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Posted to issues@spark.apache.org by "Michael Armbrust (JIRA)" <ji...@apache.org> on 2014/09/20 00:30:34 UTC

[jira] [Resolved] (SPARK-3501) Hive SimpleUDF will create duplicated type cast which cause exception in constant folding

     [ https://issues.apache.org/jira/browse/SPARK-3501?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Michael Armbrust resolved SPARK-3501.
-------------------------------------
       Resolution: Fixed
    Fix Version/s: 1.2.0

Issue resolved by pull request 2368
[https://github.com/apache/spark/pull/2368]

> Hive SimpleUDF will create duplicated type cast which cause exception in constant folding
> -----------------------------------------------------------------------------------------
>
>                 Key: SPARK-3501
>                 URL: https://issues.apache.org/jira/browse/SPARK-3501
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>            Reporter: Cheng Hao
>            Assignee: Cheng Hao
>            Priority: Minor
>             Fix For: 1.2.0
>
>
> When do the query like:
> select datediff(cast(value as timestamp), cast('2002-03-21 00:00:00' as timestamp)) from src;
> SparkSQL will raise exception:
> {panel}
> [info] - Cast Timestamp to Timestamp in UDF *** FAILED ***
> [info]   scala.MatchError: TimestampType (of class org.apache.spark.sql.catalyst.types.TimestampType$)
> [info]   at org.apache.spark.sql.catalyst.expressions.Cast.castToTimestamp(Cast.scala:77)
> [info]   at org.apache.spark.sql.catalyst.expressions.Cast.cast$lzycompute(Cast.scala:251)
> [info]   at org.apache.spark.sql.catalyst.expressions.Cast.cast(Cast.scala:247)
> [info]   at org.apache.spark.sql.catalyst.expressions.Cast.eval(Cast.scala:263)
> [info]   at org.apache.spark.sql.catalyst.optimizer.ConstantFolding$$anonfun$apply$5$$anonfun$applyOrElse$2.applyOrElse(Optimizer.scala:217)
> [info]   at org.apache.spark.sql.catalyst.optimizer.ConstantFolding$$anonfun$apply$5$$anonfun$applyOrElse$2.applyOrElse(Optimizer.scala:210)
> [info]   at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:144)
> [info]   at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4$$anonfun$apply$2.apply(TreeNode.scala:180)
> [info]   at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> [info]   at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> {panel}



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