yes, indeed the URI should be fine, besides I don't use ZK and still getting the same error... M.
2014-02-04 Mark Hamstra <[email protected]>: > Nope, sorry -- looks like that particular issue has been fixed so that > your URI should be fine. > > > On Tue, Feb 4, 2014 at 2:33 AM, Mark Hamstra <[email protected]>wrote: > >> export MASTER=mesos://zk://10.10.0.141:2181/mesos >> >> >> On Tue, Feb 4, 2014 at 2:20 AM, Francesco Bongiovanni < >> [email protected]> wrote: >> >>> Hi everyone, >>> >>> I installed the latest Spark release (0.9.0), on top of Mesos, linked >>> to my >>> HDFS 1.2.1 (sbt assembly success, make-distribution success), and when I >>> try >>> to launch some ops from the spark-shell, I got the following error. I >>> configured my spark-env.sh and exported the correct env variables, but I >>> am >>> stucked on this error. I have tried building Spark from the sources, from >>> the binaries with Hadoop1, cleaned my .ivy2 and .m2 caches, and the same >>> error arises...what am I missing ? >>> >>> Here are my spark-env and the stderr from Mesos. >>> >>> >>> =================SPARK-ENV.SH============================== >>> export MESOS_NATIVE_LIBRARY=/usr/local/lib/libmesos.so >>> export >>> SPARK_EXECUTOR_URI=hdfs:// >>> 10.10.0.141:9000/spark/spark-0.9.0-incubating.tgz >>> export MASTER=zk://10.10.0.141:2181/mesos >>> export SPARK_LOCAL_IP=10.10.0.141 >>> >>> if [ -z "$SPARK_MEM" ] ; then >>> SPARK_MEM="15g" >>> fi >>> >>> >>> if [ -z "$SPARK_WORKER_MEMORY" ] ; then >>> SPARK_WORKER_MEMORY="40g" >>> fi >>> >>> >>> >>> >>> >>> ===============STDERR======================================= >>> 14/02/04 11:04:22 INFO MesosExecutorBackend: Using Spark's default log4j >>> profile: org/apache/spark/log4j-defaults.properties >>> 14/02/04 11:04:22 INFO MesosExecutorBackend: Registered with Mesos as >>> executor ID 201402040838-2365590026-5050-31560-7 >>> 14/02/04 11:04:22 INFO Slf4jLogger: Slf4jLogger started >>> 14/02/04 11:04:22 INFO Remoting: Starting remoting >>> 14/02/04 11:04:22 INFO Remoting: Remoting started; listening on addresses >>> :[akka.tcp://[email protected]:56046] >>> 14/02/04 11:04:22 INFO Remoting: Remoting now listens on addresses: >>> [akka.tcp://[email protected]:56046] >>> 14/02/04 11:04:23 INFO SparkEnv: Connecting to BlockManagerMaster: >>> akka.tcp://spark@localhost:7077/user/BlockManagerMaster >>> akka.actor.ActorNotFound: Actor not found for: >>> ActorSelection[Actor[akka.tcp://spark@localhost >>> :7077/]/user/BlockManagerMaster] >>> at >>> >>> akka.actor.ActorSelection$$anonfun$resolveOne$1.apply(ActorSelection.scala:66) >>> at >>> >>> akka.actor.ActorSelection$$anonfun$resolveOne$1.apply(ActorSelection.scala:64) >>> at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32) >>> at >>> >>> akka.dispatch.BatchingExecutor$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$Batch.run(BatchingExecutor.scala:58) >>> at >>> >>> akka.dispatch.ExecutionContexts$sameThreadExecutionContext$.unbatchedExecute(Future.scala:74) >>> at >>> akka.dispatch.BatchingExecutor$class.execute(BatchingExecutor.scala:110) >>> at >>> >>> akka.dispatch.ExecutionContexts$sameThreadExecutionContext$.execute(Future.scala:73) >>> at >>> scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:40) >>> at >>> >>> scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:248) >>> at akka.pattern.PromiseActorRef.$bang(AskSupport.scala:269) >>> at >>> akka.actor.EmptyLocalActorRef.specialHandle(ActorRef.scala:512) >>> at >>> akka.actor.DeadLetterActorRef.specialHandle(ActorRef.scala:545) >>> at akka.actor.DeadLetterActorRef.$bang(ActorRef.scala:535) >>> at >>> >>> akka.remote.RemoteActorRefProvider$RemoteDeadLetterActorRef.$bang(RemoteActorRefProvider.scala:91) >>> at akka.actor.ActorRef.tell(ActorRef.scala:125) >>> at >>> akka.dispatch.Mailboxes$$anon$1$$anon$2.enqueue(Mailboxes.scala:44) >>> at >>> akka.dispatch.QueueBasedMessageQueue$class.cleanUp(Mailbox.scala:438) >>> at >>> >>> akka.dispatch.UnboundedDequeBasedMailbox$MessageQueue.cleanUp(Mailbox.scala:650) >>> at akka.dispatch.Mailbox.cleanUp(Mailbox.scala:309) >>> at >>> akka.dispatch.MessageDispatcher.unregister(AbstractDispatcher.scala:204) >>> at >>> akka.dispatch.MessageDispatcher.detach(AbstractDispatcher.scala:140) >>> at >>> >>> akka.actor.dungeon.FaultHandling$class.akka$actor$dungeon$FaultHandling$$finishTerminate(FaultHandling.scala:203) >>> at >>> akka.actor.dungeon.FaultHandling$class.terminate(FaultHandling.scala:163) >>> at akka.actor.ActorCell.terminate(ActorCell.scala:338) >>> at akka.actor.ActorCell.invokeAll$1(ActorCell.scala:431) >>> at akka.actor.ActorCell.systemInvoke(ActorCell.scala:447) >>> at >>> akka.dispatch.Mailbox.processAllSystemMessages(Mailbox.scala:262) >>> at akka.dispatch.Mailbox.run(Mailbox.scala:218) >>> at >>> >>> akka.dispatch.ForkJoinExecutorConfigurator$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-0" >>> >>> >>> >>> -- >>> View this message in context: >>> http://apache-spark-user-list.1001560.n3.nabble.com/spark-0-9-0-on-top-of-Mesos-error-Akka-Actor-not-found-tp1164.html >>> Sent from the Apache Spark User List mailing list archive at Nabble.com. >>> >> >> >
