I am following the 1.1.0 document to run spark-shell in yarn client mode,
just getting exceptions flooding out.
bin/spark-shell --master yarn-client
Spark assembly has been built with Hive, including Datanucleus jars on
classpath
Using Spark's default log4j profile:
org/apache/spark/log4j-defaults.properties
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 1.2.0-SNAPSHOT
/_/
Using Scala version 2.10.4 (Java HotSpot(TM) 64-Bit Server VM, Java
1.7.0_17)
Type in expressions to have them evaluated.
Type :help for more information.
14/11/12 05:44:55 WARN NativeCodeLoader: Unable to load native-hadoop
library for your platform... using builtin-java classes where applicable
14/11/12 05:42:05 ERROR OneForOneStrategy:
java.lang.NullPointerException
at
org.apache.hadoop.yarn.util.RackResolver.coreResolve(RackResolver.java:101)
at
org.apache.hadoop.yarn.util.RackResolver.resolve(RackResolver.java:81)
at
org.apache.spark.deploy.yarn.YarnSparkHadoopUtil$.populateRackInfo(YarnSparkHadoopUtil.scala:197)
at
org.apache.spark.deploy.yarn.YarnSparkHadoopUtil$.lookupRack(YarnSparkHadoopUtil.scala:187)
at
org.apache.spark.scheduler.cluster.YarnClientClusterScheduler.getRackForHost(YarnClientClusterScheduler.scala:33)
at
org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$1.apply(TaskSchedulerImpl.scala:229)
at
org.apache.spark.scheduler.TaskSchedulerImpl$$anonfun$resourceOffers$1.apply(TaskSchedulerImpl.scala:221)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at
org.apache.spark.scheduler.TaskSchedulerImpl.resourceOffers(TaskSchedulerImpl.scala:221)
at
org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverActor.makeOffers(CoarseGrainedSchedulerBackend.scala:156)
at
org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverActor$$anonfun$receiveWithLogging$1.applyOrElse(CoarseGrainedSchedulerBackend.scala:126)
at
scala.runtime.AbstractPartialFunction$mcVL$sp.apply$mcVL$sp(AbstractPartialFunction.scala:33)
at
scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:33)
at
scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:25)
at
org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:53)
at
org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:42)
at scala.PartialFunction$class.applyOrElse(PartialFunction.scala:118)
at
org.apache.spark.util.ActorLogReceive$$anon$1.applyOrElse(ActorLogReceive.scala:42)
at akka.actor.Actor$class.aroundReceive(Actor.scala:465)
at
org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend$DriverActor.aroundReceive(CoarseGrainedSchedulerBackend.scala:71)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
at akka.actor.ActorCell.invoke(ActorCell.scala:487)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)
at akka.dispatch.Mailbox.run(Mailbox.scala:220)
at
akka.dispatch.ForkJoinExecutorConfigurator$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)
Have to clue what is wrong here.
Please help!
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