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Posted to issues@spark.apache.org by "Xinrong Meng (Jira)" <ji...@apache.org> on 2023/01/04 07:22:00 UTC

[jira] [Updated] (SPARK-40307) Introduce Arrow-optimized Python UDFs

     [ https://issues.apache.org/jira/browse/SPARK-40307?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Xinrong Meng updated SPARK-40307:
---------------------------------
    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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