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https://issues.apache.org/jira/browse/SPARK-2998?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen resolved SPARK-2998.
------------------------------
Resolution: Duplicate
> scala.collection.mutable.HashSet cannot be cast to
> scala.collection.mutable.BitSet
> ----------------------------------------------------------------------------------
>
> Key: SPARK-2998
> URL: https://issues.apache.org/jira/browse/SPARK-2998
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.0.2
> Reporter: pengyanhong
> Priority: Blocker
>
> run a HiveQL via yarn-cluster, got error as below:
> {quote}
> 14/08/13 11:10:01 INFO
> org.apache.spark.Logging$class.logInfo(Logging.scala:58): Serialized task
> 8.0:2 as 20849 bytes in 0 ms
> 14/08/13 11:10:01 INFO
> org.apache.spark.Logging$class.logInfo(Logging.scala:58): Finished TID 812 in
> 24 ms on A01-R06-I149-32.jd.local (progress: 2/200)
> 14/08/13 11:10:01 INFO
> org.apache.spark.Logging$class.logInfo(Logging.scala:58): Completed
> ResultTask(8, 1)
> 14/08/13 11:10:01 INFO
> org.apache.spark.Logging$class.logInfo(Logging.scala:58): Failed to run
> reduce at joins.scala:336
> 14/08/13 11:10:01 INFO
> org.apache.spark.Logging$class.logInfo(Logging.scala:58):
> finishApplicationMaster with FAILED
> Exception in thread "Thread-2" java.lang.reflect.InvocationTargetException
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:39)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:25)
> at java.lang.reflect.Method.invoke(Method.java:597)
> at
> org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:199)
> Caused by: org.apache.spark.SparkDriverExecutionException: Execution error
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:849)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1231)
> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
> at akka.actor.ActorCell.invoke(ActorCell.scala:456)
> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
> at akka.dispatch.Mailbox.run(Mailbox.scala:219)
> at
> akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
> 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)
> Caused by: java.lang.ClassCastException: scala.collection.mutable.HashSet
> cannot be cast to scala.collection.mutable.BitSet
> at
> org.apache.spark.sql.execution.BroadcastNestedLoopJoin$$anonfun$7.apply(joins.scala:336)
> at org.apache.spark.rdd.RDD$$anonfun$19.apply(RDD.scala:813)
> at org.apache.spark.rdd.RDD$$anonfun$19.apply(RDD.scala:810)
> at
> org.apache.spark.scheduler.JobWaiter.taskSucceeded(JobWaiter.scala:56)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:845)
> ... 10 more
> 14/08/13 11:10:01 INFO
> org.apache.spark.Logging$class.logInfo(Logging.scala:58): Invoking sc stop
> from shutdown hook
> 14/08/13 11:10:01 INFO
> org.apache.spark.Logging$class.logInfo(Logging.scala:58): AppMaster received
> a signal.
> 14/08/13 11:10:01 INFO
> org.apache.spark.Logging$class.logInfo(Logging.scala:58): Starting task 8.0:3
> as TID 814 on executor 1: A01-R06-I149-32.jd.local (PROCESS_LOCAL)
> 14/08/13 11:10:01 INFO
> org.apache.spark.Logging$class.logInfo(Logging.scala:58): Serialized task
> 8.0:3 as 20849 bytes in 0 ms
> 14/08/13 11:10:01 INFO
> org.apache.spark.Logging$class.logInfo(Logging.scala:58): Finished TID 813 in
> 25 ms on A01-R06-I149-32.jd.local (progress: 3/200)
> 14/08/13 11:10:01 INFO
> org.apache.spark.Logging$class.logInfo(Logging.scala:58): Completed
> ResultTask(8, 2)
> ......
> {quote}
> It runs successfully if removing the configuration about Kryo
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