You have to manually start the shuffle service if you're not running YARN. See the "sbin/start-shuffle-service.sh" script.
On Tue, Oct 13, 2015 at 10:29 AM, <saif.a.ell...@wellsfargo.com> wrote: > I believe the confusion here is self-answered. > > The thing is that in the documentation, the spark shuffle service runs > only under YARN, while here we are speaking about a stand alone cluster. > > > > The proper question is, how to launch a shuffle service for stand alone? > > > > Saif > > > > *From:* saif.a.ell...@wellsfargo.com [mailto:saif.a.ell...@wellsfargo.com] > > *Sent:* Tuesday, October 13, 2015 2:25 PM > *To:* van...@cloudera.com > *Cc:* user@spark.apache.org > *Subject:* RE: Spark shuffle service does not work in stand alone > > > > Hi, thanks > > > > Executors are simply failing to connect to a shuffle server: > > > > 15/10/13 08:29:34 INFO BlockManagerMaster: Registered BlockManager > > 15/10/13 08:29:34 INFO BlockManager: Registering executor with local > external shuffle service. > > 15/10/13 08:29:34 ERROR BlockManager: Failed to connect to external > shuffle server, will retry 2 more times after waiting 5 seconds... > > java.io.IOException: Failed to connect to /162.xxx.zzz.yy:port > > at > org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:193) > > at > org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:156) > > at > org.apache.spark.network.shuffle.ExternalShuffleClient.registerWithShuffleServer(ExternalShuffleClient.java:140) > > at > org.apache.spark.storage.BlockManager$$anonfun$registerWithExternalShuffleServer$1.apply$mcVI$sp(BlockManager.scala:220) > > at scala.collection.immutable.Range.foreach$mVc$sp(Range.scala:141) > > at > org.apache.spark.storage.BlockManager.registerWithExternalShuffleServer(BlockManager.scala:217) > > at > org.apache.spark.storage.BlockManager.initialize(BlockManager.scala:203) > > at org.apache.spark.executor.Executor.<init>(Executor.scala:85) > > at > org.apache.spark.executor.CoarseGrainedExecutorBackend$$anonfun$receive$1.applyOrElse(CoarseGrainedExecutorBackend.scala:86) > > at org.apache.spark.rpc.akka.AkkaRpcEnv.org > $apache$spark$rpc$akka$AkkaRpcEnv$$processMessage(AkkaRpcEnv.scala:177) > > at > org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1$$anonfun$receiveWithLogging$1$$anonfun$applyOrElse$4.apply$mcV$sp(AkkaRpcEnv.scala:126) > > at org.apache.spark.rpc.akka.AkkaRpcEnv.org > $apache$spark$rpc$akka$AkkaRpcEnv$$safelyCall(AkkaRpcEnv.scala:197) > > at > org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1$$anonfun$receiveWithLogging$1.applyOrElse(AkkaRpcEnv.scala:125) > > at > scala.runtime.AbstractPartialFunction$mcVL$sp.apply$mcVL$sp(AbstractPartialFunction.scala:33) > > at > scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:33) > > at > scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:25) > > at > org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:59) > > 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:467) > > at > org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1.aroundReceive(AkkaRpcEnv.scala:92) > > at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516) > > at akka.actor.ActorCell.invoke(ActorCell.scala:487) > > at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238) > > at akka.dispatch.Mailbox.run(Mailbox.scala:220) > > at > akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:397) > > at > scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260) > > at > scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339) > > at > scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979) > > at > scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107) > > Caused by: java.net.ConnectException: Connection refused: > /162.xxx.zzz.yy:port > > at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method) > > at > sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:717) > > at > io.netty.channel.socket.nio.NioSocketChannel.doFinishConnect(NioSocketChannel.java:224) > > at > io.netty.channel.nio.AbstractNioChannel$AbstractNioUnsafe.finishConnect(AbstractNioChannel.java:289) > > at > io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:528) > > at > io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468) > > at > io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382) > > at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354) > > at > io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111) > > at java.lang.Thread.run(Thread.java:745) > > > > > > *From:* Marcelo Vanzin [mailto:van...@cloudera.com <van...@cloudera.com>] > *Sent:* Tuesday, October 13, 2015 1:13 PM > *To:* Ellafi, Saif A. > *Cc:* user@spark.apache.org > *Subject:* Re: Spark shuffle service does not work in stand alone > > > > It would probably be more helpful if you looked for the executor error and > posted it. The screenshot you posted is the driver exception caused by the > task failure, which is not terribly useful. > > > > On Tue, Oct 13, 2015 at 7:23 AM, <saif.a.ell...@wellsfargo.com> wrote: > > Has anyone tried shuffle service in Stand Alone cluster mode? I want to > enable it for d.a. but my jobs never start when I submit them. > > This happens with all my jobs. > > > > > > 15/10/13 08:29:45 INFO DAGScheduler: Job 0 failed: json at > DataLoader.scala:86, took 16.318615 s > > Exception in thread "main" org.apache.spark.SparkException: Job aborted > due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent > failure: Lost task 0.3 in stage 0.0 (TID 7, 162.101.194.47): > ExecutorLostFailure (executor 4 lost) > > Driver stacktrace: > > at org.apache.spark.scheduler.DAGScheduler.org > $apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1283) > > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1271) > > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1270) > > at > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > > at > scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) > > at > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1270) > > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697) > > at > org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697) > > at scala.Option.foreach(Option.scala:236) > > at > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:697) > > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1496) > > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1458) > > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1447) > > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) > > at > org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:567) > > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1822) > > at org.apache.spark.SparkContext.runJob(SparkContext.scala:1942) > > at org.apache.spark.rdd.RDD$$anonfun$reduce$1.apply(RDD.scala:1003) > > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147) > > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108) > > at org.apache.spark.rdd.RDD.withScope(RDD.scala:306) > > at org.apache.spark.rdd.RDD.reduce(RDD.scala:985) > > at > org.apache.spark.rdd.RDD$$anonfun$treeAggregate$1.apply(RDD.scala:1114) > > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147) > > at > org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108) > > at org.apache.spark.rdd.RDD.withScope(RDD.scala:306) > > at org.apache.spark.rdd.RDD.treeAggregate(RDD.scala:1091) > > at > org.apache.spark.sql.execution.datasources.json.InferSchema$.apply(InferSchema.scala:58) > > at > org.apache.spark.sql.execution.datasources.json.JSONRelation$$anonfun$6.apply(JSONRelation.scala:105) > > at > org.apache.spark.sql.execution.datasources.json.JSONRelation$$anonfun$6.apply(JSONRelation.scala:100) > > at scala.Option.getOrElse(Option.scala:120) > > at > org.apache.spark.sql.execution.datasources.json.JSONRelation.dataSchema$lzycompute(JSONRelation.scala:100) > > at > org.apache.spark.sql.execution.datasources.json.JSONRelation.dataSchema(JSONRelation.scala:99) > > at > org.apache.spark.sql.sources.HadoopFsRelation.schema$lzycompute(interfaces.scala:561) > > at > org.apache.spark.sql.sources.HadoopFsRelation.schema(interfaces.scala:560) > > at > org.apache.spark.sql.execution.datasources.LogicalRelation.<init>(LogicalRelation.scala:31) > > at > org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:120) > > at > org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:104) > > at > org.apache.spark.sql.DataFrameReader.json(DataFrameReader.scala:219) > > at > org.apache.saif.loaders.DataLoader$.load_json(DataLoader.scala:86) > > > > > > > > > > -- > > Marcelo > -- Marcelo
