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From "Josh Rosen (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (SPARK-3441) Explain in docs that repartitionAndSortWithinPartitions enacts Hadoop style shuffle
Date Sun, 25 Oct 2015 01:39:27 GMT

     [ https://issues.apache.org/jira/browse/SPARK-3441?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Josh Rosen resolved SPARK-3441.
-------------------------------
       Resolution: Fixed
         Assignee: Ilya Ganelin  (was: Sandy Ryza)
    Fix Version/s: 1.3.1
                   1.4.0

This was done as part of https://github.com/apache/spark/pull/5074

> Explain in docs that repartitionAndSortWithinPartitions enacts Hadoop style shuffle
> -----------------------------------------------------------------------------------
>
>                 Key: SPARK-3441
>                 URL: https://issues.apache.org/jira/browse/SPARK-3441
>             Project: Spark
>          Issue Type: Improvement
>          Components: Documentation, Spark Core
>            Reporter: Patrick Wendell
>            Assignee: Ilya Ganelin
>             Fix For: 1.4.0, 1.3.1
>
>
> I think it would be good to say something like this in the doc for repartitionAndSortWithinPartitions
and add also maybe in the doc for groupBy:
> {code}
> This can be used to enact a "Hadoop Style" shuffle along with a call to mapPartitions,
e.g.:
>    rdd.repartitionAndSortWithinPartitions(part).mapPartitions(...)
> {code}
> It might also be nice to add a version that doesn't take a partitioner and/or to mention
this in the groupBy javadoc. I guess it depends a bit whether we consider this to be an API
we want people to use more widely or whether we just consider it a narrow stable API mostly
for Hive-on-Spark. If we want people to consider this API when porting workloads from Hadoop,
then it might be worth documenting better.
> What do you think [~rxin] and [~matei]?



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