[jira] [Resolved] (SPARK-27992) PySpark socket server should sync with JVM connection thread future

["Bryan Cutler (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-27992?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Bryan Cutler resolved SPARK-27992.
----------------------------------
       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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