You are viewing a plain text version of this content. The canonical link for it is here.
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.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org