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Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2025/11/27 04:15:00 UTC

[jira] [Resolved] (SPARK-54223) Add task context and data metrics to Python runner logs

     [ https://issues.apache.org/jira/browse/SPARK-54223?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-54223.
----------------------------------
    Fix Version/s: 4.2.0
       Resolution: Fixed

Issue resolved by pull request 52931
[https://github.com/apache/spark/pull/52931]

> Add task context and data metrics to Python runner logs
> -------------------------------------------------------
>
>                 Key: SPARK-54223
>                 URL: https://issues.apache.org/jira/browse/SPARK-54223
>             Project: Spark
>          Issue Type: Improvement
>          Components: Spark Core
>    Affects Versions: 3.5.1, 4.0.1
>            Reporter: Nishanth
>            Assignee: Nishanth
>            Priority: Major
>              Labels: pull-request-available
>             Fix For: 4.2.0
>
>
> Currently, log messages in PythonRunner do not include Spark Task Context information such as the Task ID or Partition ID.
> Additionally, the logs lack useful execution metrics (e.g., number of records processed, data size), which makes it difficult to correlate Python process behavior with specific Spark tasks.
> When debugging UDF performance issues, hangs, or data skew, it’s challenging to identify which task or dataset portion caused the issue.



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