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https://issues.apache.org/jira/browse/SPARK-30306?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Apache Spark reassigned SPARK-30306:
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Assignee: Apache Spark
> Instrument Python UDF execution time and metrics using Spark Metrics system
> ---------------------------------------------------------------------------
>
> Key: SPARK-30306
> URL: https://issues.apache.org/jira/browse/SPARK-30306
> Project: Spark
> Issue Type: Improvement
> Components: PySpark, Spark Core
> Affects Versions: 3.1.0
> Reporter: Luca Canali
> Assignee: Apache Spark
> Priority: Minor
> Attachments: PandasUDF_Time_Instrumentation_Annotated.png
>
>
> This proposes to extend Spark instrumentation to add metrics aimed at
> understanding the performance of Python code called by Spark, via UDF, Pandas
> UDF or with MapPartittions. Relevant performance counters are exposed using
> the Spark Metrics System (based on the Dropwizard library). This allows to
> easily consume the metrics produced by executors, for example using a
> performance dashboard. See also the attached screenshot.
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