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https://issues.apache.org/jira/browse/SPARK-40307?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Xinrong Meng updated SPARK-40307:
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Summary: Introduce Arrow-optimized Python UDFs (was: Optimize
(De)Serialization of Python UDFs by Arrow)
> Introduce Arrow-optimized Python UDFs
> -------------------------------------
>
> Key: SPARK-40307
> URL: https://issues.apache.org/jira/browse/SPARK-40307
> Project: Spark
> Issue Type: Umbrella
> Components: PySpark
> Affects Versions: 3.4.0
> Reporter: Xinrong Meng
> Priority: Major
>
> Python user-defined function (UDF) enables users to run arbitrary code
> against PySpark columns. It uses Pickle for (de)serialization and executes
> row by row.
> One major performance bottleneck of Python UDFs is (de)serialization, that
> is, the data interchanging between the worker JVM and the spawned Python
> subprocess which actually executes the UDF. We should seek an alternative to
> handle the (de)serialization: Arrow, which is used in the (de)serialization
> of Pandas UDF already.
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