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Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2021/10/10 02:31:00 UTC
[jira] [Commented] (SPARK-36967) Report accurate block size
threshold per reduce task
[ https://issues.apache.org/jira/browse/SPARK-36967?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17426737#comment-17426737 ]
Apache Spark commented on SPARK-36967:
--------------------------------------
User 'wankunde' has created a pull request for this issue:
https://github.com/apache/spark/pull/34234
> Report accurate block size threshold per reduce task
> ----------------------------------------------------
>
> Key: SPARK-36967
> URL: https://issues.apache.org/jira/browse/SPARK-36967
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 3.3.0
> Reporter: Wan Kun
> Priority: Major
> Attachments: map_status.png, map_status2.png
>
>
> Now map task will report accurate shuffle block size if the block size is greater than "spark.shuffle.accurateBlockThreshold"( 100M by default ). But if there are a large number of map tasks and the shuffle block sizes of these tasks are smaller than "spark.shuffle.accurateBlockThreshold", there may be unrecognized data skew.
> For example, there are 10000 map task and 10000 reduce task, and each map task create 50M shuffle blocks for reduce 0, and 10K shuffle blocks for the left reduce tasks, reduce 0 is data skew, but the stat of this plan do not have this information.
> !map_status2.png!
> I think we need to judge if a shuffle block is huge and need to be accurate reported while running.
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