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From "Xuefu Zhang (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (HIVE-15683) Measure performance impact on group by by HIVE-15580
Date Wed, 08 Feb 2017 04:23:41 GMT

     [ https://issues.apache.org/jira/browse/HIVE-15683?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Xuefu Zhang updated HIVE-15683:
-------------------------------
    Status: Patch Available  (was: Open)

> Measure performance impact on group by by HIVE-15580
> ----------------------------------------------------
>
>                 Key: HIVE-15683
>                 URL: https://issues.apache.org/jira/browse/HIVE-15683
>             Project: Hive
>          Issue Type: Improvement
>          Components: Spark
>    Affects Versions: 2.2.0
>            Reporter: Xuefu Zhang
>            Assignee: Xuefu Zhang
>         Attachments: HIVE-15683.patch
>
>
> HIVE-15580 changed the way the data is shuffled for order by: instead of using Spark's
groupByKey to shuffle data, Hive on Spark now uses repartitionAndSortWithinPartitions(), which
generates (key, value) pairs instead of original (key, value iterator). This might have some
performance implications, but it's needed to get rid of unbound memory usage by {{groupByKey}}.
> Here we'd like to compare group by performance with or w/o HIVE-15580. If the impact
is significant, we can provide a configuration that allows user to switch back to the original
way of shuffling.
> This work should be ideally done after HIVE-15682 as the optimization there should help
the performance here as well. 



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