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From "Rui Li (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-13293) Query occurs performance degradation after enabling parallel order by for Hive on Spark
Date Wed, 11 May 2016 16:12:12 GMT

    [ https://issues.apache.org/jira/browse/HIVE-13293?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15280347#comment-15280347
] 

Rui Li commented on HIVE-13293:
-------------------------------

Hi [~xuefuz], yeah order by is mostly at the end of stages. But that doesn't mean the amount
of data is small - that's why we need parallel order by. During our benchmark, we hit OOM
for several cases, which is due to some bug in Spark 1.6.0. So I thought using memory level
cache may make it even worse.

To your second question, we unpersist cached RDDs at the end of each job. You can refer to
{{RemoteDriver#JobWrapper}} for that.

> Query occurs performance degradation after enabling parallel order by for Hive on Spark
> ---------------------------------------------------------------------------------------
>
>                 Key: HIVE-13293
>                 URL: https://issues.apache.org/jira/browse/HIVE-13293
>             Project: Hive
>          Issue Type: Bug
>          Components: Spark
>    Affects Versions: 2.0.0
>            Reporter: Lifeng Wang
>            Assignee: Rui Li
>         Attachments: HIVE-13293.1.patch, HIVE-13293.1.patch
>
>
> I use TPCx-BB to do some performance test on Hive on Spark engine. And found query 10
has performance degradation when enabling parallel order by.
> It seems that sampling cost much time before running the real query.



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