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https://issues.apache.org/jira/browse/SPARK-28128?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-28128.
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Resolution: Fixed
Fix Version/s: 3.0.0
Issue resolved by pull request 24926
[https://github.com/apache/spark/pull/24926]
> Pandas Grouped UDFs should skip over empty partitions
> -----------------------------------------------------
>
> Key: SPARK-28128
> URL: https://issues.apache.org/jira/browse/SPARK-28128
> Project: Spark
> Issue Type: Improvement
> Components: PySpark, SQL
> Affects Versions: 2.4.3
> Reporter: Bryan Cutler
> Assignee: Bryan Cutler
> Priority: Major
> Fix For: 3.0.0
>
>
> When running FlatMapGroupsInPandasExec or AggregateInPandasExec the shuffle
> uses a default number of partitions of 200 in "spark.sql.shuffle.partitions".
> If the data is small, e.g. in testing, many of the partitions will be empty
> but are treated just the same. For example, ArrowPythonRunner.compute is
> called and starts a number of threads that do nothing since there is no
> iteration. These computations could be skipped for empty partitions, which
> will save time overall.
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