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https://issues.apache.org/jira/browse/SPARK-2569?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14072258#comment-14072258
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Apache Spark commented on SPARK-2569:
-------------------------------------
User 'marmbrus' has created a pull request for this issue:
https://github.com/apache/spark/pull/1552
> Customized UDFs in hive not running with Spark SQL
> --------------------------------------------------
>
> Key: SPARK-2569
> URL: https://issues.apache.org/jira/browse/SPARK-2569
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.0.0
> Environment: linux or mac, hive 0.9.0 and hive 0.13.0 with hadoop
> 1.0.4, scala 2.10.3, spark 1.0.0
> Reporter: jacky hung
> Assignee: Michael Armbrust
> Priority: Critical
>
> start spark-shell,
> init (like create hiveContext, import ._ ect, make sure the jar including the
> UDFs is in classpath)
> hql("CREATE TEMPORARY FUNCTION t_ts AS 'udf.Timestamp'"), which is
> successful.
> then i tried hql("select t_ts(time) from data_common where xxxx limit
> 1").collect().foreach(println), which failed with NullPointException
> we had discussion about it in the mail list.
> http://apache-spark-user-list.1001560.n3.nabble.com/run-sparksql-hiveudf-error-throw-NPE-td8888.html#a9006
> java.lang.NullPointerException
> org.apache.spark.sql.hive.HiveFunctionFactory$class.getFunctionClass(hiveUdfs.scala:117)
> org.apache.spark.sql.hive.HiveUdf.getFunctionClass(hiveUdfs.scala:157)
> org.apache.spark.sql.hive.HiveFunctionFactory$class.createFunction(hiveUdfs.scala:119)
> org.apache.spark.sql.hive.HiveUdf.createFunction(hiveUdfs.scala:157)
> org.apache.spark.sql.hive.HiveUdf.function$lzycompute(hiveUdfs.scala:170)
> org.apache.spark.sql.hive.HiveUdf.function(hiveUdfs.scala:170)
> org.apache.spark.sql.hive.HiveSimpleUdf.method$lzycompute(hiveUdfs.scala:181)
> org.apache.spark.sql.hive.HiveSimpleUdf.method(hiveUdfs.scala:180)
> org.apache.spark.sql.hive.HiveSimpleUdf.wrappers$lzycompute(hiveUdfs.scala:186)
> org.apache.spark.sql.hive.HiveSimpleUdf.wrappers(hiveUdfs.scala:186)
> org.apache.spark.sql.hive.HiveSimpleUdf.eval(hiveUdfs.scala:220)
> org.apache.spark.sql.catalyst.expressions.MutableProjection.apply(Projection.scala:64)
>
> org.apache.spark.sql.execution.Aggregate$$anonfun$execute$1$$anonfun$7.apply(Aggregate.scala:160)
>
> org.apache.spark.sql.execution.Aggregate$$anonfun$execute$1$$anonfun$7.apply(Aggregate.scala:153)
> org.apache.spark.rdd.RDD$$anonfun$12.apply(RDD.scala:580)
> org.apache.spark.rdd.RDD$$anonfun$12.apply(RDD.scala:580)
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:261)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:228)
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
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