Yonathan Randolph created SPARK-13906: -----------------------------------------
Summary: Spark driver hangs when slave is started or stopped (org.apache.spark.rpc.RpcTimeoutException). Key: SPARK-13906 URL: https://issues.apache.org/jira/browse/SPARK-13906 Project: Spark Issue Type: Bug Components: Spark Core Affects Versions: 1.6.1 Environment: Machine with one core (e.g. ec2 t2.small) Reporter: Yonathan Randolph Priority: Minor When a slave is started or stopped and there is only one core, the spark driver hangs. Example: {code} spark-1.6.1-bin-hadoop2.6/sbin/start-master.sh spark-1.6.1-bin-hadoop2.6/sbin/start-slave.sh $(hostname):7077 spark-1.6.1-bin-hadoop2.6/bin/spark-shell --master spark://$(hostname):7077 spark> sc.parallelize(1 to 300, 20).map(x => {Thread.sleep(100); x*2}).collect() # While that is running, kill a slave spark-1.6.1-bin-hadoop2.6/sbin/stop-slave.sh {code} After 2 minutes, spark-shell spits out an error: {code} org.apache.spark.rpc.RpcTimeoutException: Cannot receive any reply in 120 seconds. This timeout is controlled by spark.rpc.askTimeout at org.apache.spark.rpc.RpcTimeout.org$apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcTimeout.scala:48) at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:63) at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59) at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:33) at scala.util.Failure$$anonfun$recover$1.apply(Try.scala:185) at scala.util.Try$.apply(Try.scala:161) at scala.util.Failure.recover(Try.scala:185) at scala.concurrent.Future$$anonfun$recover$1.apply(Future.scala:324) at scala.concurrent.Future$$anonfun$recover$1.apply(Future.scala:324) at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32) at org.spark-project.guava.util.concurrent.MoreExecutors$SameThreadExecutorService.execute(MoreExecutors.java:293) at scala.concurrent.impl.ExecutionContextImpl$$anon$1.execute(ExecutionContextImpl.scala:133) at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:40) at scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:248) at scala.concurrent.Promise$class.complete(Promise.scala:55) at scala.concurrent.impl.Promise$DefaultPromise.complete(Promise.scala:153) at scala.concurrent.Future$$anonfun$map$1.apply(Future.scala:235) at scala.concurrent.Future$$anonfun$map$1.apply(Future.scala:235) at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32) at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.processBatch$1(Future.scala:643) at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.apply$mcV$sp(Future.scala:658) at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.apply(Future.scala:635) at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.apply(Future.scala:635) at scala.concurrent.BlockContext$.withBlockContext(BlockContext.scala:72) at scala.concurrent.Future$InternalCallbackExecutor$Batch.run(Future.scala:634) at scala.concurrent.Future$InternalCallbackExecutor$.scala$concurrent$Future$InternalCallbackExecutor$$unbatchedExecute(Future.scala:694) at scala.concurrent.Future$InternalCallbackExecutor$.execute(Future.scala:685) at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:40) at scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:248) at scala.concurrent.Promise$class.tryFailure(Promise.scala:112) at scala.concurrent.impl.Promise$DefaultPromise.tryFailure(Promise.scala:153) at org.apache.spark.rpc.netty.NettyRpcEnv$$anon$1.run(NettyRpcEnv.scala:241) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) at java.util.concurrent.FutureTask.run(FutureTask.java:266) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:180) at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745) Caused by: java.util.concurrent.TimeoutException: Cannot receive any reply in 120 seconds at org.apache.spark.rpc.netty.NettyRpcEnv$$anon$1.run(NettyRpcEnv.scala:242) ... 7 more {code} Cause: When 1 == Runtime.getRuntime.availableProcessors(), by default there is only one dispatcher-event-loop thread (Dispatcher.scala). When any function on the dispatcher tries to ask a message to any endpoint on the same host, it blocks (e.g. when AppClient handles ExecutorUpdated by asking CoarseGrainedSchedulerBackend a RemoveExecutor message). {code} "dispatcher-event-loop-0" #23 daemon prio=5 os_prio=0 tid=0x00007fca7cfc9000 nid=0x907 waiting on condition [0x00007fca49982000] java.lang.Thread.State: TIMED_WAITING (parking) at sun.misc.Unsafe.park(Native Method) - parking to wait for <0x00000000c5618e90> (a scala.concurrent.impl.Promise$CompletionLatch) at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:215) at java.util.concurrent.locks.AbstractQueuedSynchronizer.doAcquireSharedNanos(AbstractQueuedSynchronizer.java:1037) at java.util.concurrent.locks.AbstractQueuedSynchronizer.tryAcquireSharedNanos(AbstractQueuedSynchronizer.java:1328) at scala.concurrent.impl.Promise$DefaultPromise.tryAwait(Promise.scala:208) at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:218) at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:223) at scala.concurrent.Await$$anonfun$result$1.apply(package.scala:107) at scala.concurrent.BlockContext$DefaultBlockContext$.blockOn(BlockContext.scala:53) at scala.concurrent.Await$.result(package.scala:107) at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75) at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:101) at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:77) at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.removeExecutor(CoarseGrainedSchedulerBackend.scala:359) at org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend.executorRemoved(SparkDeploySchedulerBackend.scala:144) at org.apache.spark.deploy.client.AppClient$ClientEndpoint$$anonfun$receive$1.applyOrElse(AppClient.scala:186) at org.apache.spark.rpc.netty.Inbox$$anonfun$process$1.apply$mcV$sp(Inbox.scala:116) at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:204) at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:100) at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.scala:215) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745) {code} Workaround: set --conf spark.rpc.netty.dispatcher.numThreads=2 on a single-core machine. Hopefully there are no deeper than 2 ask calls. -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org