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https://issues.apache.org/jira/browse/SPARK-3141?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Patrick Wendell resolved SPARK-3141.
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Resolution: Fixed
Fix Version/s: 1.1.0
Issue resolved by pull request 2045
[https://github.com/apache/spark/pull/2045]
> sortByKey() break take()
> ------------------------
>
> Key: SPARK-3141
> URL: https://issues.apache.org/jira/browse/SPARK-3141
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 1.1.0
> Reporter: Davies Liu
> Assignee: Davies Liu
> Priority: Blocker
> Fix For: 1.1.0
>
> Original Estimate: 2h
> Remaining Estimate: 2h
>
> https://github.com/apache/spark/pull/1898/files#r16449470
> I think there might be two unintended side effects of this change. This code
> used to work in pyspark:
> sc.parallelize([5,3,4,2,1]).map(lambda x: (x,x)).sortByKey().take(1)
> Now it failswith the error:
> File "<...>/spark/python/pyspark/rdd.py", line 1023, in takeUpToNumLeft
> yield next(iterator)
> TypeError: list object is not an iterator
> Changing mapFunc and sort back to generators rather than regular functions
> fixes that problem.
> After making that change, there is a second side effect due to the removal of
> flatMap where the above code returns the following unexpected result due to
> the default partitioning scheme:
> [[(1, 1), (2, 2)]]
> Removing sortByKey, e.g.:
> sc.parallelize([5,3,4,2,1]).map(lambda x: (x,x)).take(1)
> returns the expected result [(5, 5)]. Restoring the call to flatMap resolves
> this as well.
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