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Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2022/10/27 01:56:00 UTC

[jira] [Commented] (SPARK-34265) Instrument Python UDF execution using SQL Metrics

    [ https://issues.apache.org/jira/browse/SPARK-34265?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17624810#comment-17624810 ] 

Apache Spark commented on SPARK-34265:
--------------------------------------

User 'HyukjinKwon' has created a pull request for this issue:
https://github.com/apache/spark/pull/38407

> Instrument Python UDF execution using SQL Metrics
> -------------------------------------------------
>
>                 Key: SPARK-34265
>                 URL: https://issues.apache.org/jira/browse/SPARK-34265
>             Project: Spark
>          Issue Type: Improvement
>          Components: PySpark, SQL
>    Affects Versions: 3.3.0
>            Reporter: Luca Canali
>            Assignee: Luca Canali
>            Priority: Minor
>             Fix For: 3.4.0
>
>         Attachments: PandasUDF_ArrowEvalPython_Metrics.png, PythonSQLMetrics_Jira_Picture.png, proposed_Python_SQLmetrics_v20210128.png
>
>
> This proposes to add SQLMetrics instrumentation for Python UDF. 
> This is aimed at improving monitoring and performance troubleshooting of Python UDFs, Pandas UDF, including also the use of MapPartittion, and MapInArrow.
> The introduced metrics are exposed to the end users via the metrics system and are visible through the WebUI interface, in the SQL/DataFrame tab for execution steps related to Python UDF execution. See also the attached screenshots.
> This intrumentation is lightweight and can be used in production and for monitoring. It is complementary to the Python/Pandas UDF Profiler introduced in Spark 3.3 [https://spark.apache.org/docs/latest/api/python/development/debugging.html#python-pandas-udf]



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