[HIVE-7991] Incorrect calculation of number of rows in JoinStatsRule.process results in overflow

• Type: Sub-task
• Status: Closed
• Priority: Minor
• Resolution: Fixed
• Affects Version/s: 0.13.1
• Fix Version/s: 0.14.0
• Component/s: Statistics
• Assignee: Prasanth Jayachandran Assign to me
• Reporter: Mostafa Mokhtar
• Created: 05/Sep/14 01:16
• Updated: 13/Nov/14 19:43
• Resolved: 07/Sep/14 20:20

Description

This loop results in adding the parent twice incase of a 3 way join of store_sales x date_dim x store

         for (int pos = 0; pos < parents.size(); pos++) {
            ReduceSinkOperator parent = (ReduceSinkOperator) jop.getParentOperators().get(pos);

            Statistics parentStats = parent.getStatistics();
            List<ExprNodeDesc> keyExprs = parent.getConf().getKeyCols();

            // Parent RS may have column statistics from multiple parents.
            // Populate table alias to row count map, this will be used later to
            // scale down/up column statistics based on new row count
            // NOTE: JOIN with UNION as parent of RS will not have table alias
            // propagated properly. UNION operator does not propagate the table
            // alias of subqueries properly to expression nodes. Hence union20.q
            // will have wrong number of rows.
            Set<String> tableAliases = StatsUtils.getAllTableAlias(parent.getColumnExprMap());
            for (String tabAlias : tableAliases) {
              rowCountParents.put(tabAlias, parentStats.getNumRows());
            }

In the first join we have rowCountParents with

{store_sales=120464862, date_dim=36524}

which is correct.
For the second join result rowCountParents ends up with

{store=212, store_sales=120464862, date_dim=120464862}

where it should be

{store=212, store_sales=120464862, date_dim=36524}

.
The result of this is that computeNewRowCount ends up multiplying row count of store_sales x store_sales which makes the number of rows really high and eventually over flow.

Plan snippet :

   Map 1
            Map Operator Tree:
                TableScan
                  alias: store_sales
                  filterExpr: (((ss_sold_date_sk is not null and ss_store_sk is not null) and ss_item_sk is not null) and ss_sold_date BETWEEN '1999-06-01' AND '2000-05-31') (type: boolean)
                  Statistics: Num rows: 110339135 Data size: 4817453454 Basic stats: COMPLETE Column stats: COMPLETE
                  Filter Operator
                    predicate: ((ss_sold_date_sk is not null and ss_store_sk is not null) and ss_item_sk is not null) (type: boolean)
                    Statistics: Num rows: 107740258 Data size: 2124353556 Basic stats: COMPLETE Column stats: COMPLETE
                    Map Join Operator
                      condition map:
                           Inner Join 0 to 1
                      condition expressions:
                        0 {ss_sold_date_sk} {ss_item_sk} {ss_store_sk} {ss_quantity} {ss_sales_price} {ss_sold_date}
                        1 {d_date_sk} {d_month_seq} {d_year} {d_moy} {d_qoy}
                      keys:
                        0 ss_sold_date_sk (type: int)
                        1 d_date_sk (type: int)
                      outputColumnNames: _col0, _col2, _col7, _col10, _col13, _col23, _col27, _col30, _col33, _col35, _col37
                      input vertices:
                        1 Map 6
                      Statistics: Num rows: 120464862 Data size: 26984129088 Basic stats: COMPLETE Column stats: COMPLETE
                      Map Join Operator
                        condition map:
                             Inner Join 0 to 1
                        condition expressions:
                          0 {_col0} {_col2} {_col7} {_col10} {_col13} {_col23} {_col27} {_col30} {_col33} {_col35} {_col37}
                          1 {s_store_sk} {s_store_id}
                        keys:
                          0 _col7 (type: int)
                          1 s_store_sk (type: int)
                        outputColumnNames: _col0, _col2, _col7, _col10, _col13, _col23, _col27, _col30, _col33, _col35, _col37, _col58, _col59
                        input vertices:
                          1 Map 5
                        Statistics: Num rows: 17886616227069518 Data size: 5866810122478801920 Basic stats: COMPLETE Column stats: COMPLETE
                        Map Join Operator
                          condition map:
                               Inner Join 0 to 1
                          condition expressions:
                            0 {_col0} {_col2} {_col7} {_col10} {_col13} {_col23} {_col27} {_col30} {_col33} {_col35} {_col37} {_col58} {_col59}
                            1 {i_item_sk} {i_brand} {i_class} {i_category} {i_product_name}
                          keys:
                            0 _col2 (type: int)
                            1 i_item_sk (type: int)
                          outputColumnNames: _col0, _col2, _col7, _col10, _col13, _col23, _col27, _col30, _col33, _col35, _col37, _col58, _col59, _col90, _col98, _col100, _col102, _col111
                          input vertices:
                            1 Map 7
                          Statistics: Num rows: -9223372036854775808 Data size: 0 Basic stats: NONE Column stats: COMPLETE
                          Filter Operator
                            predicate: (((((_col0 = _col27) and (_col2 = _col90)) and (_col7 = _col58)) and _col30 BETWEEN 1193 AND 1204) and _col23 BETWEEN '1999-06-01' AND '2000-05-31') (type: boolean)
                            Statistics: Num rows: -9223372036854775808 Data size: 0 Basic stats: NONE Column stats: COMPLETE
                            Select Operator
                              expressions: _col102 (type: string), _col100 (type: string), _col98 (type: string), _col111 (type: string), _col33 (type: int), _col37 (type: int), _col35 (type: int), _col59 (type: string), _col13 (type: float), _col10 (type: int)
                              outputColumnNames: _col102, _col100, _col98, _col111, _col33, _col37, _col35, _col59, _col13, _col10
                              Statistics: Num rows: -9223372036854775808 Data size: 0 Basic stats: NONE Column stats: COMPLETE
                              Group By Operator
                                aggregations: sum(COALESCE((_col13 * _col10),0))
                                keys: _col102 (type: string), _col100 (type: string), _col98 (type: string), _col111 (type: string), _col33 (type: int), _col37 (type: int), _col35 (type: int), _col59 (type: string), '0' (type: string)
                                mode: hash
                                outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9
                                Statistics: Num rows: -9223372036854775808 Data size: 0 Basic stats: NONE Column stats: COMPLETE
                                Reduce Output Operator
                                  key expressions: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string), _col8 (type: string)
                                  sort order: +++++++++
                                  Map-reduce partition columns: _col0 (type: string), _col1 (type: string), _col2 (type: string), _col3 (type: string), _col4 (type: int), _col5 (type: int), _col6 (type: int), _col7 (type: string), _col8 (type: string)
                                  Statistics: Num rows: -9223372036854775808 Data size: 0 Basic stats: NONE Column stats: COMPLETE
                                  value expressions: _col9 (type: double)