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https://issues.apache.org/jira/browse/SPARK-3655?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14180155#comment-14180155
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koert kuipers edited comment on SPARK-3655 at 10/22/14 4:54 PM:
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i am not sure repartitionAndSortWithinPartitions does what i want. what i want
to do is for a given RDD[(K, V)] is use the sort-based shuffle to group by key
but sort by (K, V), so that for each key the values come out sorted in the
resulting RDD
i could do something like map a RDD[(K, V)] to a RDD[((K, V), V] and then use
sortByKey, which does result in the values sorted for each key, but if i do
that i have no guarantee that all values for a given key end up in same
partition.
maybe i am missing something...
best, koert
was (Author: koert):
i am not sure repartitionAndSortWithinPartitions does what i want. what i want
to do is for a given RDD[(K, V)] is use the sort-based shuffle to group by key
but sort by (K, V), so that for each key the values come out sorted in the
resulting RDD.
> Secondary sort
> --------------
>
> Key: SPARK-3655
> URL: https://issues.apache.org/jira/browse/SPARK-3655
> Project: Spark
> Issue Type: New Feature
> Components: Spark Core
> Affects Versions: 1.1.0
> Reporter: koert kuipers
> Priority: Minor
>
> Now that spark has a sort based shuffle, can we expect a secondary sort soon?
> There are some use cases where getting a sorted iterator of values per key is
> helpful.
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