Try Increasing the spark worker memory in conf/spark-env.sh
export SPARK_WORKER_MEMORY=2g
Thanks,
Madhu.
Ratika Prasad
<rprasad@couponsi
nc.com> To
"dev@spark.apache.org"
08/19/2015 09:22 <dev@spark.apache.org>
PM cc
Subject
Unable to run the spark application
in standalone cluster mode
Hi ,
We have a simple spark application which is running through when run
locally on master node as below
./bin/spark-submit --class
com.coupons.salestransactionprocessor.SalesTransactionDataPointCreation
--master local
sales-transaction-processor-0.0.1-SNAPSHOT-jar-with-dependencies.jar
But however I try to run it in cluster mode [ our spark cluster has two
nodes one master and one slave with executer memory of 512MB], the
application fails with the below, Pls provide some inputs as to why?
15/08/19 15:37:52 INFO client.AppClient$ClientActor: Executor updated:
app-20150819153234-0001/8 is now RUNNING
15/08/19 15:37:56 WARN scheduler.TaskSchedulerImpl: Initial job has not
accepted any resources; check your cluster UI to ensure that workers are
registered and have sufficient memory
15/08/19 15:38:11 WARN scheduler.TaskSchedulerImpl: Initial job has not
accepted any resources; check your cluster UI to ensure that workers are
registered and have sufficient memory
15/08/19 15:38:26 WARN scheduler.TaskSchedulerImpl: Initial job has not
accepted any resources; check your cluster UI to ensure that workers are
registered and have sufficient memory
15/08/19 15:38:32 INFO client.AppClient$ClientActor: Executor updated:
app-20150819153234-0001/8 is now EXITED (Command exited with code 1)
15/08/19 15:38:32 INFO cluster.SparkDeploySchedulerBackend: Executor
app-20150819153234-0001/8 removed: Command exited with code 1
15/08/19 15:38:32 INFO client.AppClient$ClientActor: Executor added:
app-20150819153234-0001/9 on
worker-20150812111932-ip-172-28-161-173.us-west-2.compute.internal-50108
(ip-172-28-161-173.us-west-2.compute.internal:50108) with 1 cores
15/08/19 15:38:32 INFO cluster.SparkDeploySchedulerBackend: Granted
executor ID app-20150819153234-0001/9 on hostPort
ip-172-28-161-173.us-west-2.compute.internal:50108 with 1 cores, 512.0 MB
RAM
15/08/19 15:38:32 INFO client.AppClient$ClientActor: Executor updated:
app-20150819153234-0001/9 is now RUNNING
15/08/19 15:38:41 WARN scheduler.TaskSchedulerImpl: Initial job has not
accepted any resources; check your cluster UI to ensure that workers are
registered and have sufficient memory
15/08/19 15:38:56 WARN scheduler.TaskSchedulerImpl: Initial job has not
accepted any resources; check your cluster UI to ensure that workers are
registered and have sufficient memory
15/08/19 15:39:11 WARN scheduler.TaskSchedulerImpl: Initial job has not
accepted any resources; check your cluster UI to ensure that workers are
registered and have sufficient memory
15/08/19 15:39:12 INFO client.AppClient$ClientActor: Executor updated:
app-20150819153234-0001/9 is now EXITED (Command exited with code 1)
15/08/19 15:39:12 INFO cluster.SparkDeploySchedulerBackend: Executor
app-20150819153234-0001/9 removed: Command exited with code 1
15/08/19 15:39:12 ERROR cluster.SparkDeploySchedulerBackend: Application
has been killed. Reason: Master removed our application: FAILED
15/08/19 15:39:12 INFO scheduler.TaskSchedulerImpl: Removed TaskSet 0.0,
whose tasks have all completed, from pool
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/metrics/json,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/stages/stage/kill,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/static,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/executors/json,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/executors,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/environment/json,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/environment,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/storage/rdd/json,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/storage/rdd,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/storage/json,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/storage,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/stages/pool/json,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/stages/pool,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/stages/stage/json,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/stages/stage,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/stages/json,null}
15/08/19 15:39:12 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/stages,null}
15/08/19 15:39:12 INFO scheduler.TaskSchedulerImpl: Cancelling stage 0
15/08/19 15:39:12 INFO scheduler.DAGScheduler: Failed to run count at
SalesTransactionDataPointCreation.java:29
Exception in thread "main" org.apache.spark.SparkException: Job aborted due
to stage failure: Master removed our application: FAILED
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark
$scheduler$DAGScheduler$$failJobAndIndependentStages
(DAGScheduler.scala:1185)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage
$1.apply(DAGScheduler.scala:1174)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage
$1.apply(DAGScheduler.scala:1173)
at scala.collection.mutable.ResizableArray$class.foreach
(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach
(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage
(DAGScheduler.scala:1173)
at org.apache.spark.scheduler.DAGScheduler$$anonfun
$handleTaskSetFailed$1.apply(DAGScheduler.scala:688)
at org.apache.spark.scheduler.DAGScheduler$$anonfun
$handleTaskSetFailed$1.apply(DAGScheduler.scala:688)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed
(DAGScheduler.scala:688)
at org.apache.spark.scheduler.DAGSchedulerEventProcessActor$
$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1391)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at akka.dispatch.ForkJoinExecutorConfigurator$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)
15/08/19 15:39:12 WARN thread.QueuedThreadPool: 8 threads could not be
stopped
15/08/19 15:39:12 INFO ui.SparkUI: Stopped Spark web UI at
http://172.28.161.131:4040
15/08/19 15:39:12 INFO scheduler.DAGScheduler: Stopping DAGScheduler
15/08/19 15:39:12 INFO cluster.SparkDeploySchedulerBackend: Shutting down
all executors
15/08/19 15:39:12 INFO cluster.SparkDeploySchedulerBackend: Asking each
executor to shut down
Thanks
R
