Spark Streaming Stateful Network Word Count - scala

Question

This is the example code that came with Spark. I copied the code here and this is the link to it: https://github.com/apache/spark/blob/master/examples/src/main/scala/org/apache/spark/examples/streaming/StatefulNetworkWordCount.scala. However, when I was trying to run the program using command "bin/run-example org.apache.spark.examples.streaming.StatefulNetworkWordCount localhost 9999", I was given the following error:
14/07/20 11:52:57 ERROR ActorSystemImpl: Uncaught fatal error from thread [spark-akka.actor.default-dispatcher-4] shutting down ActorSystem [spark]
java.lang.NoSuchMethodError: java.util.concurrent.ConcurrentHashMap.keySet()Ljava/util/concurrent/ConcurrentHashMap$KeySetView;
at org.apache.spark.streaming.scheduler.JobScheduler.getPendingTimes(JobScheduler.scala:114)
at org.apache.spark.streaming.Checkpoint.<init>(Checkpoint.scala:43)
at org.apache.spark.streaming.scheduler.JobGenerator.doCheckpoint(JobGenerator.scala:259)
at org.apache.spark.streaming.scheduler.JobGenerator.org$apache$spark$streaming$scheduler$JobGenerator$$processEvent(JobGenerator.scala:167)
at org.apache.spark.streaming.scheduler.JobGenerator$$anonfun$start$1$$anon$1$$anonfun$receive$1.applyOrElse(JobGenerator.scala:76)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at akka.dispatch.ForkJoinExecutorConfigurator$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)
Exception in thread "Thread-37" org.apache.spark.SparkException: Job cancelled because SparkContext was shut down
at org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:639)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:638)
at scala.collection.mutable.HashSet.foreach(HashSet.scala:79)
at org.apache.spark.scheduler.DAGScheduler.cleanUpAfterSchedulerStop(DAGScheduler.scala:638)
at org.apache.spark.scheduler.DAGSchedulerEventProcessActor.postStop(DAGScheduler.scala:1215)
at akka.actor.dungeon.FaultHandling$class.akka$actor$dungeon$FaultHandling$$finishTerminate(FaultHandling.scala:201)
at akka.actor.dungeon.FaultHandling$class.terminate(FaultHandling.scala:163)
at akka.actor.ActorCell.terminate(ActorCell.scala:338)
at akka.actor.ActorCell.invokeAll$1(ActorCell.scala:431)
at akka.actor.ActorCell.systemInvoke(ActorCell.scala:447)
at akka.dispatch.Mailbox.processAllSystemMessages(Mailbox.scala:262)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:240)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
14/07/20 11:53:00 ERROR Executor: Exception in task ID 0
java.lang.IllegalStateException: cannot create children while terminating or terminated
at akka.actor.dungeon.Children$class.makeChild(Children.scala:184)
at akka.actor.dungeon.Children$class.attachChild(Children.scala:42)
at akka.actor.ActorCell.attachChild(ActorCell.scala:338)
at akka.actor.ActorSystemImpl.actorOf(ActorSystem.scala:518)
at org.apache.spark.streaming.receiver.ReceiverSupervisorImpl.<init>(ReceiverSupervisorImpl.scala:67)
at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverLauncher$$anonfun$9.apply(ReceiverTracker.scala:263)
at org.apache.spark.streaming.scheduler.ReceiverTracker$ReceiverLauncher$$anonfun$9.apply(ReceiverTracker.scala:257)
at org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1080)
at org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1080)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
at org.apache.spark.scheduler.Task.run(Task.scala:51)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:744)
14/07/20 11:53:06 ERROR ExecutorUncaughtExceptionHandler: Uncaught exception in thread Thread[spark-akka.actor.default-dispatcher-13,5,main]
org.apache.spark.SparkException: Error sending message to BlockManagerMaster [message = HeartBeat(BlockManagerId(<driver>, x-131-212-225-148.uofm-secure.wireless.umn.edu, 47668, 0))]
at org.apache.spark.storage.BlockManagerMaster.askDriverWithReply(BlockManagerMaster.scala:251)
at org.apache.spark.storage.BlockManagerMaster.sendHeartBeat(BlockManagerMaster.scala:51)
at org.apache.spark.storage.BlockManager.org$apache$spark$storage$BlockManager$$heartBeat(BlockManager.scala:113)
at org.apache.spark.storage.BlockManager$$anonfun$initialize$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(BlockManager.scala:158)
at org.apache.spark.util.Utils$.tryOrExit(Utils.scala:790)
at org.apache.spark.storage.BlockManager$$anonfun$initialize$1.apply$mcV$sp(BlockManager.scala:158)
at akka.actor.Scheduler$$anon$9.run(Scheduler.scala:80)
at akka.actor.LightArrayRevolverScheduler$$anon$3$$anon$2.run(Scheduler.scala:241)
at akka.actor.LightArrayRevolverScheduler$TaskHolder.run(Scheduler.scala:464)
at akka.actor.LightArrayRevolverScheduler$$anonfun$close$1.apply(Scheduler.scala:281)
at akka.actor.LightArrayRevolverScheduler$$anonfun$close$1.apply(Scheduler.scala:280)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at akka.actor.LightArrayRevolverScheduler.close(Scheduler.scala:279)
at akka.actor.ActorSystemImpl.stopScheduler(ActorSystem.scala:630)
at akka.actor.ActorSystemImpl$$anonfun$_start$1.apply$mcV$sp(ActorSystem.scala:582)
at akka.actor.ActorSystemImpl$$anonfun$_start$1.apply(ActorSystem.scala:582)
at akka.actor.ActorSystemImpl$$anonfun$_start$1.apply(ActorSystem.scala:582)
at akka.actor.ActorSystemImpl$$anon$3.run(ActorSystem.scala:596)
at akka.actor.ActorSystemImpl$TerminationCallbacks$$anonfun$run$1.runNext$1(ActorSystem.scala:750)
at akka.actor.ActorSystemImpl$TerminationCallbacks$$anonfun$run$1.apply$mcV$sp(ActorSystem.scala:753)
at akka.actor.ActorSystemImpl$TerminationCallbacks$$anonfun$run$1.apply(ActorSystem.scala:746)
at akka.actor.ActorSystemImpl$TerminationCallbacks$$anonfun$run$1.apply(ActorSystem.scala:746)
at akka.util.ReentrantGuard.withGuard(LockUtil.scala:15)
at akka.actor.ActorSystemImpl$TerminationCallbacks.run(ActorSystem.scala:746)
at akka.actor.ActorSystemImpl$$anonfun$terminationCallbacks$1.apply(ActorSystem.scala:593)
at akka.actor.ActorSystemImpl$$anonfun$terminationCallbacks$1.apply(ActorSystem.scala:593)
at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32)
at akka.dispatch.BatchingExecutor$Batch$$anonfun$run$1.processBatch$1(BatchingExecutor.scala:67)
at akka.dispatch.BatchingExecutor$Batch$$anonfun$run$1.apply$mcV$sp(BatchingExecutor.scala:82)
at akka.dispatch.BatchingExecutor$Batch$$anonfun$run$1.apply(BatchingExecutor.scala:59)
at akka.dispatch.BatchingExecutor$Batch$$anonfun$run$1.apply(BatchingExecutor.scala:59)
at scala.concurrent.BlockContext$.withBlockContext(BlockContext.scala:72)
at akka.dispatch.BatchingExecutor$Batch.run(BatchingExecutor.scala:58)
at akka.dispatch.TaskInvocation.run(AbstractDispatcher.scala:42)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
Caused by: akka.pattern.AskTimeoutException: Recipient[Actor[akka://spark/user/BlockManagerMaster#1887396223]] had already been terminated.
at akka.pattern.AskableActorRef$.ask$extension(AskSupport.scala:134)
at org.apache.spark.storage.BlockManagerMaster.askDriverWithReply(BlockManagerMaster.scala:236)
****************CODE********************
object StatefulNetworkWordCount {
def main(args: Array[String]) {
if (args.length < 2) {
System.err.println("Usage: StatefulNetworkWordCount <hostname> <port>")
System.exit(1)
}
StreamingExamples.setStreamingLogLevels()
val updateFunc = (values: Seq[Int], state: Option[Int]) => {
val currentCount = values.foldLeft(0)(_ + _)
val previousCount = state.getOrElse(0)
Some(currentCount + previousCount)
}
val sparkConf = new SparkConf().setAppName("StatefulNetworkWordCount")
// Create the context with a 1 second batch size
val ssc = new StreamingContext(sparkConf, Seconds(1))
ssc.checkpoint(".")
// Create a NetworkInputDStream on target ip:port and count the
// words in input stream of \n delimited test (eg. generated by 'nc')
val lines = ssc.socketTextStream(args(0), args(1).toInt)
val words = lines.flatMap(_.split(" "))
val wordDstream = words.map(x => (x, 1))
// Update the cumulative count using updateStateByKey
// This will give a Dstream made of state (which is the cumulative count of the words)
val stateDstream = wordDstream.updateStateByKey[Int](updateFunc)
stateDstream.print()
ssc.start()
ssc.awaitTermination()
}
}
I wonder if it is because, it is trying to set up the checkpoint at my local file system by doing commands "ssc.checkpoint(".")", while the file is not a file compatible with hadoop? (the file must be compatible with hadoop in order to set the checkpoint) If it is, how could I fix it? Thanks!

Answer 1

what's your JRE run time release, 1.7 or 1.8 , I have the similar issue that, I compile spark-source-code in 1.8, but if I use 1.7 to run the code, this issue will happen, change back to 1.8 as run time issue will solve.
jdk 1.8, concurrenthashmap.java(line 812):
// views
private transient KeySetView<K,V> keySet;
private transient ValuesView<K,V> values;
private transient EntrySetView<K,V> entrySet;
jdk 1.7 don't have above code
Hope it will help ^_^