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https://issues.apache.org/jira/browse/SPARK-1591?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen resolved SPARK-1591.
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Resolution: Won't Fix
> scala.MatchError executing custom UDTF
> --------------------------------------
>
> Key: SPARK-1591
> URL: https://issues.apache.org/jira/browse/SPARK-1591
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 0.9.1
> Environment: CentOS 5, Hortonworks 1.3.2, Hadoop 1.2.0, Hive 0.11.0,
> Spark 0.9.1, Shark 0.9.1, sharkserver2, beeline
> Reporter: Ken Ellinwood
> Priority: Minor
>
> My custom UDTF fails to execute in Shark even though it runs fine in Hive.
> scala.MatchError: [orange, 1, Black, 419] (of class java.util.ArrayList)
> at scala.runtime.ScalaRunTime$.array_clone(ScalaRunTime.scala:118)
> at shark.execution.UDTFCollector.collect(UDTFOperator.scala:92)
> at
> org.apache.hadoop.hive.ql.udf.generic.GenericUDTF.forward(GenericUDTF.java:91)
> at
> com.mycompany.warehouse.hive.HiveUdtfColorTreeTable.process(HiveUdtfColorTreeTable.java:98)
> at shark.execution.UDTFOperator.explode(UDTFOperator.scala:79)
> at
> shark.execution.LateralViewJoinOperator$$anonfun$processPartition$1.apply(LateralViewJoinOperator.scala:141)
> The code at UDTFOperator.scala, line 92 is making two assumptions which are
> not true in my case. First, it claims to need to clone the row object.
> Second, it assumes all rows objects are arrays. In my case the row is
> represented by ArrayList and does not need to be cloned because my UDTF
> creates a new one for each row already. The clone operation fails because
> my row is not an array.
> I changed my implementation to use an array, but we have a non-trivial number
> of custom UDFs that all work with Hive and I think they should work in Shark
> without modification.
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