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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2014/10/29 06:17:33 UTC
[jira] [Commented] (SPARK-4113) Pyhon UDF on ArrayType
[ https://issues.apache.org/jira/browse/SPARK-4113?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14188007#comment-14188007 ]
Apache Spark commented on SPARK-4113:
-------------------------------------
User 'davies' has created a pull request for this issue:
https://github.com/apache/spark/pull/2973
> Pyhon UDF on ArrayType
> ----------------------
>
> Key: SPARK-4113
> URL: https://issues.apache.org/jira/browse/SPARK-4113
> Project: Spark
> Issue Type: Bug
> Components: PySpark, SQL
> Affects Versions: 1.2.0
> Reporter: Davies Liu
> Assignee: Davies Liu
> Priority: Blocker
> Fix For: 1.2.0
>
>
> from Matei:
> I have a table where column c is of type array<int>. However the following set of commands fails:
> sqlContext.registerFunction("py_func", lambda a: len(a))
> %sql select py_func(c) from some_temp
> Error in SQL statement: java.lang.RuntimeException: org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 252.0 failed 4 times, most recent failure: Lost task 2.3 in stage 252.0 (TID 8454, ip-10-0-157-104.us-west-2.compute.internal): net.razorvine.pickle.PickleException: couldn't introspect javabean: java.lang.IllegalArgumentException: wrong number of arguments
> net.razorvine.pickle.Pickler.put_javabean(Pickler.java:603)
> net.razorvine.pickle.Pickler.dispatch(Pickler.java:299)
> net.razorvine.pickle.Pickler.save(Pickler.java:125)
> net.razorvine.pickle.Pickler.put_arrayOfObjects(Pickler.java:392)
> net.razorvine.pickle.Pickler.dispatch(Pickler.java:195)
> net.razorvine.pickle.Pickler.save(Pickler.java:125)
> net.razorvine.pickle.Pickler.put_arrayOfObjects(Pickler.java:392)
> net.razorvine.pickle.Pickler.dispatch(Pickler.java:195)
> net.razorvine.pickle.Pickler.save(Pickler.java:125)
> net.razorvine.pickle.Pickler.dump(Pickler.java:95)
> The same function works if I select a Row from my table into Python and call it on its third column.
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