My bad there, I was using the correct link for docs. The spark shell runs correctly, the framework is registered fine on mesos.
is there some setting i am missing: this is my spark-env.sh>>> export MESOS_NATIVE_LIBRARY=/usr/local/lib/libmesos.so export SPARK_EXECUTOR_URI=http://100.125.5.93/sparkx.tgz export SPARK_LOCAL_IP=127.0.0.1 here is what i see on the slave node. ---------------- less 20150226-160708-788888932-5050-8971-S0/frameworks/20150323-205508-788888932-5050-29804-0012/executors/20150226-160708-788888932-5050-8971-S0/runs/cceea834-c4d9-49d6-a579-8352f1889b56/stderr >>>>> WARNING: Logging before InitGoogleLogging() is written to STDERR I0324 02:30:29.389225 27755 fetcher.cpp:76] Fetching URI ' http://100.125.5.93/sparkx.tgz' I0324 02:30:29.389361 27755 fetcher.cpp:126] Downloading ' http://100.125.5.93/sparkx.tgz' to '/tmp/mesos/slaves/20150226-160708-788888932-5050-8971-S0/frameworks/20150323-205508-788888932-5050-29804-0012/executors/20150226-160708-788888932-5050-8971-S0/runs/cceea834-c4d9-49d6-a579-8352f1889b56/sparkx.tgz' I0324 02:30:35.353446 27755 fetcher.cpp:64] Extracted resource '/tmp/mesos/slaves/20150226-160708-788888932-5050-8971-S0/frameworks/20150323-205508-788888932-5050-29804-0012/executors/20150226-160708-788888932-5050-8971-S0/runs/cceea834-c4d9-49d6-a579-8352f1889b56/sparkx.tgz' into '/tmp/mesos/slaves/20150226-160708-788888932-5050-8971-S0/frameworks/20150323-205508-788888932-5050-29804-0012/executors/20150226-160708-788888932-5050-8971-S0/runs/cceea834-c4d9-49d6-a579-8352f1889b56' Spark assembly has been built with Hive, including Datanucleus jars on classpath Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties 15/03/24 02:30:37 INFO MesosExecutorBackend: Registered signal handlers for [TERM, HUP, INT] I0324 02:30:37.071077 27863 exec.cpp:132] Version: 0.21.1 I0324 02:30:37.080971 27885 exec.cpp:206] Executor registered on slave 20150226-160708-788888932-5050-8971-S0 15/03/24 02:30:37 INFO MesosExecutorBackend: Registered with Mesos as executor ID 20150226-160708-788888932-5050-8971-S0 with 1 cpus 15/03/24 02:30:37 INFO SecurityManager: Changing view acls to: ubuntu 15/03/24 02:30:37 INFO SecurityManager: Changing modify acls to: ubuntu 15/03/24 02:30:37 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(ubuntu); users with modify permissions: Set(ubuntu) 15/03/24 02:30:37 INFO Slf4jLogger: Slf4jLogger started 15/03/24 02:30:37 INFO Remoting: Starting remoting 15/03/24 02:30:38 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkexecu...@mesos-si2.dny1.bcpc.bloomberg.com:50542] 15/03/24 02:30:38 INFO Utils: Successfully started service 'sparkExecutor' on port 50542. 15/03/24 02:30:38 INFO AkkaUtils: Connecting to MapOutputTracker: akka.tcp://sparkDriver@localhost:51849/user/MapOutputTracker 15/03/24 02:30:38 WARN Remoting: Tried to associate with unreachable remote address [akka.tcp://sparkDriver@localhost:51849]. Address is now gated for 5000 ms, all messages to this address will be delivered to dead letters. Reason: Connection refused: localhost/127.0.0.1:51849 akka.actor.ActorNotFound: Actor not found for: ActorSelection[Anchor(akka.tcp://sparkDriver@localhost:51849/), Path(/user/MapOutputTracker)] at akka.actor.ActorSelection$$anonfun$resolveOne$1.apply(ActorSelection.scala:65) at akka.actor.ActorSelection$$anonfun$resolveOne$1.apply(ActorSelection.scala:63) at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32) at akka.dispatch.BatchingExecutor$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:267) at akka.actor.EmptyLocalActorRef.specialHandle(ActorRef.scala:508) at akka.actor.DeadLetterActorRef.specialHandle(ActorRef.scala:541) at akka.actor.DeadLetterActorRef.$bang(ActorRef.scala:531) at akka.remote.RemoteActorRefProvider$RemoteDeadLetterActorRef.$bang(RemoteActorRefProvider.scala:87) On Mar 23, 2015, at 3:02 PM, Dean Wampler <deanwamp...@gmail.com> wrote: That's a very old page, try this instead: http://spark.apache.org/docs/latest/running-on-mesos.html When you run your Spark job on Mesos, tasks will be started on the slave nodes as needed, since "fine-grained" mode is the default. For a job like your example, very few tasks will be needed. Actually only one would be enough, but the default number of partitions will be used. I believe 8 is the default for Mesos. For local mode ("local[*]"), it's the number of cores. You can also set the propoerty "spark.default.parallelism". HTH, Dean Dean Wampler, Ph.D. Author: Programming Scala, 2nd Edition <http://shop.oreilly.com/product/0636920033073.do> (O'Reilly) Typesafe <http://typesafe.com> @deanwampler <http://twitter.com/deanwampler> http://polyglotprogramming.com On Mon, Mar 23, 2015 at 11:46 AM, Anirudha Jadhav <aniru...@nyu.edu> wrote: > i have a mesos cluster, which i deploy spark to by using instructions on > http://spark.apache.org/docs/0.7.2/running-on-mesos.html > > after that the spark shell starts up fine. > then i try the following on the shell: > > val data = 1 to 10000 > > val distData = sc.parallelize(data) > > distData.filter(_< 10).collect() > > open spark web ui at host:4040 and see an active job. > > NOW, how do i start workers or spark workers on mesos ? who completes my > job? > thanks, > > -- > Ani >
