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Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2019/10/08 05:43:15 UTC
[jira] [Resolved] (SPARK-2620) case class cannot be used as key for
reduce
[ https://issues.apache.org/jira/browse/SPARK-2620?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-2620.
---------------------------------
Resolution: Incomplete
> 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 Shell
> Affects Versions: 1.0.0, 1.1.0, 1.3.0, 1.4.0, 1.5.0, 1.6.0, 2.0.0, 2.1.0, 2.2.0, 2.3.0
> Environment: reproduced on spark-shell local[4]
> Reporter: Gerard Maas
> Assignee: Tobias Schlatter
> Priority: Critical
> Labels: bulk-closed, 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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