[jira] [Commented] (SPARK-4194) Exceptions thrown during SparkContext or SparkEnv construction might lead to resource leaks or corrupted global state

["Josh Rosen (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-4194?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14193732#comment-14193732 ] 

Josh Rosen commented on SPARK-4194:
-----------------------------------

I've marked this a blocker of SPARK-4180, an issue that tries to add exceptions when users try to create multiple active SparkContexts in the same JVM.  PySpark already guards against this, but earlier versions of its error-checking code ran into issues where users would fail their initial attempt to create a SparkContext and then be unable to create new ones because we didn't clear the {{activeSparkContext}} variable after the constructor threw an exception.

To fix this, we need to wrap the constructor code in a {{try}} block. 

> Exceptions thrown during SparkContext or SparkEnv construction might lead to resource leaks or corrupted global state
> ---------------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-4194
>                 URL: https://issues.apache.org/jira/browse/SPARK-4194
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>            Reporter: Josh Rosen
>            Priority: Critical
>
> The SparkContext and SparkEnv constructors instantiate a bunch of objects that may need to be cleaned up after they're no longer needed.  If an exception is thrown during SparkContext or SparkEnv construction (e.g. due to a bad configuration setting), then objects created earlier in the constructor may not be properly cleaned up.
> This is unlikely to cause problems for batch jobs submitted through {{spark-submit}}, since failure to construct SparkContext will probably cause the JVM to exit, but it is a potentially serious issue in interactive environments where a user might attempt to create SparkContext with some configuration, fail due to an error, and re-attempt the creation with new settings.  In this case, resources from the previous creation attempt might not have been cleaned up and could lead to confusing errors (especially if the old, leaked resources share global state with the new SparkContext).



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