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https://issues.apache.org/jira/browse/SPARK-27992?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Bryan Cutler resolved SPARK-27992.
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Resolution: Fixed
Fix Version/s: 3.0.0
Issue resolved by pull request 24834
[https://github.com/apache/spark/pull/24834]
> PySpark socket server should sync with JVM connection thread future
> -------------------------------------------------------------------
>
> Key: SPARK-27992
> URL: https://issues.apache.org/jira/browse/SPARK-27992
> Project: Spark
> Issue Type: Improvement
> Components: PySpark
> Affects Versions: 3.0.0
> Reporter: Bryan Cutler
> Assignee: Bryan Cutler
> Priority: Major
> Fix For: 3.0.0
>
>
> Both SPARK-27805 and SPARK-27548 identified an issue that errors in a Spark
> job are not propagated to Python. This is because toLocalIterator() and
> toPandas() with Arrow enabled run Spark jobs asynchronously in a background
> thread, after creating the socket connection info. The fix for these was to
> catch a SparkException if the job errored and then send the exception through
> the pyspark serializer.
> A better fix would be to allow Python to await on the serving thread future
> and join the thread. That way if the serving thread throws an exception, it
> will be propagated on the call to awaitResult.
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