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https://issues.apache.org/jira/browse/SPARK-50752?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated SPARK-50752:
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Labels: pull-request-available (was: )
> Introduce configs for Python UDF execution
> ------------------------------------------
>
> Key: SPARK-50752
> URL: https://issues.apache.org/jira/browse/SPARK-50752
> Project: Spark
> Issue Type: Improvement
> Components: PySpark, SQL
> Affects Versions: 4.0.0
> Reporter: Jungtaek Lim
> Priority: Major
> Labels: pull-request-available
>
> Unlike Pandas UDF, Python UDF does not have configurations to tune for
> performance. It doesn't mean we do not batch the input/output with Python
> UDF, it means the batch size is hard-coded.
> There are configurations which are available in Pandas UDF and mostly also
> relevant to Python UDF:
> * batch size (executor <-> python worker)
> * buffer size to write to channel
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