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Posted to issues@spark.apache.org by "angerszhu (Jira)" <ji...@apache.org> on 2020/09/09 09:59:00 UTC
[jira] [Updated] (SPARK-32830) Optimize Skewed
BroadcastNestedLoopJoin with AE
[ https://issues.apache.org/jira/browse/SPARK-32830?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
angerszhu updated SPARK-32830:
------------------------------
Description:
For BroadcastNestedLoopJoin, we will broadcast boradcast-side child to all executor and use stream side partition's data traversal broadcast-side data one-by-one.
We have meet some case that stream side data skew and all success task wait for skewed partition to finish.
We know that the execution time increases exponentially with the amount of partition's data.
If skewd with 100x, skewed partition's data will execute 100x than non-skewed part.
It is a bottleneck， with AE, we can avoid this by split skewed part's data to make it more balanced.
> Optimize Skewed BroadcastNestedLoopJoin with AE
> -----------------------------------------------
>
> Key: SPARK-32830
> URL: https://issues.apache.org/jira/browse/SPARK-32830
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 3.1.0
> Reporter: angerszhu
> Priority: Major
>
> For BroadcastNestedLoopJoin, we will broadcast boradcast-side child to all executor and use stream side partition's data traversal broadcast-side data one-by-one.
> We have meet some case that stream side data skew and all success task wait for skewed partition to finish.
> We know that the execution time increases exponentially with the amount of partition's data.
> If skewd with 100x, skewed partition's data will execute 100x than non-skewed part.
> It is a bottleneck， with AE, we can avoid this by split skewed part's data to make it more balanced.
>
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