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From "Sergey Shelukhin (JIRA)" <>
Subject [jira] [Created] (HIVE-11794) GBY vectorization appears to process COMPLETE reduce-side GBY incorrectly
Date Fri, 11 Sep 2015 00:46:46 GMT
Sergey Shelukhin created HIVE-11794:

             Summary: GBY vectorization appears to process COMPLETE reduce-side GBY incorrectly
                 Key: HIVE-11794
             Project: Hive
          Issue Type: Bug
            Reporter: Sergey Shelukhin
            Assignee: Matt McCline

The code in Vectorizer is as such:
    boolean isMergePartial = (desc.getMode() != GroupByDesc.Mode.HASH);
then, if it's reduce side:
    if (isMergePartial) {
        // Reduce Merge-Partial GROUP BY.
        // A merge-partial GROUP BY is fed by grouping by keys from reduce-shuffle.  It is
        // first (or root) operator for its reduce task.
      } else {
        // Reduce Hash GROUP BY or global aggregation.

In fact, the comments are missing the COMPLETE mode. Both from the comment:
 COMPLETE: complete 1-phase aggregation: iterate, terminate
HASH: For non-distinct the same as PARTIAL1 but use hash-table-based aggregation
PARTIAL1: partial aggregation - first phase: iterate, terminatePartial

and from the explain plan like this (the query has multiple stages of aggregations over a
union; the mapper does a partial hash aggregation for each side of the union, which is then
followed by mergepartial, and 2nd stage as complete):
Reduce Operator Tree:
  Group By Operator
    keys: KEY._col0 (type: int), KEY._col1 (type: int), KEY._col2 (type: int), KEY._col3 (type:
int), KEY._col4 (type: int), KEY._col5 (type: bigint), KEY._col6 (type: bigint), KEY._col7
(type: bigint), KEY._col8 (type: bigint), KEY._col9 (type: bigint), KEY._col10 (type: bigint),
KEY._col11 (type: bigint), KEY._col12 (type: bigint)
    mode: mergepartial
    outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9,
_col10, _col11, _col12
    Group By Operator
      aggregations: sum(_col5), sum(_col6), sum(_col7), sum(_col8), sum(_col9), sum(_col10),
sum(_col11), sum(_col12)
      keys: _col0 (type: int), _col1 (type: int), _col2 (type: int), _col3 (type: int), _col4
(type: int)
      mode: complete
      outputColumnNames: _col0, _col1, _col2, _col3, _col4, _col5, _col6, _col7, _col8, _col9,
_col10, _col11, _col12

it seems like COMPLETE is actually the global aggregation, and HASH isn't (or may not be).
So, it seems like reduce-side COMPLETE should be handled on the else-path of the above if.
For map-side, it doesn't check mode at all as far as I can see.
Not sure if additional code changes are necessary after that, it may just work.

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