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https://issues.apache.org/jira/browse/SPARK-4785?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14237649#comment-14237649
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Cheng Lian commented on SPARK-4785:
-----------------------------------
Looked into this a bit. Seems that this issue is caused by a UDF contract
change in Hive 0.13.1. In Hive 0.12.0, it's always safe to construct and
initialize a fresh UDF object on worker side, while in Hive 0.13.1, UDF objects
should only be initialized on driver side and then serialized to the worker
side.
Thanks [~chenghao] for helping investigating this issue!
> When called with arguments referring column fields, PMOD throws NPE
> -------------------------------------------------------------------
>
> Key: SPARK-4785
> URL: https://issues.apache.org/jira/browse/SPARK-4785
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Reporter: Cheng Lian
> Priority: Blocker
>
> Reproducible when compiled with {{-Phive-0.13.1}}, {{-Phive0.12.0}} is OK.
> Reproduction steps with {{hive/console}}:
> {code}
> scala> loadTestTable("src")
> scala> sql("SELECT PMOD(key, 10) FROM src LIMIT 1").collect()
> ...
> 14/12/08 15:11:31 INFO DAGScheduler: Job 0 failed: runJob at
> basicOperators.scala:141, took 0.235788 s
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in
> stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0
> (TID 0, localhost): java.lang.NullPointerException
> at
> org.apache.hadoop.hive.ql.udf.generic.GenericUDFBaseNumeric.initialize(GenericUDFBaseNumeric.java:109)
> at
> org.apache.hadoop.hive.ql.udf.generic.GenericUDF.initializeAndFoldConstants(GenericUDF.java:116)
> at
> org.apache.spark.sql.hive.HiveGenericUdf.returnInspector$lzycompute(hiveUdfs.scala:156)
> at
> org.apache.spark.sql.hive.HiveGenericUdf.returnInspector(hiveUdfs.scala:155)
> at org.apache.spark.sql.hive.HiveGenericUdf.eval(hiveUdfs.scala:174)
> at
> org.apache.spark.sql.catalyst.expressions.Alias.eval(namedExpressions.scala:92)
> at
> org.apache.spark.sql.catalyst.expressions.InterpretedMutableProjection.apply(Projection.scala:68)
> at
> org.apache.spark.sql.catalyst.expressions.InterpretedMutableProjection.apply(Projection.scala:52)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$$anon$10.next(Iterator.scala:312)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at
> scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> at
> scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
> at
> org.apache.spark.sql.execution.Limit$$anonfun$4.apply(basicOperators.scala:141)
> at
> org.apache.spark.sql.execution.Limit$$anonfun$4.apply(basicOperators.scala:141)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1314)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1314)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
> at org.apache.spark.scheduler.Task.run(Task.scala:56)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:745)
> Driver stacktrace:
> at
> org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1214)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1203)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1202)
> at
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> at
> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1202)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
> at
> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:696)
> at scala.Option.foreach(Option.scala:236)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:696)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1420)
> at akka.actor.Actor$class.aroundReceive(Actor.scala:465)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessActor.aroundReceive(DAGScheduler.scala:1375)
> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
> at akka.actor.ActorCell.invoke(ActorCell.scala:487)
> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)
> at akka.dispatch.Mailbox.run(Mailbox.scala:220)
> at
> akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:393)
> at
> scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
> at
> scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
> at
> scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
> at
> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
> {code}
> This issue is introduced in [PR
> #3109|https://github.com/apache/spark/pull/3109/files#diff-010a66b2d9b5e8a991c7b23f666a2036R156],
> where {{GenericUDF.initialize}} was replaced by
> {{GenericUDF.initializeAndFoldConstants}}, which then calls
> {{GenericUDFBaseNumeric.initialize}} in case of {{PMOD}}. However,
> {{GenericUDFBaseNumeric.initialize}} needs to access the current
> {{SessionState}}
> [\[1\]|https://github.com/apache/hive/blob/release-0.13.1/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDFBaseNumeric.java#L109],
> which only exists on the driver side. Thus, when executed on executor side,
> an NPE is thrown.
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