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From "Ashutosh Chauhan (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-9025) join38.q (without map join) produces incorrect result when testing with multiple reducers
Date Wed, 10 Dec 2014 21:17:14 GMT

    [ https://issues.apache.org/jira/browse/HIVE-9025?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14241753#comment-14241753
] 

Ashutosh Chauhan commented on HIVE-9025:
----------------------------------------

+1
[~vikram.dixit] it will be good to have this in 0.14 branch as well, since this is a correctness
issue.

> join38.q (without map join) produces incorrect result when testing with multiple reducers
> -----------------------------------------------------------------------------------------
>
>                 Key: HIVE-9025
>                 URL: https://issues.apache.org/jira/browse/HIVE-9025
>             Project: Hive
>          Issue Type: Bug
>          Components: Logical Optimizer
>    Affects Versions: 0.14.0
>            Reporter: Chao
>            Assignee: Ted Xu
>            Priority: Blocker
>         Attachments: HIVE-9025.patch
>
>
> I have this query from a modified version of {{join38.q}}, which does NOT use map join:
> {code}
> FROM src a JOIN tmp b ON (a.key = b.col11)
> SELECT a.value, b.col5, count(1) as count
> where b.col11 = 111
> group by a.value, b.col5;
> {code}
> If I set {{mapred.reduce.tasks}} to 1, the result is correct. But, if I set it to be
a larger number (3 for instance), then result will be 
> {noformat}
> val_111	105	1
> {noformat}
> which is wrong.
> I think the issue is that, for this case, ConstantPropagationProcFactory will overwrite
the partition cols for the reduce sink desc, with an empty list. Then, later on in ReduceSinkOperator#computeHashCode,
since partitionEval is length 0, it will use an random number as hashcode, for each separate
row. As result, rows with same key will be distributed to different reducers, and hence leads
to incorrect result.



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