[jira] [Updated] (SPARK-2569) Customized UDFs in hive not running with Spark SQL

["Michael Armbrust (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-2569?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Michael Armbrust updated SPARK-2569:
------------------------------------

            Priority: Critical  (was: Major)
    Target Version/s: 1.1.0

> 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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