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Posted to issues@spark.apache.org by "Burak Yavuz (JIRA)" <ji...@apache.org> on 2015/08/04 23:43:05 UTC

[jira] [Commented] (SPARK-9614) InternalRow representation during executionPlan.toRdd.aggregete possibly problematic

    [ https://issues.apache.org/jira/browse/SPARK-9614?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14654402#comment-14654402 ] 

Burak Yavuz commented on SPARK-9614:
------------------------------------

cc [~joshrosen]

> InternalRow representation during executionPlan.toRdd.aggregete possibly problematic
> ------------------------------------------------------------------------------------
>
>                 Key: SPARK-9614
>                 URL: https://issues.apache.org/jira/browse/SPARK-9614
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 1.5.0
>            Reporter: Burak Yavuz
>            Priority: Blocker
>
> For example, in FrequentItems.scala, we have a specialized FrequentItems counter which is backed by a Mutable Map. The keys in the MutableMap are the elements in a column.
> After iterating through a partition, all the keys turn out to be the latest element seen in that partition!
> Assume a partition is composed of the elements ("0","1","2","3","4") for a column of a dataframe. The expected map is:
> {code}
> ("0" -> 1,"1" -> 1,"2" -> 1,"3" -> 1,"4" -> 1)
> {code}
> But once you print it out, it turns out to be:
> {code}
> ("4" -> 1,"4" -> 1,"4" -> 1,"4" -> 1,"4" -> 1)
> {code}
> There might be other instances where such behavior may be observed, and it must be analyzed before the release.



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