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https://issues.apache.org/jira/browse/SPARK-9746?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14662441#comment-14662441
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Andreas commented on SPARK-9746:
--------------------------------
Sure I tried this with different inputs (driven by ScalaCheck). If V would have
been arbitrary I wouldn't made up this issue.
Youst try 'cntxt.parallelize(List (("a", 1), ("a",
2))).groupBy(_._1).countByKey()' and you will get count '1' instead of '2' (one
key, two values)
> PairRDDFunctions.countByKey: values/counts always 1
> ---------------------------------------------------
>
> Key: SPARK-9746
> URL: https://issues.apache.org/jira/browse/SPARK-9746
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.4.0
> Reporter: Andreas
>
> org.apache.spark.rdd.PairRDDFunctionscountByKey(): Map[K, Long] =
> self.withScope {
> self.mapValues(_ => 1L).reduceByKey(_ + _).collect().toMap
> }
> obviously always returns count 1 for each key.
> If I understand the docs correctly I would expect this implementation:
> self.mapValues(_.size).reduceByKey(_ + _).collect().toMap
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