[
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.
>
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
