Description
Hive driver would load guava 11.0.2 from hadoop/tez, while remote spark context depends on guava 14.0.1, It should be JobMetrics deserialize failed on Hive driver side since Absent is used in Metrics, here is the hive driver log:
java.lang.IllegalAccessError: tried to access method com.google.common.base.Optional.<init>()V from class com.google.common.base.Absent at com.google.common.base.Absent.<init>(Absent.java:35) at com.google.common.base.Absent.<clinit>(Absent.java:33) at sun.misc.Unsafe.ensureClassInitialized(Native Method) at sun.reflect.UnsafeFieldAccessorFactory.newFieldAccessor(UnsafeFieldAccessorFactory.java:43) at sun.reflect.ReflectionFactory.newFieldAccessor(ReflectionFactory.java:140) at java.lang.reflect.Field.acquireFieldAccessor(Field.java:1057) at java.lang.reflect.Field.getFieldAccessor(Field.java:1038) at java.lang.reflect.Field.getLong(Field.java:591) at java.io.ObjectStreamClass.getDeclaredSUID(ObjectStreamClass.java:1663) at java.io.ObjectStreamClass.access$700(ObjectStreamClass.java:72) at java.io.ObjectStreamClass$2.run(ObjectStreamClass.java:480) at java.io.ObjectStreamClass$2.run(ObjectStreamClass.java:468) at java.security.AccessController.doPrivileged(Native Method) at java.io.ObjectStreamClass.<init>(ObjectStreamClass.java:468) at java.io.ObjectStreamClass.lookup(ObjectStreamClass.java:365) at java.io.ObjectStreamClass.initNonProxy(ObjectStreamClass.java:602) at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1622) at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1517) at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1771) at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1990) at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1915) at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798) at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1990) at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1915) at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1798) at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1350) at java.io.ObjectInputStream.readObject(ObjectInputStream.java:370) at akka.serialization.JavaSerializer$$anonfun$1.apply(Serializer.scala:136) at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57) at akka.serialization.JavaSerializer.fromBinary(Serializer.scala:136) at akka.serialization.Serialization$$anonfun$deserialize$1.apply(Serialization.scala:104) at scala.util.Try$.apply(Try.scala:161) at akka.serialization.Serialization.deserialize(Serialization.scala:98) at akka.remote.serialization.MessageContainerSerializer.fromBinary(MessageContainerSerializer.scala:63) at akka.serialization.Serialization$$anonfun$deserialize$1.apply(Serialization.scala:104) at scala.util.Try$.apply(Try.scala:161) at akka.serialization.Serialization.deserialize(Serialization.scala:98) at akka.remote.MessageSerializer$.deserialize(MessageSerializer.scala:23) at akka.remote.DefaultMessageDispatcher.payload$lzycompute$1(Endpoint.scala:58) at akka.remote.DefaultMessageDispatcher.payload$1(Endpoint.scala:58) at akka.remote.DefaultMessageDispatcher.dispatch(Endpoint.scala:76) at akka.remote.EndpointReader$$anonfun$receive$2.applyOrElse(Endpoint.scala:937) at akka.actor.Actor$class.aroundReceive(Actor.scala:465) at akka.remote.EndpointActor.aroundReceive(Endpoint.scala:415) 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)
and remote spark context log:
2014-11-13 17:16:28,481 INFO [task-result-getter-1]: scheduler.TaskSetManager (Logging.scala:logInfo(59)) - Finished task 0.0 in stage 1.0 (TID 1) in 439 ms on node14-4 (1/1) 2014-11-13 17:16:28,482 INFO [sparkDriver-akka.actor.default-dispatcher-8]: scheduler.DAGScheduler (Logging.scala:logInfo(59)) - Stage 1 (foreachAsync at RemoteHiveSparkClient.java:121) finished in 0.452 s 2014-11-13 17:16:28,482 INFO [task-result-getter-1]: scheduler.TaskSchedulerImpl (Logging.scala:logInfo(59)) - Removed TaskSet 1.0, whose tasks have all completed, from pool 2014-11-13 17:16:28,486 INFO [08592e9f-19a2-413d-bc48-c871259c4d2e-akka.actor.default-dispatcher-4]: remote.RemoteActorRefProvider$RemoteDeadLetterActorRef (Slf4jLogger.scala:apply$mcV$sp(74)) - Message [org.apache.hive.spark.client.Protocol$JobMetrics] from Actor[akka://08592e9f-19a2-413d-bc48-c871259c4d2e/user/RemoteDriver#-893697064] to Actor[akka://08592e9f-19a2-413d-bc48-c871259c4d2e/deadLetters] was not delivered. [3] dead letters encountered. This logging can be turned off or adjusted with configuration settings 'akka.log-dead-letters' and 'akka.log-dead-letters-during-shutdown'. 2014-11-13 17:16:28,494 INFO [08592e9f-19a2-413d-bc48-c871259c4d2e-akka.actor.default-dispatcher-4]: remote.RemoteActorRefProvider$RemoteDeadLetterActorRef (Slf4jLogger.scala:apply$mcV$sp(74)) - Message [org.apache.hive.spark.client.Protocol$JobResult] from Actor[akka://08592e9f-19a2-413d-bc48-c871259c4d2e/user/RemoteDriver#-893697064] to Actor[akka://08592e9f-19a2-413d-bc48-c871259c4d2e/deadLetters] was not delivered. [4] dead letters encountered. This logging can be turned off or adjusted with configuration settings 'akka.log-dead-letters' and 'akka.log-dead-letters-during-shutdown'.
Attachments
Attachments
Issue Links
- is related to
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HIVE-8878 Downgrade guava version to be consistent with Hive and the rest of Hadoop [Spark Branch]
- Open
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HIVE-7387 Guava version conflict between hadoop and spark [Spark-Branch]
- Resolved
- relates to
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HIVE-8903 downgrade guava version for spark branch from 14.0.1 to 11.0.2.[Spark Branch]
- Resolved
- links to