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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2016/08/10 13:00:27 UTC

[jira] [Commented] (SPARK-16995) TreeNodeException when flat mapping RelationalGroupedDataset created from DataFrame containing a column created with lit/expr

    [ https://issues.apache.org/jira/browse/SPARK-16995?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15415243#comment-15415243 ] 

Sean Owen commented on SPARK-16995:
-----------------------------------

You haven't shown the exception -- this is typically useful.

> TreeNodeException when flat mapping RelationalGroupedDataset created from DataFrame containing a column created with lit/expr
> -----------------------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-16995
>                 URL: https://issues.apache.org/jira/browse/SPARK-16995
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.0.0
>            Reporter: Cédric Perriard
>
> A TreeNodeException is thrown when executing the following minimal example in Spark 2.0. Crucial is that the column q is generated with lit/expr. 
> {code}
> import spark.implicits._
> case class test (x: Int, q: Int)
> val d = Seq(1).toDF("x")
> d.withColumn("q", lit(0)).as[test].groupByKey(_.x).flatMapGroups{case (x, iter) => List()}.show
> d.withColumn("q", expr("0")).as[test].groupByKey(_.x).flatMapGroups{case (x, iter) => List()}.show
> // this works fine
> d.withColumn("q", lit(0)).as[test].groupByKey(_.x).count()
> {code}
> A possible workaround is to write the dataframe to disk before grouping and mapping.



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