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https://issues.apache.org/jira/browse/SPARK-29265?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16939423#comment-16939423
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Florentino Sainz commented on SPARK-29265:
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Ok just realized what's happening, we did have one element with MANY rows
inside the same group, when using collect_list we are multiplying the list for
each row. (this was not expected tho...)
I changed it to groupBy and now we only have one row with all the values :).
> Window+collect_list causing single-task operation
> -------------------------------------------------
>
> Key: SPARK-29265
> URL: https://issues.apache.org/jira/browse/SPARK-29265
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.4.0
> Environment: Any
> Reporter: Florentino Sainz
> Priority: Minor
>
> Hi,
>
> I had this problem in "real" environments and also made a self-contained test
> ( [^Test.scala] attached).
> Having this Window definition:
> {code:scala}
> val myWindow = Window.partitionBy($"word").orderBy("word")
> val filt2 = filtrador.withColumn("avg_Time",
> collect_list($"number").over(myWindow))
> {code}
>
> In the test I can see how all elements of my DF are being collected in a
> single task.
> Unbounded+unordered Window + collect_list seems to be collecting ALL the
> dataframe in a single executor/task.
> groupBy + collect_list seems to do it as expect (collect_list for each group
> independently).
>
> Full Code showing the error (see how the mapPartitions shows 99 rows in one
> partition) attached in Test.scala, sbt project (src and build.sbt) attached
> too in TestSpark.zip.
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