null) THEN (true) WHEN (_col8 is not null) THEN (false) WHEN (_col0 is null) THEN (null) WHEN ((_col5 < _col4)) THEN (false) ELSE (true) END (type: boolean) - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col5 < _col4) is not true or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null or _col0 is null) and (_col0 is not null or ((_col4 = 0L) or _col4 is null) is true or _col8 is not null) and (_col8 is null or ((_col4 = 0L) or _col4 is null) is true)) (type: boolean) + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col1 (type: string), _col0 (type: string), _col2 (type: int) outputColumnNames: _col0, _col1, _col2 - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 15 Data size: 1903 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 30 Data size: 3807 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat diff --git ql/src/test/results/clientpositive/timestamp_ints_casts.q.out ql/src/test/results/clientpositive/timestamp_ints_casts.q.out index 3997377966..ee65623a43 100644 --- ql/src/test/results/clientpositive/timestamp_ints_casts.q.out +++ ql/src/test/results/clientpositive/timestamp_ints_casts.q.out @@ -48,10 +48,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((cbigint % 250) = 0) (type: boolean) + filterExpr: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((cbigint % 250) = 0) (type: boolean) + predicate: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 6144 Data size: 1453997 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: CAST( ctinyint AS TIMESTAMP) (type: timestamp), CAST( csmallint AS TIMESTAMP) (type: timestamp), CAST( cint AS TIMESTAMP) (type: timestamp), CAST( cbigint AS TIMESTAMP) (type: timestamp), CAST( cfloat AS TIMESTAMP) (type: timestamp), CAST( cdouble AS TIMESTAMP) (type: timestamp), CAST( cboolean1 AS TIMESTAMP) (type: timestamp), CAST( (cbigint * 0L) AS TIMESTAMP) (type: timestamp), ctimestamp1 (type: timestamp), CAST( cstring1 AS TIMESTAMP) (type: timestamp), CAST( substr(cstring1, 1, 1) AS TIMESTAMP) (type: timestamp) @@ -186,10 +186,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((cbigint % 250) = 0) (type: boolean) + filterExpr: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((cbigint % 250) = 0) (type: boolean) + predicate: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 6144 Data size: 1453997 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: CAST( ctinyint AS TIMESTAMP) (type: timestamp), CAST( csmallint AS TIMESTAMP) (type: timestamp), CAST( cint AS TIMESTAMP) (type: timestamp), CAST( cbigint AS TIMESTAMP) (type: timestamp), CAST( cfloat AS TIMESTAMP) (type: timestamp), CAST( cdouble AS TIMESTAMP) (type: timestamp), CAST( cboolean1 AS TIMESTAMP) (type: timestamp), CAST( (cbigint * 0L) AS TIMESTAMP) (type: timestamp), ctimestamp1 (type: timestamp), CAST( cstring1 AS TIMESTAMP) (type: timestamp), CAST( substr(cstring1, 1, 1) AS TIMESTAMP) (type: timestamp) diff --git ql/src/test/results/clientpositive/truncate_column_list_bucket.q.out ql/src/test/results/clientpositive/truncate_column_list_bucket.q.out index 5f01999500..6418e1d3b1 100644 --- ql/src/test/results/clientpositive/truncate_column_list_bucket.q.out +++ ql/src/test/results/clientpositive/truncate_column_list_bucket.q.out @@ -59,7 +59,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@test_tab_n3 POSTHOOK: Input: default@test_tab_n3@part=1 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('484' AS STRING) AS `key`, `value`, CAST('1' AS STRING) AS `part` +OPTIMIZED SQL: SELECT CAST('484' AS VARCHAR(65536)) AS `key`, `value`, CAST('1' AS VARCHAR(65536)) AS `part` FROM `default`.`test_tab_n3` WHERE `part` = '1' AND `key` = '484' STAGE DEPENDENCIES: @@ -186,7 +186,7 @@ POSTHOOK: type: QUERY POSTHOOK: Input: default@test_tab_n3 POSTHOOK: Input: default@test_tab_n3@part=1 #### A masked pattern was here #### -OPTIMIZED SQL: SELECT CAST('0' AS STRING) AS `key`, `value`, CAST('1' AS STRING) AS `part` +OPTIMIZED SQL: SELECT CAST('0' AS VARCHAR(65536)) AS `key`, `value`, CAST('1' AS VARCHAR(65536)) AS `part` FROM `default`.`test_tab_n3` WHERE `part` = '1' AND `key` = '0' STAGE DEPENDENCIES: diff --git ql/src/test/results/clientpositive/udf_isops_simplify.q.out ql/src/test/results/clientpositive/udf_isops_simplify.q.out index 96a07181c1..6d2566902e 100644 --- ql/src/test/results/clientpositive/udf_isops_simplify.q.out +++ ql/src/test/results/clientpositive/udf_isops_simplify.q.out @@ -163,7 +163,7 @@ STAGE PLANS: outputColumnNames: _col0 Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Select Operator - expressions: (not _col0 is not null) (type: boolean) + expressions: _col0 is null (type: boolean) outputColumnNames: _col0 Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE File Output Operator diff --git ql/src/test/results/clientpositive/union22.q.out ql/src/test/results/clientpositive/union22.q.out index 3862eb8cb2..0a5c3a36a2 100644 --- ql/src/test/results/clientpositive/union22.q.out +++ ql/src/test/results/clientpositive/union22.q.out @@ -80,6 +80,17 @@ POSTHOOK: Input: default@dst_union22@ds=1 POSTHOOK: Input: default@dst_union22_delta POSTHOOK: Input: default@dst_union22_delta@ds=1 POSTHOOK: Output: default@dst_union22@ds=2 +OPTIMIZED SQL: SELECT `k1`, `k2`, `k3`, `k4` +FROM `default`.`dst_union22_delta` +WHERE `ds` = '1' AND `k0` <= 50 +UNION ALL +SELECT `t2`.`k1`, `t2`.`k2`, `t4`.`k3`, `t4`.`k4` +FROM (SELECT `k1`, `k2`, `ds` = '1' AS `=` +FROM `default`.`dst_union22` +WHERE `k1` > 20) AS `t2` +LEFT JOIN (SELECT `k1`, `k3`, `k4` +FROM `default`.`dst_union22_delta` +WHERE `ds` = '1' AND `k0` > 50 AND `k1` > 20) AS `t4` ON `t2`.`k1` = `t4`.`k1` AND `t2`.`=` STAGE DEPENDENCIES: Stage-7 is a root stage , consists of Stage-8, Stage-4 Stage-8 has a backup stage: Stage-4 diff --git ql/src/test/results/clientpositive/union_offcbo.q.out ql/src/test/results/clientpositive/union_offcbo.q.out index 61413983de..31cddc1a07 100644 --- ql/src/test/results/clientpositive/union_offcbo.q.out +++ ql/src/test/results/clientpositive/union_offcbo.q.out @@ -644,10 +644,10 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Filter Operator - predicate: (((COALESCE(_col0,-1) <> COALESCE(_col7,-1)) or (COALESCE(_col1,-1) <> COALESCE(_col8,-1))) and CASE WHEN ((_col0 is null and (_col3 >= '2016-02-05'))) THEN (true) WHEN ((_col0 is null and (_col3 <= '2016-02-05'))) THEN (false) WHEN (((_col7 = _col0) and (_col8 <> _col1))) THEN (true) ELSE (true) END) (type: boolean) + predicate: (((COALESCE(_col0,-1) <> COALESCE(_col7,-1)) or (COALESCE(_col1,-1) <> COALESCE(_col8,-1))) and (CASE WHEN ((_col0 is null and (_col3 >= '2016-02-05') and _col7 is not null)) THEN ('DEL') WHEN ((_col0 is null and (_col3 <= '2016-02-05') and _col7 is not null)) THEN ('RET') WHEN (((_col7 = _col0) and (_col8 <> _col1))) THEN ('A_INS') ELSE ('NA') END <> 'RET')) (type: boolean) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Select Operator - expressions: _col2 (type: bigint), _col5 (type: string), _col6 (type: bigint), _col4 (type: string), _col7 (type: string), _col8 (type: string), CASE WHEN ((_col0 is null and (_col3 >= '2016-02-05'))) THEN ('DEL') WHEN ((_col0 is null and (_col3 <= '2016-02-05'))) THEN ('RET') WHEN (((_col7 = _col0) and (_col8 <> _col1))) THEN ('A_INS') ELSE ('NA') END (type: string) + expressions: _col2 (type: bigint), _col5 (type: string), _col6 (type: bigint), _col4 (type: string), _col7 (type: string), _col8 (type: string), CASE WHEN ((_col0 is null and (_col3 >= '2016-02-05') and _col7 is not null)) THEN ('DEL') WHEN ((_col0 is null and (_col3 <= '2016-02-05') and _col7 is not null)) THEN ('RET') WHEN (((_col7 = _col0) and (_col8 <> _col1))) THEN ('A_INS') ELSE ('NA') END (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6 Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE File Output Operator @@ -720,29 +720,29 @@ STAGE PLANS: predicate: ('2015-11-20' BETWEEN dt1 AND dt2 and khash is not null) (type: boolean) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Select Operator - expressions: khash (type: string), rhash (type: string) - outputColumnNames: _col0, _col1 + expressions: ts1 (type: string), khash (type: string), rhash (type: string) + outputColumnNames: _col0, _col1, _col2 Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Reduce Output Operator - key expressions: _col0 (type: string) + key expressions: _col1 (type: string) sort order: + - Map-reduce partition columns: _col0 (type: string) + Map-reduce partition columns: _col1 (type: string) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE - value expressions: _col1 (type: string) + value expressions: _col0 (type: string), _col2 (type: string) Reduce Operator Tree: Join Operator condition map: Left Outer Join 0 to 1 keys: 0 _col3 (type: string) - 1 _col0 (type: string) - outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6 + 1 _col1 (type: string) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7 Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Filter Operator - predicate: ((COALESCE(_col3,-1) <> COALESCE(_col5,-1)) or (COALESCE(_col4,-1) <> COALESCE(_col6,-1))) (type: boolean) + predicate: (((COALESCE(_col3,-1) <> COALESCE(_col6,-1)) or (COALESCE(_col4,-1) <> COALESCE(_col7,-1))) and (CASE WHEN ((_col3 is null and (_col5 <= '2015-11-20') and _col6 is not null)) THEN ('DEL') WHEN (((_col6 is null and _col3 is not null) or ((_col6 = _col3) and (_col7 <> _col4)))) THEN ('INS') ELSE ('NA') END <> 'RET')) (type: boolean) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Select Operator - expressions: _col0 (type: bigint), _col1 (type: string), _col2 (type: bigint), '2099-12-31' (type: string), _col3 (type: string), _col4 (type: string), CASE WHEN ((_col5 is null or ((_col5 = _col3) and (_col6 <> _col4)))) THEN ('INS') ELSE ('NA') END (type: string) + expressions: _col0 (type: bigint), _col1 (type: string), _col2 (type: bigint), '2099-12-31' (type: string), _col3 (type: string), _col4 (type: string), CASE WHEN ((_col3 is null and (_col5 <= '2015-11-20') and _col6 is not null)) THEN ('DEL') WHEN (((_col6 is null and _col3 is not null) or ((_col6 = _col3) and (_col7 <> _col4)))) THEN ('INS') ELSE ('NA') END (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6 Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE File Output Operator @@ -1713,10 +1713,10 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8 Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Filter Operator - predicate: (((COALESCE(_col0,-1) <> COALESCE(_col7,-1)) or (COALESCE(_col1,-1) <> COALESCE(_col8,-1))) and CASE WHEN ((_col0 is null and (_col3 >= '2016-02-05'))) THEN (true) WHEN ((_col0 is null and (_col3 <= '2016-02-05'))) THEN (false) WHEN (((_col7 = _col0) and (_col8 <> _col1))) THEN (true) ELSE (true) END) (type: boolean) + predicate: (((COALESCE(_col0,-1) <> COALESCE(_col7,-1)) or (COALESCE(_col1,-1) <> COALESCE(_col8,-1))) and (CASE WHEN ((_col0 is null and (_col3 >= '2016-02-05') and _col7 is not null)) THEN ('DEL') WHEN ((_col0 is null and (_col3 <= '2016-02-05') and _col7 is not null)) THEN ('RET') WHEN (((_col7 = _col0) and (_col8 <> _col1))) THEN ('A_INS') ELSE ('NA') END <> 'RET')) (type: boolean) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Select Operator - expressions: _col2 (type: bigint), _col5 (type: string), _col6 (type: bigint), _col4 (type: string), _col7 (type: string), _col8 (type: string), CASE WHEN ((_col0 is null and (_col3 >= '2016-02-05'))) THEN ('DEL') WHEN ((_col0 is null and (_col3 <= '2016-02-05'))) THEN ('RET') WHEN (((_col7 = _col0) and (_col8 <> _col1))) THEN ('A_INS') ELSE ('NA') END (type: string) + expressions: _col2 (type: bigint), _col5 (type: string), _col6 (type: bigint), _col4 (type: string), _col7 (type: string), _col8 (type: string), CASE WHEN ((_col0 is null and (_col3 >= '2016-02-05') and _col7 is not null)) THEN ('DEL') WHEN ((_col0 is null and (_col3 <= '2016-02-05') and _col7 is not null)) THEN ('RET') WHEN (((_col7 = _col0) and (_col8 <> _col1))) THEN ('A_INS') ELSE ('NA') END (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6 Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE File Output Operator @@ -1787,29 +1787,29 @@ STAGE PLANS: predicate: ('2015-11-20' BETWEEN dt1 AND dt2 and khash is not null) (type: boolean) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Select Operator - expressions: khash (type: string), rhash (type: string) - outputColumnNames: _col0, _col1 + expressions: ts1 (type: string), khash (type: string), rhash (type: string) + outputColumnNames: _col0, _col1, _col2 Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Reduce Output Operator - key expressions: _col0 (type: string) + key expressions: _col1 (type: string) sort order: + - Map-reduce partition columns: _col0 (type: string) + Map-reduce partition columns: _col1 (type: string) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE - value expressions: _col1 (type: string) + value expressions: _col0 (type: string), _col2 (type: string) Reduce Operator Tree: Join Operator condition map: Left Outer Join 0 to 1 keys: 0 _col3 (type: string) - 1 _col0 (type: string) - outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6 + 1 _col1 (type: string) + outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7 Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Filter Operator - predicate: ((COALESCE(_col3,-1) <> COALESCE(_col5,-1)) or (COALESCE(_col4,-1) <> COALESCE(_col6,-1))) (type: boolean) + predicate: (((COALESCE(_col3,-1) <> COALESCE(_col6,-1)) or (COALESCE(_col4,-1) <> COALESCE(_col7,-1))) and (CASE WHEN ((_col3 is null and (_col5 <= '2015-11-20') and _col6 is not null)) THEN ('DEL') WHEN (((_col6 is null and _col3 is not null) or ((_col6 = _col3) and (_col7 <> _col4)))) THEN ('INS') ELSE ('NA') END <> 'RET')) (type: boolean) Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE Select Operator - expressions: _col0 (type: bigint), _col1 (type: string), _col2 (type: bigint), '2099-12-31' (type: string), _col3 (type: string), _col4 (type: string), CASE WHEN ((_col5 is null or ((_col5 = _col3) and (_col6 <> _col4)))) THEN ('INS') ELSE ('NA') END (type: string) + expressions: _col0 (type: bigint), _col1 (type: string), _col2 (type: bigint), '2099-12-31' (type: string), _col3 (type: string), _col4 (type: string), CASE WHEN ((_col3 is null and (_col5 <= '2015-11-20') and _col6 is not null)) THEN ('DEL') WHEN (((_col6 is null and _col3 is not null) or ((_col6 = _col3) and (_col7 <> _col4)))) THEN ('INS') ELSE ('NA') END (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6 Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE File Output Operator diff --git ql/src/test/results/clientpositive/vector_case_when_1.q.out ql/src/test/results/clientpositive/vector_case_when_1.q.out index 87f28afcde..c30a136a39 100644 --- ql/src/test/results/clientpositive/vector_case_when_1.q.out +++ ql/src/test/results/clientpositive/vector_case_when_1.q.out @@ -206,13 +206,13 @@ STAGE PLANS: native: true vectorizationSchemaColumns: [0:l_orderkey:int, 1:l_partkey:int, 2:l_suppkey:int, 3:l_linenumber:int, 4:l_quantity:int, 5:l_extendedprice:double, 6:l_discount:double, 7:l_tax:decimal(10,2)/DECIMAL_64, 8:l_returnflag:char(1), 9:l_linestatus:char(1), 10:l_shipdate:date, 11:l_commitdate:date, 12:l_receiptdate:date, 13:l_shipinstruct:varchar(20), 14:l_shipmode:char(10), 15:l_comment:string, 16:ROW__ID:struct] Select Operator - expressions: l_quantity (type: int), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN (null) ELSE (null) END (type: string), if((l_shipmode = 'SHIP '), date_add(l_shipdate, 10), date_add(l_shipdate, 5)) (type: date), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END (type: double), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END (type: double), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(10,2)), if((l_partkey > 30), CAST( l_receiptdate AS TIMESTAMP), CAST( l_commitdate AS TIMESTAMP)) (type: timestamp), if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null) (type: int), if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)) (type: int), if(((l_suppkey % 500) > 100), DATE'2009-01-01', DATE'2009-12-31') (type: date) + expressions: l_quantity (type: int), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') ELSE (null) END (type: string), if((l_shipmode = 'SHIP '), date_add(l_shipdate, 10), date_add(l_shipdate, 5)) (type: date), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END (type: double), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END (type: double), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(10,2)), if((l_partkey > 30), CAST( l_receiptdate AS TIMESTAMP), CAST( l_commitdate AS TIMESTAMP)) (type: timestamp), if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null) (type: int), if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)) (type: int), if(((l_suppkey % 500) > 100), DATE'2009-01-01', DATE'2009-12-31') (type: date) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16 Select Vectorization: className: VectorSelectOperator native: true - projectedOutputColumnNums: [4, 21, 26, 31, 35, 39, 43, 45, 47, 49, 51, 53, 55, 59, 62, 65, 68] - selectExpressions: VectorUDFAdaptor(CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END)(children: LongColEqualLongScalar(col 4:int, val 1) -> 17:boolean, LongColEqualLongScalar(col 4:int, val 2) -> 18:boolean, LongColLessLongScalar(col 4:int, val 10) -> 19:boolean, LongColLessLongScalar(col 4:int, val 100) -> 20:boolean) -> 21:string, VectorUDFAdaptor(CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END)(children: LongColEqualLongScalar(col 4:int, val 1) -> 22:boolean, LongColEqualLongScalar(col 4:int, val 2) -> 23:boolean, LongColLessLongScalar(col 4:int, val 10) -> 24:boolean, LongColLessLongScalar(col 4:int, val 100) -> 25:boolean) -> 26:string, VectorUDFAdaptor(CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN (null) ELSE (null) END)(children: LongColEqualLongScalar(col 4:int, val 1) -> 27:boolean, LongColEqualLongScalar(col 4:int, val 2) -> 28:boolean, LongColLessLongScalar(col 4:int, val 10) -> 29:boolean, LongColLessLongScalar(col 4:int, val 100) -> 30:boolean) -> 31:string, IfExprLongColumnLongColumn(col 32:boolean, col 33:date, col 34:date)(children: StringGroupColEqualCharScalar(col 14:char(10), val SHIP) -> 32:boolean, VectorUDFDateAddColScalar(col 10:date, val 10) -> 33:date, VectorUDFDateAddColScalar(col 10:date, val 5) -> 34:date) -> 35:date, VectorUDFAdaptor(CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 36:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 37:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 37:double) -> 38:double) -> 39:double, VectorUDFAdaptor(CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 40:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 41:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 41:double) -> 42:double) -> 43:double, VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 44:boolean) -> 45:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 46:boolean) -> 47:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 48:boolean) -> 49:decimal(12,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 50:boolean) -> 51:decimal(12,2), IfExprDecimal64ScalarDecimal64Column(col 52:boolean, decimal64Val 0, decimalVal 0, col 7:decimal(10,2)/DECIMAL_64)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 52:boolean) -> 53:decimal(10,2)/DECIMAL_64, IfExprDecimal64ColumnDecimal64Scalar(col 54:boolean, col 7:decimal(10,2)/DECIMAL_64, decimal64Val 0, decimalVal 0)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 54:boolean) -> 55:decimal(10,2)/DECIMAL_64, IfExprTimestampColumnColumn(col 56:boolean, col 57:timestampcol 58:timestamp)(children: LongColGreaterLongScalar(col 1:int, val 30) -> 56:boolean, CastDateToTimestamp(col 12:date) -> 57:timestamp, CastDateToTimestamp(col 11:date) -> 58:timestamp) -> 59:timestamp, VectorUDFAdaptor(if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null))(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 60:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 61:int) -> 62:int, VectorUDFAdaptor(if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)))(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 63:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 64:int) -> 65:int, IfExprLongScalarLongScalar(col 67:boolean, val 14245, val 14609)(children: LongColGreaterLongScalar(col 66:int, val 100)(children: LongColModuloLongScalar(col 2:int, val 500) -> 66:int) -> 67:boolean) -> 68:date + projectedOutputColumnNums: [4, 21, 26, 30, 34, 38, 42, 44, 46, 48, 50, 52, 54, 58, 61, 64, 67] + selectExpressions: VectorUDFAdaptor(CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END)(children: LongColEqualLongScalar(col 4:int, val 1) -> 17:boolean, LongColEqualLongScalar(col 4:int, val 2) -> 18:boolean, LongColLessLongScalar(col 4:int, val 10) -> 19:boolean, LongColLessLongScalar(col 4:int, val 100) -> 20:boolean) -> 21:string, VectorUDFAdaptor(CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END)(children: LongColEqualLongScalar(col 4:int, val 1) -> 22:boolean, LongColEqualLongScalar(col 4:int, val 2) -> 23:boolean, LongColLessLongScalar(col 4:int, val 10) -> 24:boolean, LongColLessLongScalar(col 4:int, val 100) -> 25:boolean) -> 26:string, VectorUDFAdaptor(CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') ELSE (null) END)(children: LongColEqualLongScalar(col 4:int, val 1) -> 27:boolean, LongColEqualLongScalar(col 4:int, val 2) -> 28:boolean, LongColLessLongScalar(col 4:int, val 10) -> 29:boolean) -> 30:string, IfExprLongColumnLongColumn(col 31:boolean, col 32:date, col 33:date)(children: StringGroupColEqualCharScalar(col 14:char(10), val SHIP) -> 31:boolean, VectorUDFDateAddColScalar(col 10:date, val 10) -> 32:date, VectorUDFDateAddColScalar(col 10:date, val 5) -> 33:date) -> 34:date, VectorUDFAdaptor(CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 35:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 36:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 36:double) -> 37:double) -> 38:double, VectorUDFAdaptor(CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 39:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 40:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 40:double) -> 41:double) -> 42:double, VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 43:boolean) -> 44:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 45:boolean) -> 46:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 47:boolean) -> 48:decimal(12,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 49:boolean) -> 50:decimal(12,2), IfExprDecimal64ScalarDecimal64Column(col 51:boolean, decimal64Val 0, decimalVal 0, col 7:decimal(10,2)/DECIMAL_64)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 51:boolean) -> 52:decimal(10,2)/DECIMAL_64, IfExprDecimal64ColumnDecimal64Scalar(col 53:boolean, col 7:decimal(10,2)/DECIMAL_64, decimal64Val 0, decimalVal 0)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 53:boolean) -> 54:decimal(10,2)/DECIMAL_64, IfExprTimestampColumnColumn(col 55:boolean, col 56:timestampcol 57:timestamp)(children: LongColGreaterLongScalar(col 1:int, val 30) -> 55:boolean, CastDateToTimestamp(col 12:date) -> 56:timestamp, CastDateToTimestamp(col 11:date) -> 57:timestamp) -> 58:timestamp, VectorUDFAdaptor(if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null))(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 59:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 60:int) -> 61:int, VectorUDFAdaptor(if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)))(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 62:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 63:int) -> 64:int, IfExprLongScalarLongScalar(col 66:boolean, val 14245, val 14609)(children: LongColGreaterLongScalar(col 65:int, val 100)(children: LongColModuloLongScalar(col 2:int, val 500) -> 65:int) -> 66:boolean) -> 67:date Statistics: Num rows: 101 Data size: 78500 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false @@ -239,7 +239,7 @@ STAGE PLANS: includeColumns: [1, 2, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14] dataColumns: l_orderkey:int, l_partkey:int, l_suppkey:int, l_linenumber:int, l_quantity:int, l_extendedprice:double, l_discount:double, l_tax:decimal(10,2)/DECIMAL_64, l_returnflag:char(1), l_linestatus:char(1), l_shipdate:date, l_commitdate:date, l_receiptdate:date, l_shipinstruct:varchar(20), l_shipmode:char(10), l_comment:string partitionColumnCount: 0 - scratchColumnTypeNames: [bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, double, double, double, bigint, double, double, double, bigint, decimal(10,2), bigint, decimal(10,2), bigint, decimal(12,2), bigint, decimal(12,2), bigint, decimal(10,2)/DECIMAL_64, bigint, decimal(10,2)/DECIMAL_64, bigint, timestamp, timestamp, timestamp, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint] + scratchColumnTypeNames: [bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, double, double, double, bigint, double, double, double, bigint, decimal(10,2), bigint, decimal(10,2), bigint, decimal(12,2), bigint, decimal(12,2), bigint, decimal(10,2)/DECIMAL_64, bigint, decimal(10,2)/DECIMAL_64, bigint, timestamp, timestamp, timestamp, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint] Stage: Stage-0 Fetch Operator @@ -539,13 +539,13 @@ STAGE PLANS: native: true vectorizationSchemaColumns: [0:l_orderkey:int, 1:l_partkey:int, 2:l_suppkey:int, 3:l_linenumber:int, 4:l_quantity:int, 5:l_extendedprice:double, 6:l_discount:double, 7:l_tax:decimal(10,2)/DECIMAL_64, 8:l_returnflag:char(1), 9:l_linestatus:char(1), 10:l_shipdate:date, 11:l_commitdate:date, 12:l_receiptdate:date, 13:l_shipinstruct:varchar(20), 14:l_shipmode:char(10), 15:l_comment:string, 16:ROW__ID:struct] Select Operator - expressions: l_quantity (type: int), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN (null) ELSE (null) END (type: string), if((l_shipmode = 'SHIP '), date_add(l_shipdate, 10), date_add(l_shipdate, 5)) (type: date), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END (type: double), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END (type: double), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(10,2)), if((l_partkey > 30), CAST( l_receiptdate AS TIMESTAMP), CAST( l_commitdate AS TIMESTAMP)) (type: timestamp), if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null) (type: int), if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)) (type: int), if(((l_suppkey % 500) > 100), DATE'2009-01-01', DATE'2009-12-31') (type: date) + expressions: l_quantity (type: int), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') ELSE (null) END (type: string), if((l_shipmode = 'SHIP '), date_add(l_shipdate, 10), date_add(l_shipdate, 5)) (type: date), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END (type: double), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END (type: double), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(10,2)), if((l_partkey > 30), CAST( l_receiptdate AS TIMESTAMP), CAST( l_commitdate AS TIMESTAMP)) (type: timestamp), if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null) (type: int), if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)) (type: int), if(((l_suppkey % 500) > 100), DATE'2009-01-01', DATE'2009-12-31') (type: date) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16 Select Vectorization: className: VectorSelectOperator native: true projectedOutputColumnNums: [4, 24, 33, 40, 44, 49, 53, 55, 57, 59, 61, 63, 65, 69, 72, 75, 78] - selectExpressions: IfExprStringScalarStringGroupColumn(col 17:boolean, val Singlecol 23:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 17:boolean, IfExprStringScalarStringGroupColumn(col 18:boolean, val Twocol 22:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 18:boolean, IfExprStringScalarStringGroupColumn(col 19:boolean, val Somecol 21:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 19:boolean, IfExprStringScalarStringScalar(col 20:boolean, val Many, val Huge number)(children: LongColLessLongScalar(col 4:int, val 100) -> 20:boolean) -> 21:string) -> 22:string) -> 23:string) -> 24:string, IfExprStringScalarStringGroupColumn(col 25:boolean, val Singlecol 32:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 25:boolean, IfExprStringScalarStringGroupColumn(col 26:boolean, val Twocol 31:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 26:boolean, IfExprStringScalarStringGroupColumn(col 27:boolean, val Somecol 30:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 27:boolean, IfExprColumnNull(col 28:boolean, col 29:string, null)(children: LongColLessLongScalar(col 4:int, val 100) -> 28:boolean, ConstantVectorExpression(val Many) -> 29:string) -> 30:string) -> 31:string) -> 32:string) -> 33:string, IfExprStringScalarStringGroupColumn(col 34:boolean, val Singlecol 39:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 34:boolean, IfExprStringScalarStringGroupColumn(col 35:boolean, val Twocol 38:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 35:boolean, IfExprStringScalarStringGroupColumn(col 36:boolean, val Somecol 37:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 36:boolean, IfExprNullNull(null, null) -> 37:string) -> 38:string) -> 39:string) -> 40:string, IfExprLongColumnLongColumn(col 41:boolean, col 42:date, col 43:date)(children: StringGroupColEqualCharScalar(col 14:char(10), val SHIP) -> 41:boolean, VectorUDFDateAddColScalar(col 10:date, val 10) -> 42:date, VectorUDFDateAddColScalar(col 10:date, val 5) -> 43:date) -> 44:date, IfExprDoubleColumnDoubleColumn(col 45:boolean, col 47:doublecol 48:double)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 45:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 46:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 46:double) -> 47:double, ConstantVectorExpression(val 0.0) -> 48:double) -> 49:double, IfExprDoubleColumnDoubleScalar(col 50:boolean, col 52:double, val 0.0)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 50:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 51:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 51:double) -> 52:double) -> 53:double, IfExprNullColumn(col 54:boolean, null, col 79)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 54:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 79:decimal(10,2)) -> 55:decimal(10,2), IfExprColumnNull(col 56:boolean, col 80:decimal(10,2), null)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 56:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 80:decimal(10,2)) -> 57:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 58:boolean) -> 59:decimal(12,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 60:boolean) -> 61:decimal(12,2), IfExprDecimal64ScalarDecimal64Column(col 62:boolean, decimal64Val 0, decimalVal 0, col 7:decimal(10,2)/DECIMAL_64)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 62:boolean) -> 63:decimal(10,2)/DECIMAL_64, IfExprDecimal64ColumnDecimal64Scalar(col 64:boolean, col 7:decimal(10,2)/DECIMAL_64, decimal64Val 0, decimalVal 0)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 64:boolean) -> 65:decimal(10,2)/DECIMAL_64, IfExprTimestampColumnColumn(col 66:boolean, col 67:timestampcol 68:timestamp)(children: LongColGreaterLongScalar(col 1:int, val 30) -> 66:boolean, CastDateToTimestamp(col 12:date) -> 67:timestamp, CastDateToTimestamp(col 11:date) -> 68:timestamp) -> 69:timestamp, IfExprColumnNull(col 70:boolean, col 71:int, null)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 70:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 71:int) -> 72:int, IfExprNullColumn(col 73:boolean, null, col 74)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 73:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 74:int) -> 75:int, IfExprLongScalarLongScalar(col 77:boolean, val 14245, val 14609)(children: LongColGreaterLongScalar(col 76:int, val 100)(children: LongColModuloLongScalar(col 2:int, val 500) -> 76:int) -> 77:boolean) -> 78:date + selectExpressions: IfExprStringScalarStringGroupColumn(col 17:boolean, val Singlecol 23:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 17:boolean, IfExprStringScalarStringGroupColumn(col 18:boolean, val Twocol 22:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 18:boolean, IfExprStringScalarStringGroupColumn(col 19:boolean, val Somecol 21:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 19:boolean, IfExprStringScalarStringScalar(col 20:boolean, val Many, val Huge number)(children: LongColLessLongScalar(col 4:int, val 100) -> 20:boolean) -> 21:string) -> 22:string) -> 23:string) -> 24:string, IfExprStringScalarStringGroupColumn(col 25:boolean, val Singlecol 32:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 25:boolean, IfExprStringScalarStringGroupColumn(col 26:boolean, val Twocol 31:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 26:boolean, IfExprStringScalarStringGroupColumn(col 27:boolean, val Somecol 30:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 27:boolean, IfExprColumnNull(col 28:boolean, col 29:string, null)(children: LongColLessLongScalar(col 4:int, val 100) -> 28:boolean, ConstantVectorExpression(val Many) -> 29:string) -> 30:string) -> 31:string) -> 32:string) -> 33:string, IfExprStringScalarStringGroupColumn(col 34:boolean, val Singlecol 39:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 34:boolean, IfExprStringScalarStringGroupColumn(col 35:boolean, val Twocol 38:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 35:boolean, IfExprColumnNull(col 36:boolean, col 37:string, null)(children: LongColLessLongScalar(col 4:int, val 10) -> 36:boolean, ConstantVectorExpression(val Some) -> 37:string) -> 38:string) -> 39:string) -> 40:string, IfExprLongColumnLongColumn(col 41:boolean, col 42:date, col 43:date)(children: StringGroupColEqualCharScalar(col 14:char(10), val SHIP) -> 41:boolean, VectorUDFDateAddColScalar(col 10:date, val 10) -> 42:date, VectorUDFDateAddColScalar(col 10:date, val 5) -> 43:date) -> 44:date, IfExprDoubleColumnDoubleColumn(col 45:boolean, col 47:doublecol 48:double)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 45:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 46:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 46:double) -> 47:double, ConstantVectorExpression(val 0.0) -> 48:double) -> 49:double, IfExprDoubleColumnDoubleScalar(col 50:boolean, col 52:double, val 0.0)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 50:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 51:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 51:double) -> 52:double) -> 53:double, IfExprNullColumn(col 54:boolean, null, col 79)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 54:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 79:decimal(10,2)) -> 55:decimal(10,2), IfExprColumnNull(col 56:boolean, col 80:decimal(10,2), null)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 56:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 80:decimal(10,2)) -> 57:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 58:boolean) -> 59:decimal(12,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 60:boolean) -> 61:decimal(12,2), IfExprDecimal64ScalarDecimal64Column(col 62:boolean, decimal64Val 0, decimalVal 0, col 7:decimal(10,2)/DECIMAL_64)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 62:boolean) -> 63:decimal(10,2)/DECIMAL_64, IfExprDecimal64ColumnDecimal64Scalar(col 64:boolean, col 7:decimal(10,2)/DECIMAL_64, decimal64Val 0, decimalVal 0)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 64:boolean) -> 65:decimal(10,2)/DECIMAL_64, IfExprTimestampColumnColumn(col 66:boolean, col 67:timestampcol 68:timestamp)(children: LongColGreaterLongScalar(col 1:int, val 30) -> 66:boolean, CastDateToTimestamp(col 12:date) -> 67:timestamp, CastDateToTimestamp(col 11:date) -> 68:timestamp) -> 69:timestamp, IfExprColumnNull(col 70:boolean, col 71:int, null)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 70:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 71:int) -> 72:int, IfExprNullColumn(col 73:boolean, null, col 74)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 73:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 74:int) -> 75:int, IfExprLongScalarLongScalar(col 77:boolean, val 14245, val 14609)(children: LongColGreaterLongScalar(col 76:int, val 100)(children: LongColModuloLongScalar(col 2:int, val 500) -> 76:int) -> 77:boolean) -> 78:date Statistics: Num rows: 101 Data size: 78500 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false @@ -872,13 +872,13 @@ STAGE PLANS: native: true vectorizationSchemaColumns: [0:l_orderkey:int, 1:l_partkey:int, 2:l_suppkey:int, 3:l_linenumber:int, 4:l_quantity:int, 5:l_extendedprice:double, 6:l_discount:double, 7:l_tax:decimal(10,2)/DECIMAL_64, 8:l_returnflag:char(1), 9:l_linestatus:char(1), 10:l_shipdate:date, 11:l_commitdate:date, 12:l_receiptdate:date, 13:l_shipinstruct:varchar(20), 14:l_shipmode:char(10), 15:l_comment:string, 16:ROW__ID:struct] Select Operator - expressions: l_quantity (type: int), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN (null) ELSE (null) END (type: string), if((l_shipmode = 'SHIP '), date_add(l_shipdate, 10), date_add(l_shipdate, 5)) (type: date), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END (type: double), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END (type: double), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(10,2)), if((l_partkey > 30), CAST( l_receiptdate AS TIMESTAMP), CAST( l_commitdate AS TIMESTAMP)) (type: timestamp), if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null) (type: int), if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)) (type: int), if(((l_suppkey % 500) > 100), DATE'2009-01-01', DATE'2009-12-31') (type: date) + expressions: l_quantity (type: int), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE ('Huge number') END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') WHEN ((l_quantity < 100)) THEN ('Many') ELSE (null) END (type: string), CASE WHEN ((l_quantity = 1)) THEN ('Single') WHEN ((l_quantity = 2)) THEN ('Two') WHEN ((l_quantity < 10)) THEN ('Some') ELSE (null) END (type: string), if((l_shipmode = 'SHIP '), date_add(l_shipdate, 10), date_add(l_shipdate, 5)) (type: date), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0) END (type: double), CASE WHEN ((l_returnflag = 'N')) THEN ((l_extendedprice * (1.0D - l_discount))) ELSE (0.0D) END (type: double), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), null, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, null) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(12,2)), if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax) (type: decimal(10,2)), if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0) (type: decimal(10,2)), if((l_partkey > 30), CAST( l_receiptdate AS TIMESTAMP), CAST( l_commitdate AS TIMESTAMP)) (type: timestamp), if((l_suppkey > 10000), datediff(l_receiptdate, l_commitdate), null) (type: int), if((l_suppkey > 10000), null, datediff(l_receiptdate, l_commitdate)) (type: int), if(((l_suppkey % 500) > 100), DATE'2009-01-01', DATE'2009-12-31') (type: date) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10, _col11, _col12, _col13, _col14, _col15, _col16 Select Vectorization: className: VectorSelectOperator native: true - projectedOutputColumnNums: [4, 27, 39, 49, 53, 58, 63, 65, 67, 72, 77, 79, 81, 85, 88, 91, 94] - selectExpressions: IfExprColumnCondExpr(col 17:boolean, col 18:stringcol 26:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 17:boolean, ConstantVectorExpression(val Single) -> 18:string, IfExprColumnCondExpr(col 19:boolean, col 20:stringcol 25:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 19:boolean, ConstantVectorExpression(val Two) -> 20:string, IfExprColumnCondExpr(col 21:boolean, col 22:stringcol 24:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 21:boolean, ConstantVectorExpression(val Some) -> 22:string, IfExprStringScalarStringScalar(col 23:boolean, val Many, val Huge number)(children: LongColLessLongScalar(col 4:int, val 100) -> 23:boolean) -> 24:string) -> 25:string) -> 26:string) -> 27:string, IfExprColumnCondExpr(col 28:boolean, col 29:stringcol 38:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 28:boolean, ConstantVectorExpression(val Single) -> 29:string, IfExprColumnCondExpr(col 30:boolean, col 31:stringcol 37:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 30:boolean, ConstantVectorExpression(val Two) -> 31:string, IfExprColumnCondExpr(col 32:boolean, col 33:stringcol 36:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 32:boolean, ConstantVectorExpression(val Some) -> 33:string, IfExprColumnNull(col 34:boolean, col 35:string, null)(children: LongColLessLongScalar(col 4:int, val 100) -> 34:boolean, ConstantVectorExpression(val Many) -> 35:string) -> 36:string) -> 37:string) -> 38:string) -> 39:string, IfExprColumnCondExpr(col 40:boolean, col 41:stringcol 48:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 40:boolean, ConstantVectorExpression(val Single) -> 41:string, IfExprColumnCondExpr(col 42:boolean, col 43:stringcol 47:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 42:boolean, ConstantVectorExpression(val Two) -> 43:string, IfExprColumnCondExpr(col 44:boolean, col 45:stringcol 46:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 44:boolean, ConstantVectorExpression(val Some) -> 45:string, IfExprNullNull(null, null) -> 46:string) -> 47:string) -> 48:string) -> 49:string, IfExprCondExprCondExpr(col 50:boolean, col 51:datecol 52:date)(children: StringGroupColEqualCharScalar(col 14:char(10), val SHIP) -> 50:boolean, VectorUDFDateAddColScalar(col 10:date, val 10) -> 51:date, VectorUDFDateAddColScalar(col 10:date, val 5) -> 52:date) -> 53:date, IfExprCondExprCondExpr(col 54:boolean, col 56:doublecol 57:double)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 54:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 55:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 55:double) -> 56:double, ConstantVectorExpression(val 0.0) -> 57:double) -> 58:double, IfExprCondExprColumn(col 59:boolean, col 61:double, col 62:double)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 59:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 60:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 60:double) -> 61:double, ConstantVectorExpression(val 0.0) -> 62:double) -> 63:double, IfExprNullColumn(col 64:boolean, null, col 95)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 64:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 95:decimal(10,2)) -> 65:decimal(10,2), IfExprColumnNull(col 66:boolean, col 96:decimal(10,2), null)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 66:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 96:decimal(10,2)) -> 67:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 71:boolean) -> 72:decimal(12,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 76:boolean) -> 77:decimal(12,2), IfExprDecimal64ScalarDecimal64Column(col 78:boolean, decimal64Val 0, decimalVal 0, col 7:decimal(10,2)/DECIMAL_64)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 78:boolean) -> 79:decimal(10,2)/DECIMAL_64, IfExprDecimal64ColumnDecimal64Scalar(col 80:boolean, col 7:decimal(10,2)/DECIMAL_64, decimal64Val 0, decimalVal 0)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 80:boolean) -> 81:decimal(10,2)/DECIMAL_64, IfExprCondExprCondExpr(col 82:boolean, col 83:timestampcol 84:timestamp)(children: LongColGreaterLongScalar(col 1:int, val 30) -> 82:boolean, CastDateToTimestamp(col 12:date) -> 83:timestamp, CastDateToTimestamp(col 11:date) -> 84:timestamp) -> 85:timestamp, IfExprCondExprNull(col 86:boolean, col 87:int, null)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 86:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 87:int) -> 88:int, IfExprNullCondExpr(col 89:boolean, null, col 90:int)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 89:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 90:int) -> 91:int, IfExprLongScalarLongScalar(col 93:boolean, val 14245, val 14609)(children: LongColGreaterLongScalar(col 92:int, val 100)(children: LongColModuloLongScalar(col 2:int, val 500) -> 92:int) -> 93:boolean) -> 94:date + projectedOutputColumnNums: [4, 27, 39, 48, 52, 57, 62, 64, 66, 71, 76, 78, 80, 84, 87, 90, 93] + selectExpressions: IfExprColumnCondExpr(col 17:boolean, col 18:stringcol 26:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 17:boolean, ConstantVectorExpression(val Single) -> 18:string, IfExprColumnCondExpr(col 19:boolean, col 20:stringcol 25:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 19:boolean, ConstantVectorExpression(val Two) -> 20:string, IfExprColumnCondExpr(col 21:boolean, col 22:stringcol 24:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 21:boolean, ConstantVectorExpression(val Some) -> 22:string, IfExprStringScalarStringScalar(col 23:boolean, val Many, val Huge number)(children: LongColLessLongScalar(col 4:int, val 100) -> 23:boolean) -> 24:string) -> 25:string) -> 26:string) -> 27:string, IfExprColumnCondExpr(col 28:boolean, col 29:stringcol 38:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 28:boolean, ConstantVectorExpression(val Single) -> 29:string, IfExprColumnCondExpr(col 30:boolean, col 31:stringcol 37:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 30:boolean, ConstantVectorExpression(val Two) -> 31:string, IfExprColumnCondExpr(col 32:boolean, col 33:stringcol 36:string)(children: LongColLessLongScalar(col 4:int, val 10) -> 32:boolean, ConstantVectorExpression(val Some) -> 33:string, IfExprColumnNull(col 34:boolean, col 35:string, null)(children: LongColLessLongScalar(col 4:int, val 100) -> 34:boolean, ConstantVectorExpression(val Many) -> 35:string) -> 36:string) -> 37:string) -> 38:string) -> 39:string, IfExprColumnCondExpr(col 40:boolean, col 41:stringcol 47:string)(children: LongColEqualLongScalar(col 4:int, val 1) -> 40:boolean, ConstantVectorExpression(val Single) -> 41:string, IfExprColumnCondExpr(col 42:boolean, col 43:stringcol 46:string)(children: LongColEqualLongScalar(col 4:int, val 2) -> 42:boolean, ConstantVectorExpression(val Two) -> 43:string, IfExprColumnNull(col 44:boolean, col 45:string, null)(children: LongColLessLongScalar(col 4:int, val 10) -> 44:boolean, ConstantVectorExpression(val Some) -> 45:string) -> 46:string) -> 47:string) -> 48:string, IfExprCondExprCondExpr(col 49:boolean, col 50:datecol 51:date)(children: StringGroupColEqualCharScalar(col 14:char(10), val SHIP) -> 49:boolean, VectorUDFDateAddColScalar(col 10:date, val 10) -> 50:date, VectorUDFDateAddColScalar(col 10:date, val 5) -> 51:date) -> 52:date, IfExprCondExprCondExpr(col 53:boolean, col 55:doublecol 56:double)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 53:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 54:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 54:double) -> 55:double, ConstantVectorExpression(val 0.0) -> 56:double) -> 57:double, IfExprCondExprColumn(col 58:boolean, col 60:double, col 61:double)(children: StringGroupColEqualCharScalar(col 8:char(1), val N) -> 58:boolean, DoubleColMultiplyDoubleColumn(col 5:double, col 59:double)(children: DoubleScalarSubtractDoubleColumn(val 1.0, col 6:double) -> 59:double) -> 60:double, ConstantVectorExpression(val 0.0) -> 61:double) -> 62:double, IfExprNullColumn(col 63:boolean, null, col 94)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 63:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 94:decimal(10,2)) -> 64:decimal(10,2), IfExprColumnNull(col 65:boolean, col 95:decimal(10,2), null)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 65:boolean, ConvertDecimal64ToDecimal(col 7:decimal(10,2)/DECIMAL_64) -> 95:decimal(10,2)) -> 66:decimal(10,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'DELIVER IN PERSON'), 0, l_tax))(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 70:boolean) -> 71:decimal(12,2), VectorUDFAdaptor(if((CAST( l_shipinstruct AS STRING) = 'TAKE BACK RETURN'), l_tax, 0))(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 75:boolean) -> 76:decimal(12,2), IfExprDecimal64ScalarDecimal64Column(col 77:boolean, decimal64Val 0, decimalVal 0, col 7:decimal(10,2)/DECIMAL_64)(children: StringGroupColEqualStringScalar(col 13:string, val DELIVER IN PERSON)(children: col 13:varchar(20)) -> 77:boolean) -> 78:decimal(10,2)/DECIMAL_64, IfExprDecimal64ColumnDecimal64Scalar(col 79:boolean, col 7:decimal(10,2)/DECIMAL_64, decimal64Val 0, decimalVal 0)(children: StringGroupColEqualStringScalar(col 13:string, val TAKE BACK RETURN)(children: col 13:varchar(20)) -> 79:boolean) -> 80:decimal(10,2)/DECIMAL_64, IfExprCondExprCondExpr(col 81:boolean, col 82:timestampcol 83:timestamp)(children: LongColGreaterLongScalar(col 1:int, val 30) -> 81:boolean, CastDateToTimestamp(col 12:date) -> 82:timestamp, CastDateToTimestamp(col 11:date) -> 83:timestamp) -> 84:timestamp, IfExprCondExprNull(col 85:boolean, col 86:int, null)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 85:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 86:int) -> 87:int, IfExprNullCondExpr(col 88:boolean, null, col 89:int)(children: LongColGreaterLongScalar(col 2:int, val 10000) -> 88:boolean, VectorUDFDateDiffColCol(col 12:date, col 11:date) -> 89:int) -> 90:int, IfExprLongScalarLongScalar(col 92:boolean, val 14245, val 14609)(children: LongColGreaterLongScalar(col 91:int, val 100)(children: LongColModuloLongScalar(col 2:int, val 500) -> 91:int) -> 92:boolean) -> 93:date Statistics: Num rows: 101 Data size: 78500 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false @@ -905,7 +905,7 @@ STAGE PLANS: includeColumns: [1, 2, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14] dataColumns: l_orderkey:int, l_partkey:int, l_suppkey:int, l_linenumber:int, l_quantity:int, l_extendedprice:double, l_discount:double, l_tax:decimal(10,2)/DECIMAL_64, l_returnflag:char(1), l_linestatus:char(1), l_shipdate:date, l_commitdate:date, l_receiptdate:date, l_shipinstruct:varchar(20), l_shipmode:char(10), l_comment:string partitionColumnCount: 0 - scratchColumnTypeNames: [bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, string, bigint, string, bigint, string, bigint, string, string, string, string, string, bigint, bigint, bigint, bigint, bigint, double, double, double, double, bigint, double, double, double, double, bigint, decimal(10,2), bigint, decimal(10,2), bigint, bigint, decimal(12,2), bigint, decimal(12,2), bigint, decimal(12,2), bigint, bigint, decimal(12,2), bigint, decimal(10,2)/DECIMAL_64, bigint, decimal(10,2)/DECIMAL_64, bigint, timestamp, timestamp, timestamp, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, decimal(10,2), decimal(10,2)] + scratchColumnTypeNames: [bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, string, bigint, string, bigint, string, bigint, string, string, string, string, bigint, bigint, bigint, bigint, bigint, double, double, double, double, bigint, double, double, double, double, bigint, decimal(10,2), bigint, decimal(10,2), bigint, bigint, decimal(12,2), bigint, decimal(12,2), bigint, decimal(12,2), bigint, bigint, decimal(12,2), bigint, decimal(10,2)/DECIMAL_64, bigint, decimal(10,2)/DECIMAL_64, bigint, timestamp, timestamp, timestamp, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, decimal(10,2), decimal(10,2)] Stage: Stage-0 Fetch Operator diff --git ql/src/test/results/clientpositive/vector_case_when_2.q.out ql/src/test/results/clientpositive/vector_case_when_2.q.out index a59166c2d6..77e3558863 100644 --- ql/src/test/results/clientpositive/vector_case_when_2.q.out +++ ql/src/test/results/clientpositive/vector_case_when_2.q.out @@ -138,13 +138,13 @@ STAGE PLANS: native: true vectorizationSchemaColumns: [0:cdate:date, 1:ctimestamp1:timestamp, 2:stimestamp1:string, 3:ctimestamp2:timestamp, 4:ROW__ID:struct] Select Operator - expressions: ctimestamp1 (type: timestamp), ctimestamp2 (type: timestamp), CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN (null) ELSE (null) END (type: string), if((ctimestamp1 < TIMESTAMP'1974-10-04 17:21:03.989'), year(ctimestamp1), year(ctimestamp2)) (type: int), CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END (type: string), if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)) (type: int), if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null) (type: int), if(((UDFToDouble(ctimestamp1) % 500.0D) > 100.0D), date_add(cdate, 1), date_add(cdate, 365)) (type: date), stimestamp1 (type: string) + expressions: ctimestamp1 (type: timestamp), ctimestamp2 (type: timestamp), CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') ELSE (null) END (type: string), if((ctimestamp1 < TIMESTAMP'1974-10-04 17:21:03.989'), year(ctimestamp1), year(ctimestamp2)) (type: int), CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END (type: string), if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)) (type: int), if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null) (type: int), if(((UDFToDouble(ctimestamp1) % 500.0D) > 100.0D), date_add(cdate, 1), date_add(cdate, 365)) (type: date), stimestamp1 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10 Select Vectorization: className: VectorSelectOperator native: true - projectedOutputColumnNums: [1, 3, 9, 14, 19, 23, 25, 28, 33, 39, 2] - selectExpressions: VectorUDFAdaptor(CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 1800-12-31 00:00:00) -> 5:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 1900-01-01 00:00:00) -> 6:boolean, TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 7:boolean, TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 8:boolean) -> 9:string, VectorUDFAdaptor(CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 10:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 11:boolean, TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 12:boolean, TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 13:boolean) -> 14:string, VectorUDFAdaptor(CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN (null) ELSE (null) END)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 15:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 16:boolean, TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 17:boolean, TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 18:boolean) -> 19:string, IfExprLongColumnLongColumn(col 20:boolean, col 21:int, col 22:int)(children: TimestampColLessTimestampScalar(col 1:timestamp, val 1974-10-04 17:21:03.989) -> 20:boolean, VectorUDFYearTimestamp(col 1:timestamp, field YEAR) -> 21:int, VectorUDFYearTimestamp(col 3:timestamp, field YEAR) -> 22:int) -> 23:int, VectorUDFAdaptor(CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END)(children: SelectStringColLikeStringScalar(col 2:string) -> 24:boolean) -> 25:string, VectorUDFAdaptor(if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)))(children: TimestampColEqualTimestampScalar(col 1:timestamp, val 2021-09-24 03:18:32.413655165) -> 26:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 27:int) -> 28:int, VectorUDFAdaptor(if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null))(children: ColAndCol(col 29:boolean, col 30:boolean)(children: TimestampColGreaterEqualTimestampScalar(col 3:timestamp, val 5344-10-04 18:40:08.165) -> 29:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 6631-11-13 16:31:29.702202248) -> 30:boolean) -> 31:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 32:int) -> 33:int, IfExprLongColumnLongColumn(col 36:boolean, col 37:date, col 38:date)(children: DoubleColGreaterDoubleScalar(col 35:double, val 100.0)(children: DoubleColModuloDoubleScalar(col 34:double, val 500.0)(children: CastTimestampToDouble(col 1:timestamp) -> 34:double) -> 35:double) -> 36:boolean, VectorUDFDateAddColScalar(col 0:date, val 1) -> 37:date, VectorUDFDateAddColScalar(col 0:date, val 365) -> 38:date) -> 39:date + projectedOutputColumnNums: [1, 3, 9, 14, 18, 22, 24, 27, 32, 38, 2] + selectExpressions: VectorUDFAdaptor(CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 1800-12-31 00:00:00) -> 5:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 1900-01-01 00:00:00) -> 6:boolean, TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 7:boolean, TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 8:boolean) -> 9:string, VectorUDFAdaptor(CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 10:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 11:boolean, TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 12:boolean, TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 13:boolean) -> 14:string, VectorUDFAdaptor(CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') ELSE (null) END)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 15:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 16:boolean, TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 17:boolean) -> 18:string, IfExprLongColumnLongColumn(col 19:boolean, col 20:int, col 21:int)(children: TimestampColLessTimestampScalar(col 1:timestamp, val 1974-10-04 17:21:03.989) -> 19:boolean, VectorUDFYearTimestamp(col 1:timestamp, field YEAR) -> 20:int, VectorUDFYearTimestamp(col 3:timestamp, field YEAR) -> 21:int) -> 22:int, VectorUDFAdaptor(CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END)(children: SelectStringColLikeStringScalar(col 2:string) -> 23:boolean) -> 24:string, VectorUDFAdaptor(if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)))(children: TimestampColEqualTimestampScalar(col 1:timestamp, val 2021-09-24 03:18:32.413655165) -> 25:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 26:int) -> 27:int, VectorUDFAdaptor(if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null))(children: ColAndCol(col 28:boolean, col 29:boolean)(children: TimestampColGreaterEqualTimestampScalar(col 3:timestamp, val 5344-10-04 18:40:08.165) -> 28:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 6631-11-13 16:31:29.702202248) -> 29:boolean) -> 30:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 31:int) -> 32:int, IfExprLongColumnLongColumn(col 35:boolean, col 36:date, col 37:date)(children: DoubleColGreaterDoubleScalar(col 34:double, val 100.0)(children: DoubleColModuloDoubleScalar(col 33:double, val 500.0)(children: CastTimestampToDouble(col 1:timestamp) -> 33:double) -> 34:double) -> 35:boolean, VectorUDFDateAddColScalar(col 0:date, val 1) -> 36:date, VectorUDFDateAddColScalar(col 0:date, val 365) -> 37:date) -> 38:date Statistics: Num rows: 51 Data size: 12300 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: timestamp), _col10 (type: string), _col1 (type: timestamp) @@ -171,7 +171,7 @@ STAGE PLANS: includeColumns: [0, 1, 2, 3] dataColumns: cdate:date, ctimestamp1:timestamp, stimestamp1:string, ctimestamp2:timestamp partitionColumnCount: 0 - scratchColumnTypeNames: [bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, double, double, bigint, bigint, bigint, bigint] + scratchColumnTypeNames: [bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, double, double, bigint, bigint, bigint, bigint] Reduce Vectorization: enabled: false enableConditionsMet: hive.vectorized.execution.reduce.enabled IS true @@ -401,13 +401,13 @@ STAGE PLANS: native: true vectorizationSchemaColumns: [0:cdate:date, 1:ctimestamp1:timestamp, 2:stimestamp1:string, 3:ctimestamp2:timestamp, 4:ROW__ID:struct] Select Operator - expressions: ctimestamp1 (type: timestamp), ctimestamp2 (type: timestamp), CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN (null) ELSE (null) END (type: string), if((ctimestamp1 < TIMESTAMP'1974-10-04 17:21:03.989'), year(ctimestamp1), year(ctimestamp2)) (type: int), CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END (type: string), if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)) (type: int), if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null) (type: int), if(((UDFToDouble(ctimestamp1) % 500.0D) > 100.0D), date_add(cdate, 1), date_add(cdate, 365)) (type: date), stimestamp1 (type: string) + expressions: ctimestamp1 (type: timestamp), ctimestamp2 (type: timestamp), CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') ELSE (null) END (type: string), if((ctimestamp1 < TIMESTAMP'1974-10-04 17:21:03.989'), year(ctimestamp1), year(ctimestamp2)) (type: int), CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END (type: string), if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)) (type: int), if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null) (type: int), if(((UDFToDouble(ctimestamp1) % 500.0D) > 100.0D), date_add(cdate, 1), date_add(cdate, 365)) (type: date), stimestamp1 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10 Select Vectorization: className: VectorSelectOperator native: true projectedOutputColumnNums: [1, 3, 12, 21, 28, 32, 34, 37, 42, 48, 2] - selectExpressions: IfExprStringScalarStringGroupColumn(col 5:boolean, val 1800s or Earliercol 11:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 1800-12-31 00:00:00) -> 5:boolean, IfExprStringScalarStringGroupColumn(col 6:boolean, val 1900scol 10:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 1900-01-01 00:00:00) -> 6:boolean, IfExprStringScalarStringGroupColumn(col 7:boolean, val Late 2000scol 9:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 7:boolean, IfExprStringScalarStringScalar(col 8:boolean, val Early 2010s, val Unknown)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 8:boolean) -> 9:string) -> 10:string) -> 11:string) -> 12:string, IfExprStringScalarStringGroupColumn(col 13:boolean, val Oldcol 20:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 13:boolean, IfExprStringScalarStringGroupColumn(col 14:boolean, val Early 2000scol 19:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 14:boolean, IfExprStringScalarStringGroupColumn(col 15:boolean, val Late 2000scol 18:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 15:boolean, IfExprColumnNull(col 16:boolean, col 17:string, null)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 16:boolean, ConstantVectorExpression(val Early 2010s) -> 17:string) -> 18:string) -> 19:string) -> 20:string) -> 21:string, IfExprStringScalarStringGroupColumn(col 22:boolean, val Oldcol 27:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 22:boolean, IfExprStringScalarStringGroupColumn(col 23:boolean, val Early 2000scol 26:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 23:boolean, IfExprStringScalarStringGroupColumn(col 24:boolean, val Late 2000scol 25:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 24:boolean, IfExprNullNull(null, null) -> 25:string) -> 26:string) -> 27:string) -> 28:string, IfExprLongColumnLongColumn(col 29:boolean, col 30:int, col 31:int)(children: TimestampColLessTimestampScalar(col 1:timestamp, val 1974-10-04 17:21:03.989) -> 29:boolean, VectorUDFYearTimestamp(col 1:timestamp, field YEAR) -> 30:int, VectorUDFYearTimestamp(col 3:timestamp, field YEAR) -> 31:int) -> 32:int, IfExprStringGroupColumnStringScalar(col 33:boolean, col 2:string, val 2018-03-08 23:04:59)(children: SelectStringColLikeStringScalar(col 2:string) -> 33:boolean) -> 34:string, IfExprNullColumn(col 35:boolean, null, col 36)(children: TimestampColEqualTimestampScalar(col 1:timestamp, val 2021-09-24 03:18:32.413655165) -> 35:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 36:int) -> 37:int, IfExprColumnNull(col 40:boolean, col 41:int, null)(children: ColAndCol(col 38:boolean, col 39:boolean)(children: TimestampColGreaterEqualTimestampScalar(col 3:timestamp, val 5344-10-04 18:40:08.165) -> 38:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 6631-11-13 16:31:29.702202248) -> 39:boolean) -> 40:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 41:int) -> 42:int, IfExprLongColumnLongColumn(col 45:boolean, col 46:date, col 47:date)(children: DoubleColGreaterDoubleScalar(col 44:double, val 100.0)(children: DoubleColModuloDoubleScalar(col 43:double, val 500.0)(children: CastTimestampToDouble(col 1:timestamp) -> 43:double) -> 44:double) -> 45:boolean, VectorUDFDateAddColScalar(col 0:date, val 1) -> 46:date, VectorUDFDateAddColScalar(col 0:date, val 365) -> 47:date) -> 48:date + selectExpressions: IfExprStringScalarStringGroupColumn(col 5:boolean, val 1800s or Earliercol 11:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 1800-12-31 00:00:00) -> 5:boolean, IfExprStringScalarStringGroupColumn(col 6:boolean, val 1900scol 10:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 1900-01-01 00:00:00) -> 6:boolean, IfExprStringScalarStringGroupColumn(col 7:boolean, val Late 2000scol 9:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 7:boolean, IfExprStringScalarStringScalar(col 8:boolean, val Early 2010s, val Unknown)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 8:boolean) -> 9:string) -> 10:string) -> 11:string) -> 12:string, IfExprStringScalarStringGroupColumn(col 13:boolean, val Oldcol 20:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 13:boolean, IfExprStringScalarStringGroupColumn(col 14:boolean, val Early 2000scol 19:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 14:boolean, IfExprStringScalarStringGroupColumn(col 15:boolean, val Late 2000scol 18:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 15:boolean, IfExprColumnNull(col 16:boolean, col 17:string, null)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 16:boolean, ConstantVectorExpression(val Early 2010s) -> 17:string) -> 18:string) -> 19:string) -> 20:string) -> 21:string, IfExprStringScalarStringGroupColumn(col 22:boolean, val Oldcol 27:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 22:boolean, IfExprStringScalarStringGroupColumn(col 23:boolean, val Early 2000scol 26:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 23:boolean, IfExprColumnNull(col 24:boolean, col 25:string, null)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 24:boolean, ConstantVectorExpression(val Late 2000s) -> 25:string) -> 26:string) -> 27:string) -> 28:string, IfExprLongColumnLongColumn(col 29:boolean, col 30:int, col 31:int)(children: TimestampColLessTimestampScalar(col 1:timestamp, val 1974-10-04 17:21:03.989) -> 29:boolean, VectorUDFYearTimestamp(col 1:timestamp, field YEAR) -> 30:int, VectorUDFYearTimestamp(col 3:timestamp, field YEAR) -> 31:int) -> 32:int, IfExprStringGroupColumnStringScalar(col 33:boolean, col 2:string, val 2018-03-08 23:04:59)(children: SelectStringColLikeStringScalar(col 2:string) -> 33:boolean) -> 34:string, IfExprNullColumn(col 35:boolean, null, col 36)(children: TimestampColEqualTimestampScalar(col 1:timestamp, val 2021-09-24 03:18:32.413655165) -> 35:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 36:int) -> 37:int, IfExprColumnNull(col 40:boolean, col 41:int, null)(children: ColAndCol(col 38:boolean, col 39:boolean)(children: TimestampColGreaterEqualTimestampScalar(col 3:timestamp, val 5344-10-04 18:40:08.165) -> 38:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 6631-11-13 16:31:29.702202248) -> 39:boolean) -> 40:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 41:int) -> 42:int, IfExprLongColumnLongColumn(col 45:boolean, col 46:date, col 47:date)(children: DoubleColGreaterDoubleScalar(col 44:double, val 100.0)(children: DoubleColModuloDoubleScalar(col 43:double, val 500.0)(children: CastTimestampToDouble(col 1:timestamp) -> 43:double) -> 44:double) -> 45:boolean, VectorUDFDateAddColScalar(col 0:date, val 1) -> 46:date, VectorUDFDateAddColScalar(col 0:date, val 365) -> 47:date) -> 48:date Statistics: Num rows: 51 Data size: 12300 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: timestamp), _col10 (type: string), _col1 (type: timestamp) @@ -664,13 +664,13 @@ STAGE PLANS: native: true vectorizationSchemaColumns: [0:cdate:date, 1:ctimestamp1:timestamp, 2:stimestamp1:string, 3:ctimestamp2:timestamp, 4:ROW__ID:struct] Select Operator - expressions: ctimestamp1 (type: timestamp), ctimestamp2 (type: timestamp), CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN (null) ELSE (null) END (type: string), if((ctimestamp1 < TIMESTAMP'1974-10-04 17:21:03.989'), year(ctimestamp1), year(ctimestamp2)) (type: int), CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END (type: string), if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)) (type: int), if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null) (type: int), if(((UDFToDouble(ctimestamp1) % 500.0D) > 100.0D), date_add(cdate, 1), date_add(cdate, 365)) (type: date), stimestamp1 (type: string) + expressions: ctimestamp1 (type: timestamp), ctimestamp2 (type: timestamp), CASE WHEN ((ctimestamp2 <= TIMESTAMP'1800-12-31 00:00:00')) THEN ('1800s or Earlier') WHEN ((ctimestamp2 < TIMESTAMP'1900-01-01 00:00:00')) THEN ('1900s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE ('Unknown') END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') WHEN ((ctimestamp2 <= TIMESTAMP'2015-12-31 23:59:59.999999999')) THEN ('Early 2010s') ELSE (null) END (type: string), CASE WHEN ((ctimestamp2 <= TIMESTAMP'2000-12-31 23:59:59.999999999')) THEN ('Old') WHEN ((ctimestamp2 < TIMESTAMP'2006-01-01 00:00:00')) THEN ('Early 2000s') WHEN (ctimestamp2 BETWEEN TIMESTAMP'2006-01-01 00:00:00' AND TIMESTAMP'2010-12-31 23:59:59.999999999') THEN ('Late 2000s') ELSE (null) END (type: string), if((ctimestamp1 < TIMESTAMP'1974-10-04 17:21:03.989'), year(ctimestamp1), year(ctimestamp2)) (type: int), CASE WHEN ((stimestamp1 like '%19%')) THEN (stimestamp1) ELSE ('2018-03-08 23:04:59') END (type: string), if((ctimestamp1 = TIMESTAMP'2021-09-24 03:18:32.413655165'), null, minute(ctimestamp1)) (type: int), if(((ctimestamp2 >= TIMESTAMP'5344-10-04 18:40:08.165') and (ctimestamp2 < TIMESTAMP'6631-11-13 16:31:29.702202248')), minute(ctimestamp1), null) (type: int), if(((UDFToDouble(ctimestamp1) % 500.0D) > 100.0D), date_add(cdate, 1), date_add(cdate, 365)) (type: date), stimestamp1 (type: string) outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9, _col10 Select Vectorization: className: VectorSelectOperator native: true - projectedOutputColumnNums: [1, 3, 15, 27, 37, 41, 43, 46, 51, 57, 2] - selectExpressions: IfExprColumnCondExpr(col 5:boolean, col 6:stringcol 14:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 1800-12-31 00:00:00) -> 5:boolean, ConstantVectorExpression(val 1800s or Earlier) -> 6:string, IfExprColumnCondExpr(col 7:boolean, col 8:stringcol 13:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 1900-01-01 00:00:00) -> 7:boolean, ConstantVectorExpression(val 1900s) -> 8:string, IfExprColumnCondExpr(col 9:boolean, col 10:stringcol 12:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 9:boolean, ConstantVectorExpression(val Late 2000s) -> 10:string, IfExprStringScalarStringScalar(col 11:boolean, val Early 2010s, val Unknown)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 11:boolean) -> 12:string) -> 13:string) -> 14:string) -> 15:string, IfExprColumnCondExpr(col 16:boolean, col 17:stringcol 26:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 16:boolean, ConstantVectorExpression(val Old) -> 17:string, IfExprColumnCondExpr(col 18:boolean, col 19:stringcol 25:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 18:boolean, ConstantVectorExpression(val Early 2000s) -> 19:string, IfExprColumnCondExpr(col 20:boolean, col 21:stringcol 24:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 20:boolean, ConstantVectorExpression(val Late 2000s) -> 21:string, IfExprColumnNull(col 22:boolean, col 23:string, null)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 22:boolean, ConstantVectorExpression(val Early 2010s) -> 23:string) -> 24:string) -> 25:string) -> 26:string) -> 27:string, IfExprColumnCondExpr(col 28:boolean, col 29:stringcol 36:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 28:boolean, ConstantVectorExpression(val Old) -> 29:string, IfExprColumnCondExpr(col 30:boolean, col 31:stringcol 35:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 30:boolean, ConstantVectorExpression(val Early 2000s) -> 31:string, IfExprColumnCondExpr(col 32:boolean, col 33:stringcol 34:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 32:boolean, ConstantVectorExpression(val Late 2000s) -> 33:string, IfExprNullNull(null, null) -> 34:string) -> 35:string) -> 36:string) -> 37:string, IfExprCondExprCondExpr(col 38:boolean, col 39:intcol 40:int)(children: TimestampColLessTimestampScalar(col 1:timestamp, val 1974-10-04 17:21:03.989) -> 38:boolean, VectorUDFYearTimestamp(col 1:timestamp, field YEAR) -> 39:int, VectorUDFYearTimestamp(col 3:timestamp, field YEAR) -> 40:int) -> 41:int, IfExprStringGroupColumnStringScalar(col 42:boolean, col 2:string, val 2018-03-08 23:04:59)(children: SelectStringColLikeStringScalar(col 2:string) -> 42:boolean) -> 43:string, IfExprNullCondExpr(col 44:boolean, null, col 45:int)(children: TimestampColEqualTimestampScalar(col 1:timestamp, val 2021-09-24 03:18:32.413655165) -> 44:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 45:int) -> 46:int, IfExprCondExprNull(col 49:boolean, col 50:int, null)(children: ColAndCol(col 47:boolean, col 48:boolean)(children: TimestampColGreaterEqualTimestampScalar(col 3:timestamp, val 5344-10-04 18:40:08.165) -> 47:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 6631-11-13 16:31:29.702202248) -> 48:boolean) -> 49:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 50:int) -> 51:int, IfExprCondExprCondExpr(col 54:boolean, col 55:datecol 56:date)(children: DoubleColGreaterDoubleScalar(col 53:double, val 100.0)(children: DoubleColModuloDoubleScalar(col 52:double, val 500.0)(children: CastTimestampToDouble(col 1:timestamp) -> 52:double) -> 53:double) -> 54:boolean, VectorUDFDateAddColScalar(col 0:date, val 1) -> 55:date, VectorUDFDateAddColScalar(col 0:date, val 365) -> 56:date) -> 57:date + projectedOutputColumnNums: [1, 3, 15, 27, 36, 40, 42, 45, 50, 56, 2] + selectExpressions: IfExprColumnCondExpr(col 5:boolean, col 6:stringcol 14:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 1800-12-31 00:00:00) -> 5:boolean, ConstantVectorExpression(val 1800s or Earlier) -> 6:string, IfExprColumnCondExpr(col 7:boolean, col 8:stringcol 13:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 1900-01-01 00:00:00) -> 7:boolean, ConstantVectorExpression(val 1900s) -> 8:string, IfExprColumnCondExpr(col 9:boolean, col 10:stringcol 12:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 9:boolean, ConstantVectorExpression(val Late 2000s) -> 10:string, IfExprStringScalarStringScalar(col 11:boolean, val Early 2010s, val Unknown)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 11:boolean) -> 12:string) -> 13:string) -> 14:string) -> 15:string, IfExprColumnCondExpr(col 16:boolean, col 17:stringcol 26:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 16:boolean, ConstantVectorExpression(val Old) -> 17:string, IfExprColumnCondExpr(col 18:boolean, col 19:stringcol 25:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 18:boolean, ConstantVectorExpression(val Early 2000s) -> 19:string, IfExprColumnCondExpr(col 20:boolean, col 21:stringcol 24:string)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 20:boolean, ConstantVectorExpression(val Late 2000s) -> 21:string, IfExprColumnNull(col 22:boolean, col 23:string, null)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2015-12-31 23:59:59.999999999) -> 22:boolean, ConstantVectorExpression(val Early 2010s) -> 23:string) -> 24:string) -> 25:string) -> 26:string) -> 27:string, IfExprColumnCondExpr(col 28:boolean, col 29:stringcol 35:string)(children: TimestampColLessEqualTimestampScalar(col 3:timestamp, val 2000-12-31 23:59:59.999999999) -> 28:boolean, ConstantVectorExpression(val Old) -> 29:string, IfExprColumnCondExpr(col 30:boolean, col 31:stringcol 34:string)(children: TimestampColLessTimestampScalar(col 3:timestamp, val 2006-01-01 00:00:00) -> 30:boolean, ConstantVectorExpression(val Early 2000s) -> 31:string, IfExprColumnNull(col 32:boolean, col 33:string, null)(children: TimestampColumnBetween(col 3:timestamp, left 2005-12-31 16:00:00.0, right 2010-12-31 15:59:59.999999999) -> 32:boolean, ConstantVectorExpression(val Late 2000s) -> 33:string) -> 34:string) -> 35:string) -> 36:string, IfExprCondExprCondExpr(col 37:boolean, col 38:intcol 39:int)(children: TimestampColLessTimestampScalar(col 1:timestamp, val 1974-10-04 17:21:03.989) -> 37:boolean, VectorUDFYearTimestamp(col 1:timestamp, field YEAR) -> 38:int, VectorUDFYearTimestamp(col 3:timestamp, field YEAR) -> 39:int) -> 40:int, IfExprStringGroupColumnStringScalar(col 41:boolean, col 2:string, val 2018-03-08 23:04:59)(children: SelectStringColLikeStringScalar(col 2:string) -> 41:boolean) -> 42:string, IfExprNullCondExpr(col 43:boolean, null, col 44:int)(children: TimestampColEqualTimestampScalar(col 1:timestamp, val 2021-09-24 03:18:32.413655165) -> 43:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 44:int) -> 45:int, IfExprCondExprNull(col 48:boolean, col 49:int, null)(children: ColAndCol(col 46:boolean, col 47:boolean)(children: TimestampColGreaterEqualTimestampScalar(col 3:timestamp, val 5344-10-04 18:40:08.165) -> 46:boolean, TimestampColLessTimestampScalar(col 3:timestamp, val 6631-11-13 16:31:29.702202248) -> 47:boolean) -> 48:boolean, VectorUDFMinuteTimestamp(col 1:timestamp, field MINUTE) -> 49:int) -> 50:int, IfExprCondExprCondExpr(col 53:boolean, col 54:datecol 55:date)(children: DoubleColGreaterDoubleScalar(col 52:double, val 100.0)(children: DoubleColModuloDoubleScalar(col 51:double, val 500.0)(children: CastTimestampToDouble(col 1:timestamp) -> 51:double) -> 52:double) -> 53:boolean, VectorUDFDateAddColScalar(col 0:date, val 1) -> 54:date, VectorUDFDateAddColScalar(col 0:date, val 365) -> 55:date) -> 56:date Statistics: Num rows: 51 Data size: 12300 Basic stats: COMPLETE Column stats: NONE Reduce Output Operator key expressions: _col0 (type: timestamp), _col10 (type: string), _col1 (type: timestamp) @@ -697,7 +697,7 @@ STAGE PLANS: includeColumns: [0, 1, 2, 3] dataColumns: cdate:date, ctimestamp1:timestamp, stimestamp1:string, ctimestamp2:timestamp partitionColumnCount: 0 - scratchColumnTypeNames: [bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, string, bigint, string, bigint, string, bigint, string, string, string, string, string, bigint, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, double, double, bigint, bigint, bigint, bigint] + scratchColumnTypeNames: [bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, bigint, string, bigint, string, bigint, string, bigint, string, string, string, string, string, bigint, string, bigint, string, bigint, string, string, string, string, bigint, bigint, bigint, bigint, bigint, string, bigint, bigint, bigint, bigint, bigint, bigint, bigint, bigint, double, double, bigint, bigint, bigint, bigint] Reduce Vectorization: enabled: false enableConditionsMet: hive.vectorized.execution.reduce.enabled IS true diff --git ql/src/test/results/clientpositive/vector_coalesce_3.q.out ql/src/test/results/clientpositive/vector_coalesce_3.q.out index cf9d9e3521..5db881877f 100644 --- ql/src/test/results/clientpositive/vector_coalesce_3.q.out +++ ql/src/test/results/clientpositive/vector_coalesce_3.q.out @@ -88,7 +88,7 @@ STAGE PLANS: alias: n Statistics: Num rows: 3 Data size: 32 Basic stats: COMPLETE Column stats: NONE Select Operator - expressions: member (type: bigint), CASE WHEN (CASE WHEN (attr is not null) THEN ((attr > 1L)) ELSE (true) END) THEN (attr) ELSE (null) END (type: bigint) + expressions: member (type: bigint), CASE WHEN (((attr > 1L) or attr is null)) THEN (attr) ELSE (null) END (type: bigint) outputColumnNames: _col0, _col1 Statistics: Num rows: 3 Data size: 32 Basic stats: COMPLETE Column stats: NONE HashTable Sink Operator diff --git ql/src/test/results/clientpositive/vector_decimal_math_funcs.q.out ql/src/test/results/clientpositive/vector_decimal_math_funcs.q.out index da2a93561f..4d17e916ab 100644 --- ql/src/test/results/clientpositive/vector_decimal_math_funcs.q.out +++ ql/src/test/results/clientpositive/vector_decimal_math_funcs.q.out @@ -116,7 +116,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: decimal_test_n0 - filterExpr: (((cbigint % 500) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) + filterExpr: (((cbigint % 500L) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) Statistics: Num rows: 12289 Data size: 2201752 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -126,7 +126,7 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: FilterExprAndExpr(children: FilterLongColEqualLongScalar(col 5:bigint, val 0)(children: LongColModuloLongScalar(col 0:bigint, val 500) -> 5:bigint), FilterDoubleColGreaterEqualDoubleScalar(col 7:double, val -1.0)(children: FuncSinDoubleToDouble(col 6:double)(children: CastDecimalToDouble(col 2:decimal(20,10)) -> 6:double) -> 7:double)) - predicate: (((cbigint % 500) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) + predicate: (((cbigint % 500L) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) Statistics: Num rows: 2048 Data size: 366928 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: cdecimal1 (type: decimal(20,10)), round(cdecimal1, 2) (type: decimal(13,2)), round(cdecimal1) (type: decimal(11,0)), floor(cdecimal1) (type: decimal(11,0)), ceil(cdecimal1) (type: decimal(11,0)), round(exp(cdecimal1), 58) (type: double), ln(cdecimal1) (type: double), log10(cdecimal1) (type: double), log2(cdecimal1) (type: double), log2((cdecimal1 - 15601)) (type: double), log(2, cdecimal1) (type: double), power(log2(cdecimal1), 2) (type: double), power(log2(cdecimal1), 2) (type: double), sqrt(cdecimal1) (type: double), abs(cdecimal1) (type: decimal(20,10)), sin(cdecimal1) (type: double), asin(cdecimal1) (type: double), cos(cdecimal1) (type: double), acos(cdecimal1) (type: double), atan(cdecimal1) (type: double), degrees(cdecimal1) (type: double), radians(cdecimal1) (type: double), cdecimal1 (type: decimal(20,10)), (- cdecimal1) (type: decimal(20,10)), sign(cdecimal1) (type: int), cos(((- sin(log(cdecimal1))) + 3.14159D)) (type: double) @@ -363,7 +363,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: decimal_test_small - filterExpr: (((cbigint % 500) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) + filterExpr: (((cbigint % 500L) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) Statistics: Num rows: 12288 Data size: 2201192 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -373,7 +373,7 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: FilterExprAndExpr(children: FilterLongColEqualLongScalar(col 5:bigint, val 0)(children: LongColModuloLongScalar(col 0:bigint, val 500) -> 5:bigint), FilterDoubleColGreaterEqualDoubleScalar(col 8:double, val -1.0)(children: FuncSinDoubleToDouble(col 7:double)(children: CastDecimalToDouble(col 6:decimal(12,4))(children: ConvertDecimal64ToDecimal(col 2:decimal(12,4)/DECIMAL_64) -> 6:decimal(12,4)) -> 7:double) -> 8:double)) - predicate: (((cbigint % 500) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) + predicate: (((cbigint % 500L) = 0) and (sin(cdecimal1) >= -1.0D)) (type: boolean) Statistics: Num rows: 2048 Data size: 366865 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: cdecimal1 (type: decimal(12,4)), round(cdecimal1, 2) (type: decimal(11,2)), round(cdecimal1) (type: decimal(9,0)), floor(cdecimal1) (type: decimal(9,0)), ceil(cdecimal1) (type: decimal(9,0)), round(exp(cdecimal1), 58) (type: double), ln(cdecimal1) (type: double), log10(cdecimal1) (type: double), log2(cdecimal1) (type: double), log2((cdecimal1 - 15601)) (type: double), log(2, cdecimal1) (type: double), power(log2(cdecimal1), 2) (type: double), power(log2(cdecimal1), 2) (type: double), sqrt(cdecimal1) (type: double), abs(cdecimal1) (type: decimal(12,4)), sin(cdecimal1) (type: double), asin(cdecimal1) (type: double), cos(cdecimal1) (type: double), acos(cdecimal1) (type: double), atan(cdecimal1) (type: double), degrees(cdecimal1) (type: double), radians(cdecimal1) (type: double), cdecimal1 (type: decimal(12,4)), (- cdecimal1) (type: decimal(12,4)), sign(cdecimal1) (type: int), cos(((- sin(log(cdecimal1))) + 3.14159D)) (type: double) diff --git ql/src/test/results/clientpositive/vector_groupby_mapjoin.q.out ql/src/test/results/clientpositive/vector_groupby_mapjoin.q.out index 1f60366c5e..56fb08ef1d 100644 --- ql/src/test/results/clientpositive/vector_groupby_mapjoin.q.out +++ ql/src/test/results/clientpositive/vector_groupby_mapjoin.q.out @@ -228,9 +228,9 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterLongColEqualLongScalar(col 3:bigint, val 0), FilterExprAndExpr(children: SelectColumnIsNull(col 2:boolean), SelectColumnIsNotNull(col 0:string), FilterLongColGreaterEqualLongColumn(col 4:bigint, col 3:bigint))) - predicate: ((_col2 = 0L) or (_col5 is null and _col0 is not null and (_col3 >= _col2))) (type: boolean) - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + predicateExpression: FilterExprAndExpr(children: FilterExprOrExpr(children: SelectColumnIsNull(col 2:boolean), FilterLongColEqualLongScalar(col 3:bigint, val 0)), FilterExprOrExpr(children: SelectColumnIsNotNull(col 0:string), FilterLongColEqualLongScalar(col 3:bigint, val 0), SelectColumnIsNotNull(col 2:boolean)), FilterExprOrExpr(children: FilterLongColGreaterEqualLongColumn(col 4:bigint, col 3:bigint), FilterLongColEqualLongScalar(col 3:bigint, val 0), SelectColumnIsNotNull(col 2:boolean), SelectColumnIsNull(col 0:string))) + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col0 is null) and (_col0 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: string) outputColumnNames: _col0, _col1 @@ -238,7 +238,7 @@ STAGE PLANS: className: VectorSelectOperator native: true projectedOutputColumnNums: [0, 1] - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false File Sink Vectorization: @@ -275,7 +275,7 @@ STAGE PLANS: native: false nativeConditionsMet: hive.vectorized.execution.reducesink.new.enabled IS true, No PTF TopN IS true, No DISTINCT columns IS true, BinarySortableSerDe for keys IS true, LazyBinarySerDe for values IS true nativeConditionsNotMet: hive.execution.engine mr IN [tez, spark] IS false - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE value expressions: _col1 (type: string) Execution mode: vectorized Map Vectorization: @@ -295,10 +295,10 @@ STAGE PLANS: Select Operator expressions: KEY.reducesinkkey0 (type: string), VALUE._col0 (type: string) outputColumnNames: _col0, _col1 - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE table: input format: org.apache.hadoop.mapred.SequenceFileInputFormat output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat @@ -350,9 +350,9 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterLongColEqualLongScalar(col 3:bigint, val 0), FilterExprAndExpr(children: SelectColumnIsNull(col 2:boolean), SelectColumnIsNotNull(col 0:string), FilterLongColGreaterEqualLongColumn(col 4:bigint, col 3:bigint))) - predicate: ((_col2 = 0L) or (_col5 is null and _col0 is not null and (_col3 >= _col2))) (type: boolean) - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + predicateExpression: FilterExprAndExpr(children: FilterExprOrExpr(children: SelectColumnIsNull(col 2:boolean), FilterLongColEqualLongScalar(col 3:bigint, val 0)), FilterExprOrExpr(children: SelectColumnIsNotNull(col 0:string), FilterLongColEqualLongScalar(col 3:bigint, val 0), SelectColumnIsNotNull(col 2:boolean)), FilterExprOrExpr(children: FilterLongColGreaterEqualLongColumn(col 4:bigint, col 3:bigint), FilterLongColEqualLongScalar(col 3:bigint, val 0), SelectColumnIsNotNull(col 2:boolean), SelectColumnIsNull(col 0:string))) + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col0 is null) and (_col0 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: string) outputColumnNames: _col0, _col1 @@ -360,7 +360,7 @@ STAGE PLANS: className: VectorSelectOperator native: true projectedOutputColumnNums: [0, 1] - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false File Sink Vectorization: @@ -410,12 +410,12 @@ STAGE PLANS: outputColumnNames: _col0, _col1, _col2, _col3, _col5 Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: ((_col2 = 0L) or (_col5 is null and _col0 is not null and (_col3 >= _col2))) (type: boolean) - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + predicate: (((_col3 >= _col2) or (_col2 = 0L) or _col5 is not null or _col0 is null) and (_col0 is not null or (_col2 = 0L) or _col5 is not null) and (_col5 is null or (_col2 = 0L))) (type: boolean) + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: _col0 (type: string), _col1 (type: string) outputColumnNames: _col0, _col1 - Statistics: Num rows: 366 Data size: 10110 Basic stats: COMPLETE Column stats: NONE + Statistics: Num rows: 550 Data size: 15193 Basic stats: COMPLETE Column stats: NONE File Output Operator compressed: false table: diff --git ql/src/test/results/clientpositive/vectorization_5.q.out ql/src/test/results/clientpositive/vectorization_5.q.out index e0bfa727d7..69d8b324a1 100644 --- ql/src/test/results/clientpositive/vectorization_5.q.out +++ ql/src/test/results/clientpositive/vectorization_5.q.out @@ -56,7 +56,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((cboolean2 is not null and (cstring1 like '%b%')) or ((UDFToDouble(ctinyint) = cdouble) and ctimestamp2 is not null and (cstring2 like 'a'))) (type: boolean) + filterExpr: (((cstring1 like '%b%') and cboolean2 is not null) or ((UDFToDouble(ctinyint) = cdouble) and (cstring2 like 'a') and ctimestamp2 is not null)) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -65,8 +65,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: SelectColumnIsNotNull(col 11:boolean), FilterStringColLikeStringScalar(col 6:string, pattern %b%)), FilterExprAndExpr(children: FilterDoubleColEqualDoubleColumn(col 13:double, col 5:double)(children: CastLongToDouble(col 0:tinyint) -> 13:double), SelectColumnIsNotNull(col 9:timestamp), FilterStringColLikeStringScalar(col 7:string, pattern a))) - predicate: (((UDFToDouble(ctinyint) = cdouble) and ctimestamp2 is not null and (cstring2 like 'a')) or (cboolean2 is not null and (cstring1 like '%b%'))) (type: boolean) + predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: FilterStringColLikeStringScalar(col 6:string, pattern %b%), SelectColumnIsNotNull(col 11:boolean)), FilterExprAndExpr(children: FilterDoubleColEqualDoubleColumn(col 13:double, col 5:double)(children: CastLongToDouble(col 0:tinyint) -> 13:double), FilterStringColLikeStringScalar(col 7:string, pattern a), SelectColumnIsNotNull(col 9:timestamp))) + predicate: (((UDFToDouble(ctinyint) = cdouble) and (cstring2 like 'a') and ctimestamp2 is not null) or ((cstring1 like '%b%') and cboolean2 is not null)) (type: boolean) Statistics: Num rows: 9216 Data size: 2180995 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: ctinyint (type: tinyint), csmallint (type: smallint), cint (type: int) diff --git ql/src/test/results/clientpositive/vectorization_8.q.out ql/src/test/results/clientpositive/vectorization_8.q.out index 4af9888a13..af4a19a409 100644 --- ql/src/test/results/clientpositive/vectorization_8.q.out +++ ql/src/test/results/clientpositive/vectorization_8.q.out @@ -66,7 +66,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((cstring2 is not null and (UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D)) or (cfloat < -6432.0) or (cboolean1 is not null and (cdouble = 988888.0D))) (type: boolean) + filterExpr: (((UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D) and cstring2 is not null) or (cfloat < -6432.0) or ((cdouble = 988888.0D) and cboolean1 is not null)) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -75,8 +75,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: SelectColumnIsNotNull(col 7:string), FilterDoubleColLessEqualDoubleScalar(col 13:double, val 10.0)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 16.0)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: SelectColumnIsNotNull(col 10:boolean), FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0))) - predicate: ((cboolean1 is not null and (cdouble = 988888.0D)) or (cfloat < -6432.0) or (cstring2 is not null and (UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D))) (type: boolean) + predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: FilterDoubleColLessEqualDoubleScalar(col 13:double, val 10.0)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 16.0)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double), SelectColumnIsNotNull(col 7:string)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0), SelectColumnIsNotNull(col 10:boolean))) + predicate: (((UDFToDouble(ctimestamp1) <= 10.0D) and (UDFToDouble(ctimestamp2) <> 16.0D) and cstring2 is not null) or ((cdouble = 988888.0D) and cboolean1 is not null) or (cfloat < -6432.0)) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: ctimestamp1 (type: timestamp), cdouble (type: double), cboolean1 (type: boolean), cstring1 (type: string), cfloat (type: float), (- cdouble) (type: double), (-5638.15D - cdouble) (type: double), (cdouble * -257.0D) (type: double), (UDFToFloat(cint) + cfloat) (type: float), ((- cdouble) + UDFToDouble(cbigint)) (type: double), (- cdouble) (type: double), (-1.389 - cfloat) (type: float), (- cfloat) (type: float), ((-5638.15D - cdouble) + UDFToDouble((UDFToFloat(cint) + cfloat))) (type: double) @@ -279,7 +279,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((cstring2 is not null and (UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D)) or (cfloat < -6432.0) or (cboolean1 is not null and (cdouble = 988888.0D))) (type: boolean) + filterExpr: (((UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D) and cstring2 is not null) or (cfloat < -6432.0) or ((cdouble = 988888.0D) and cboolean1 is not null)) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -287,8 +287,8 @@ STAGE PLANS: Filter Vectorization: className: VectorFilterOperator native: true - predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: SelectColumnIsNotNull(col 7:string), FilterDoubleColLessEqualDoubleScalar(col 13:double, val 12.503)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 11.998)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: SelectColumnIsNotNull(col 10:boolean), FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0))) - predicate: ((cboolean1 is not null and (cdouble = 988888.0D)) or (cfloat < -6432.0) or (cstring2 is not null and (UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D))) (type: boolean) + predicateExpression: FilterExprOrExpr(children: FilterExprAndExpr(children: FilterDoubleColLessEqualDoubleScalar(col 13:double, val 12.503)(children: CastTimestampToDouble(col 8:timestamp) -> 13:double), FilterDoubleColNotEqualDoubleScalar(col 14:double, val 11.998)(children: CastTimestampToDouble(col 9:timestamp) -> 14:double), SelectColumnIsNotNull(col 7:string)), FilterDoubleColLessDoubleScalar(col 4:float, val -6432.0), FilterExprAndExpr(children: FilterDoubleColEqualDoubleScalar(col 5:double, val 988888.0), SelectColumnIsNotNull(col 10:boolean))) + predicate: (((UDFToDouble(ctimestamp1) <= 12.503D) and (UDFToDouble(ctimestamp2) <> 11.998D) and cstring2 is not null) or ((cdouble = 988888.0D) and cboolean1 is not null) or (cfloat < -6432.0)) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: ctimestamp1 (type: timestamp), cdouble (type: double), cboolean1 (type: boolean), cstring1 (type: string), cfloat (type: float), (- cdouble) (type: double), (-5638.15D - cdouble) (type: double), (cdouble * -257.0D) (type: double), (UDFToFloat(cint) + cfloat) (type: float), ((- cdouble) + UDFToDouble(cbigint)) (type: double), (- cdouble) (type: double), (-1.389 - cfloat) (type: float), (- cfloat) (type: float), ((-5638.15D - cdouble) + UDFToDouble((UDFToFloat(cint) + cfloat))) (type: double) diff --git ql/src/test/results/clientpositive/vectorized_casts.q.out ql/src/test/results/clientpositive/vectorized_casts.q.out index 1755ea4b57..ec56b64cbb 100644 --- ql/src/test/results/clientpositive/vectorized_casts.q.out +++ ql/src/test/results/clientpositive/vectorized_casts.q.out @@ -166,7 +166,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((cbigint % 250) = 0) (type: boolean) + filterExpr: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -176,7 +176,7 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: FilterLongColEqualLongScalar(col 13:bigint, val 0)(children: LongColModuloLongScalar(col 3:bigint, val 250) -> 13:bigint) - predicate: ((cbigint % 250) = 0) (type: boolean) + predicate: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 6144 Data size: 1453997 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: UDFToBoolean(ctinyint) (type: boolean), UDFToBoolean(csmallint) (type: boolean), UDFToBoolean(cint) (type: boolean), UDFToBoolean(cbigint) (type: boolean), UDFToBoolean(cfloat) (type: boolean), UDFToBoolean(cdouble) (type: boolean), cboolean1 (type: boolean), UDFToBoolean((cbigint * 0L)) (type: boolean), UDFToBoolean(ctimestamp1) (type: boolean), UDFToBoolean(cstring1) (type: boolean), UDFToInteger(ctinyint) (type: int), UDFToInteger(csmallint) (type: int), cint (type: int), UDFToInteger(cbigint) (type: int), UDFToInteger(cfloat) (type: int), UDFToInteger(cdouble) (type: int), UDFToInteger(cboolean1) (type: int), UDFToInteger(ctimestamp1) (type: int), UDFToInteger(cstring1) (type: int), UDFToInteger(substr(cstring1, 1, 1)) (type: int), UDFToByte(cfloat) (type: tinyint), UDFToShort(cfloat) (type: smallint), UDFToLong(cfloat) (type: bigint), UDFToDouble(ctinyint) (type: double), UDFToDouble(csmallint) (type: double), UDFToDouble(cint) (type: double), UDFToDouble(cbigint) (type: double), UDFToDouble(cfloat) (type: double), cdouble (type: double), UDFToDouble(cboolean1) (type: double), UDFToDouble(ctimestamp1) (type: double), UDFToDouble(cstring1) (type: double), UDFToDouble(substr(cstring1, 1, 1)) (type: double), UDFToFloat(cint) (type: float), UDFToFloat(cdouble) (type: float), CAST( ctinyint AS TIMESTAMP) (type: timestamp), CAST( csmallint AS TIMESTAMP) (type: timestamp), CAST( cint AS TIMESTAMP) (type: timestamp), CAST( cbigint AS TIMESTAMP) (type: timestamp), CAST( cfloat AS TIMESTAMP) (type: timestamp), CAST( cdouble AS TIMESTAMP) (type: timestamp), CAST( cboolean1 AS TIMESTAMP) (type: timestamp), CAST( (cbigint * 0L) AS TIMESTAMP) (type: timestamp), CAST( CAST( ctimestamp1 AS DATE) AS TIMESTAMP) (type: timestamp), ctimestamp1 (type: timestamp), CAST( cstring1 AS TIMESTAMP) (type: timestamp), CAST( substr(cstring1, 1, 1) AS TIMESTAMP) (type: timestamp), CAST( ctinyint AS STRING) (type: string), CAST( csmallint AS STRING) (type: string), CAST( cint AS STRING) (type: string), CAST( cbigint AS STRING) (type: string), CAST( cfloat AS STRING) (type: string), CAST( cdouble AS STRING) (type: string), CAST( cboolean1 AS STRING) (type: string), CAST( (cbigint * 0L) AS STRING) (type: string), CAST( ctimestamp1 AS STRING) (type: string), cstring1 (type: string), CAST( CAST( cstring1 AS CHAR(10)) AS STRING) (type: string), CAST( CAST( cstring1 AS varchar(10)) AS STRING) (type: string), UDFToFloat(UDFToInteger(cfloat)) (type: float), UDFToDouble((cint * 2)) (type: double), CAST( sin(cfloat) AS STRING) (type: string), (UDFToDouble(UDFToFloat(cint)) + UDFToDouble(cboolean1)) (type: double) diff --git ql/src/test/results/clientpositive/vectorized_math_funcs.q.out ql/src/test/results/clientpositive/vectorized_math_funcs.q.out index 0f96980026..ee92279bc3 100644 --- ql/src/test/results/clientpositive/vectorized_math_funcs.q.out +++ ql/src/test/results/clientpositive/vectorized_math_funcs.q.out @@ -120,7 +120,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: (((cbigint % 500) = 0) and (sin(cfloat) >= -1.0D)) (type: boolean) + filterExpr: (((cbigint % 500L) = 0) and (sin(cfloat) >= -1.0D)) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -129,7 +129,7 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: FilterExprAndExpr(children: FilterLongColEqualLongScalar(col 13:bigint, val 0)(children: LongColModuloLongScalar(col 3:bigint, val 500) -> 13:bigint), FilterDoubleColGreaterEqualDoubleScalar(col 14:double, val -1.0)(children: FuncSinDoubleToDouble(col 4:float) -> 14:double)) - predicate: (((cbigint % 500) = 0) and (sin(cfloat) >= -1.0D)) (type: boolean) + predicate: (((cbigint % 500L) = 0) and (sin(cfloat) >= -1.0D)) (type: boolean) Statistics: Num rows: 2048 Data size: 484665 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: cdouble (type: double), round(cdouble, 2) (type: double), floor(cdouble) (type: bigint), ceil(cdouble) (type: bigint), rand() (type: double), rand(98007) (type: double), exp(ln(cdouble)) (type: double), ln(cdouble) (type: double), ln(cfloat) (type: double), log10(cdouble) (type: double), log2(cdouble) (type: double), log2((cdouble - 15601.0D)) (type: double), log2(cfloat) (type: double), log2(cbigint) (type: double), log2(cint) (type: double), log2(csmallint) (type: double), log2(ctinyint) (type: double), log(2, cdouble) (type: double), power(log2(cdouble), 2) (type: double), power(log2(cdouble), 2) (type: double), sqrt(cdouble) (type: double), sqrt(cbigint) (type: double), bin(cbigint) (type: string), hex(cdouble) (type: string), conv(cbigint, 10, 16) (type: string), abs(cdouble) (type: double), abs(ctinyint) (type: int), (cint pmod 3) (type: int), sin(cdouble) (type: double), asin(cdouble) (type: double), cos(cdouble) (type: double), acos(cdouble) (type: double), atan(cdouble) (type: double), degrees(cdouble) (type: double), radians(cdouble) (type: double), cdouble (type: double), cbigint (type: bigint), (- cdouble) (type: double), sign(cdouble) (type: double), sign(cbigint) (type: double), cos(((- sin(log(cdouble))) + 3.14159D)) (type: double) diff --git ql/src/test/results/clientpositive/vectorized_string_funcs.q.out ql/src/test/results/clientpositive/vectorized_string_funcs.q.out index d4db85452a..3f757bcb76 100644 --- ql/src/test/results/clientpositive/vectorized_string_funcs.q.out +++ ql/src/test/results/clientpositive/vectorized_string_funcs.q.out @@ -60,10 +60,10 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: (((cbigint % 237) = 0) and (length(substr(cstring1, 1, 2)) <= 2) and (cstring1 like '%')) (type: boolean) + filterExpr: (((cbigint % 237L) = 0) and (length(substr(cstring1, 1, 2)) <= 2) and (cstring1 like '%')) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE Filter Operator - predicate: (((cbigint % 237) = 0) and (cstring1 like '%') and (length(substr(cstring1, 1, 2)) <= 2)) (type: boolean) + predicate: (((cbigint % 237L) = 0) and (cstring1 like '%') and (length(substr(cstring1, 1, 2)) <= 2)) (type: boolean) Statistics: Num rows: 1024 Data size: 242332 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: substr(cstring1, 1, 2) (type: string), substr(cstring1, 2) (type: string), lower(cstring1) (type: string), upper(cstring1) (type: string), upper(cstring1) (type: string), length(cstring1) (type: int), trim(cstring1) (type: string), ltrim(cstring1) (type: string), rtrim(cstring1) (type: string), concat(cstring1, cstring2) (type: string), concat('>', cstring1) (type: string), concat(cstring1, '<') (type: string), concat(substr(cstring1, 1, 2), substr(cstring2, 1, 2)) (type: string) diff --git ql/src/test/results/clientpositive/vectorized_timestamp_ints_casts.q.out ql/src/test/results/clientpositive/vectorized_timestamp_ints_casts.q.out index 8204067dc9..1bc64271f6 100644 --- ql/src/test/results/clientpositive/vectorized_timestamp_ints_casts.q.out +++ ql/src/test/results/clientpositive/vectorized_timestamp_ints_casts.q.out @@ -52,7 +52,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((cbigint % 250) = 0) (type: boolean) + filterExpr: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -61,7 +61,7 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: FilterLongColEqualLongScalar(col 13:bigint, val 0)(children: LongColModuloLongScalar(col 3:bigint, val 250) -> 13:bigint) - predicate: ((cbigint % 250) = 0) (type: boolean) + predicate: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 6144 Data size: 1453997 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: CAST( ctinyint AS TIMESTAMP) (type: timestamp), CAST( csmallint AS TIMESTAMP) (type: timestamp), CAST( cint AS TIMESTAMP) (type: timestamp), CAST( cbigint AS TIMESTAMP) (type: timestamp), CAST( cfloat AS TIMESTAMP) (type: timestamp), CAST( cdouble AS TIMESTAMP) (type: timestamp), CAST( cboolean1 AS TIMESTAMP) (type: timestamp), CAST( (cbigint * 0L) AS TIMESTAMP) (type: timestamp), ctimestamp1 (type: timestamp), CAST( cstring1 AS TIMESTAMP) (type: timestamp), CAST( substr(cstring1, 1, 1) AS TIMESTAMP) (type: timestamp) @@ -217,7 +217,7 @@ STAGE PLANS: Map Operator Tree: TableScan alias: alltypesorc - filterExpr: ((cbigint % 250) = 0) (type: boolean) + filterExpr: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 12288 Data size: 2907994 Basic stats: COMPLETE Column stats: NONE TableScan Vectorization: native: true @@ -226,7 +226,7 @@ STAGE PLANS: className: VectorFilterOperator native: true predicateExpression: FilterLongColEqualLongScalar(col 13:bigint, val 0)(children: LongColModuloLongScalar(col 3:bigint, val 250) -> 13:bigint) - predicate: ((cbigint % 250) = 0) (type: boolean) + predicate: ((cbigint % 250L) = 0) (type: boolean) Statistics: Num rows: 6144 Data size: 1453997 Basic stats: COMPLETE Column stats: NONE Select Operator expressions: CAST( ctinyint AS TIMESTAMP) (type: timestamp), CAST( csmallint AS TIMESTAMP) (type: timestamp), CAST( cint AS TIMESTAMP) (type: timestamp), CAST( cbigint AS TIMESTAMP) (type: timestamp), CAST( cfloat AS TIMESTAMP) (type: timestamp), CAST( cdouble AS TIMESTAMP) (type: timestamp), CAST( cboolean1 AS TIMESTAMP) (type: timestamp), CAST( (cbigint * 0L) AS TIMESTAMP) (type: timestamp), ctimestamp1 (type: timestamp), CAST( cstring1 AS TIMESTAMP) (type: timestamp), CAST( substr(cstring1, 1, 1) AS TIMESTAMP) (type: timestamp)