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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-2620) case class cannot be used as key for reduce
Date Fri, 25 Jul 2014 08:26:38 GMT

    [ https://issues.apache.org/jira/browse/SPARK-2620?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14074196#comment-14074196
] 

Apache Spark commented on SPARK-2620:
-------------------------------------

User 'ash211' has created a pull request for this issue:
https://github.com/apache/spark/pull/1588

> case class cannot be used as key for reduce
> -------------------------------------------
>
>                 Key: SPARK-2620
>                 URL: https://issues.apache.org/jira/browse/SPARK-2620
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 1.0.0
>         Environment: reproduced on spark-shell local[4]
>            Reporter: Gerard Maas
>            Priority: Critical
>              Labels: case-class, core
>
> Using a case class as a key doesn't seem to work properly on Spark 1.0.0
> A minimal example:
> case class P(name:String)
> val ps = Array(P("alice"), P("bob"), P("charly"), P("bob"))
> sc.parallelize(ps).map(x=> (x,1)).reduceByKey((x,y) => x+y).collect
> [Spark shell local mode] res : Array[(P, Int)] = Array((P(bob),1), (P(bob),1), (P(abe),1),
(P(charly),1))
> In contrast to the expected behavior, that should be equivalent to:
> sc.parallelize(ps).map(x=> (x.name,1)).reduceByKey((x,y) => x+y).collect
> Array[(String, Int)] = Array((charly,1), (abe,1), (bob,2))
> groupByKey and distinct also present the same behavior.



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