Its not recommended to have multiple spark contexts in one JVM, but you
could launch a separate JVM per context. How resources get allocated is
probably outside the scope of Spark, and more of a task for the cluster
manager.

On Fri, Nov 14, 2014 at 12:58 PM, Charles <charles...@cenx.com> wrote:

> I need continuously run multiple calculations concurrently on a cluster.
> They
> are not sharing RDDs.
> Each of the calculations needs different number of cores and memory. Also,
> some of them are long running calculation and others are short running
> calculation.They all need be run on regular basis and finish in time. The
> short ones cannot wait until long ones to finish. They cannot run too slow
> either since the short ones' running interval is short as well.
>
> It looks like the sharing inside a sparkContext cannot guarantee that the
> short ones will get enough resources to finish in time if long ones already
> running. Or am I wrong about that?
>
>  I tried to create a sparkContext for each of the calculations but only the
> first one is alive. The rest dies. I am getting the error below. Is it
> possible to create multiple sparkContext from inside one application jvm?
>
> ERROR 2014-11-14 14:59:46 akka.actor.OneForOneStrategy:
> spark.httpBroadcast.uri
> java.util.NoSuchElementException: spark.httpBroadcast.uri
> at org.apache.spark.SparkConf$$anonfun$get$1.apply(SparkConf.scala:151)
> at org.apache.spark.SparkConf$$anonfun$get$1.apply(SparkConf.scala:151)
> at scala.collection.MapLike$class.getOrElse(MapLike.scala:128)
> at scala.collection.AbstractMap.getOrElse(Map.scala:58)
> at org.apache.spark.SparkConf.get(SparkConf.scala:151)
> at
>
> org.apache.spark.broadcast.HttpBroadcast$.initialize(HttpBroadcast.scala:104)
> at
>
> org.apache.spark.broadcast.HttpBroadcastFactory.initialize(HttpBroadcast.scala:70)
> at
> org.apache.spark.broadcast.BroadcastManager.initialize(Broadcast.scala:81)
> at org.apache.spark.broadcast.BroadcastManager.<init>(Broadcast.scala:68)
> at org.apache.spark.SparkEnv$.create(SparkEnv.scala:175)
> at org.apache.spark.executor.Executor.<init>(Executor.scala:110)
> at
>
> org.apache.spark.executor.CoarseGrainedExecutorBackend$$anonfun$receive$1.applyOrElse(CoarseGrainedExecutorBackend.scala:56)
> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
> at akka.actor.ActorCell.invoke(ActorCell.scala:456)
> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
> at akka.dispatch.Mailbox.run(Mailbox.scala:219)
> at
>
> akka.dispatch.ForkJoinExecutorConfigurator$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)
> INFO 2014-11-14 14:59:46
> org.apache.spark.executor.CoarseGrainedExecutorBackend: Connecting to
> driver: akka.tcp://spark@172.32.1.12:51590/user/CoarseGrainedScheduler
> ERROR 2014-11-14 14:59:46
> org.apache.spark.executor.CoarseGrainedExecutorBackend: Slave registration
> failed: Duplicate executor ID: 1
>
>
>
> --
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