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https://issues.apache.org/jira/browse/SPARK-1498?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Kay Ousterhout resolved SPARK-1498.
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Resolution: Fixed
> Spark can hang if pyspark tasks fail
> ------------------------------------
>
> Key: SPARK-1498
> URL: https://issues.apache.org/jira/browse/SPARK-1498
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 0.9.0, 0.9.1, 0.9.2
> Reporter: Kay Ousterhout
> Fix For: 1.0.0
>
>
> In pyspark, when some kinds of jobs fail, Spark hangs rather than returning
> an error. This is partially a scheduler problem -- the scheduler sometimes
> thinks failed tasks succeed, even though they have a stack trace and
> exception.
> You can reproduce this problem with:
> ardd = sc.parallelize([(1,2,3), (4,5,6)])
> brdd = sc.parallelize([(1,2,6), (4,5,9)])
> ardd.join(brdd).count()
> The last line will run forever (the problem in this code is that the RDD
> entries have 3 values instead of the expected 2). I haven't verified if this
> is a problem for 1.0 as well as 0.9.
> Thanks to Shivaram for helping diagnose this issue!
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