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https://issues.apache.org/jira/browse/SPARK-9746?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14662341#comment-14662341
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Andreas edited comment on SPARK-9746 at 8/7/15 8:04 PM:
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Sorry, but I don't agree.
cntxt..parallelize(List (("a", 1), ("a", 2))).groupBy(_._1).countByKey()
returns 'Map(a -> 1)' but should in my opinion return 'Map(a -> 2)'
If the values (counts) are irrelevant then why this function is called
*count*ByKey and why does it return a Map instead of a Set?
The current implementation has no added value compared to
'pairRDD.keys.collect().toSet'
was (Author: agrothe1):
Sorry, but I don't agree.
cntxt..parallelize(List (("a", 1), ("a", 2))).groupBy(_._1).countByKey()
returns 'Map(a -> 1)' but should in my opinion return 'Map(a -> 2)'
If the values (counts) are irrelevant then why this function is called
*count*ByKey and why does it return a Map instead of a Set?
The current implementation has no added value compared to
'pairRDD.keys.collect().toSet'
cntxt.paralize
> 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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