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https://issues.apache.org/jira/browse/SPARK-30713?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Dongjoon Hyun updated SPARK-30713:
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Affects Version/s: (was: 3.0.0)
3.1.0
> Respect mapOutputSize in memory in adaptive execution
> -----------------------------------------------------
>
> Key: SPARK-30713
> URL: https://issues.apache.org/jira/browse/SPARK-30713
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 3.1.0
> Reporter: liupengcheng
> Priority: Major
>
> Currently, Spark adaptive execution use the MapOutputStatistics information
> to adjust the plan dynamically, but this MapOutputSize does not respect the
> compression factor. So there are cases that the original SparkPlan is
> `SortMergeJoin`, but the Plan after adaptive adjustment was changed to
> `BroadcastHashJoin`, but this `BroadcastHashJoin` might causing OOMs due to
> inaccurate estimation.
>
> Also, if the shuffle implementation is local shuffle(intel Spark-Adaptive
> execution impl), then in some cases, it will cause `Too large Frame`
> exception.
>
> So I propose to respect the compression factor in adaptive execution, or use
> `dataSize` metrics in `ShuffleExchangeExec` in adaptive execution.
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