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Posted to issues@spark.apache.org by "Wenchen Fan (Jira)" <ji...@apache.org> on 2022/10/24 09:05:00 UTC
[jira] [Assigned] (SPARK-34265) Instrument Python UDF execution using SQL Metrics
[ https://issues.apache.org/jira/browse/SPARK-34265?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Wenchen Fan reassigned SPARK-34265:
-----------------------------------
Assignee: Luca Canali
> 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
> 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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