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  1. Hive
  2. HIVE-8699 Enable support for common map join [Spark Branch]
  3. HIVE-8700

Replace ReduceSink to HashTableSink (or equi.) for small tables [Spark Branch]

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Details

    • Sub-task
    • Status: Resolved
    • Major
    • Resolution: Fixed
    • None
    • 1.1.0
    • Spark
    • None

    Description

      With HIVE-8616 enabled, the new plan has ReduceSinkOperator for the small tables. For example, the follow represents the operator plan for the small table dec1 derived from query

      explain select /*+ MAPJOIN(dec)*/ * from dec join dec1 on dec.value=dec1.d;
              Map 2 
                  Map Operator Tree:
                      TableScan
                        alias: dec1
                        Statistics: Num rows: 0 Data size: 107 Basic stats: PARTIAL Column stats: NONE
                        Filter Operator
                          predicate: d is not null (type: boolean)
                          Statistics: Num rows: 0 Data size: 0 Basic stats: NONE Column stats: NONE
                          Reduce Output Operator
                            key expressions: d (type: decimal(5,2))
                            sort order: +
                            Map-reduce partition columns: d (type: decimal(5,2))
                            Statistics: Num rows: 0 Data size: 0 Basic stats: NONE Column stats: NONE
                            value expressions: i (type: int)
      
      

      With the new design for broadcasting small tables, we need to convert the ReduceSinkOperator with HashTableSinkOperator or equivalent in the new plan.

      Attachments

        1. HIVE-8700.2-spark.patch
          5 kB
          Suhas Satish
        2. HIVE-8700.3-spark.patch
          4 kB
          Suhas Satish
        3. HIVE-8700.patch
          26 kB
          Suhas Satish
        4. HIVE-8700-spark.patch
          16 kB
          Suhas Satish

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          People

            ssatish Suhas Satish
            xuefuz Xuefu Zhang
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            Dates

              Created:
              Updated:
              Resolved: