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https://issues.apache.org/jira/browse/HIVE-25335?focusedWorklogId=771137&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-771137
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ASF GitHub Bot logged work on HIVE-25335:
-----------------------------------------

                Author: ASF GitHub Bot
            Created on: 17/May/22 04:25
            Start Date: 17/May/22 04:25
    Worklog Time Spent: 10m 
      Work Description: zhengchenyu commented on PR #3292:
URL: https://github.com/apache/hive/pull/3292#issuecomment-1128396054

   @zabetak UT in my environment is right. Seems error happen in post stage.
   Because I change the logical of maxDataSize, so some explain output may 
changed. 
   Maybe many explain output should repair, so I need setup a jenkins pipeline. 
Is there any introducation about hive jenkins pipeline. Many problem happen 
when I setup the pipeline in my dev enviromnent.
   




Issue Time Tracking
-------------------

    Worklog Id:     (was: 771137)
    Time Spent: 2h 50m  (was: 2h 40m)

> Unreasonable setting reduce number, when join big size table(but small row 
> count) and small size table
> ------------------------------------------------------------------------------------------------------
>
>                 Key: HIVE-25335
>                 URL: https://issues.apache.org/jira/browse/HIVE-25335
>             Project: Hive
>          Issue Type: Improvement
>            Reporter: zhengchenyu
>            Assignee: zhengchenyu
>            Priority: Major
>              Labels: pull-request-available
>         Attachments: HIVE-25335.001.patch
>
>          Time Spent: 2h 50m
>  Remaining Estimate: 0h
>
> I found an application which is slow in our cluster, because the proccess 
> bytes of one reduce is very huge, but only two reduce. 
> when I debug, I found the reason. Because in this sql, one big size table 
> (about 30G) with few row count(about 3.5M), another small size table (about 
> 100M) have more row count (about 3.6M). So JoinStatsRule.process only use 
> 100M to estimate reducer's number. But we need to  process 30G byte in fact.  



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