Dear all:
I am a brand new Spark user trying out the SimpleApp from the Quick Start
page.
Here is the code:
object SimpleApp {
def main(args: Array[String]) {
val logFile = "/dev/spark-1.0.2-bin-hadoop2/README.md" // Should be some
file on your system
val conf = new SparkConf()
.setAppName("Simple Application")
.set("spark.executor.memory", "512m")
.setMaster("spark://myhost.local:7077")
.setJars(Seq("/spark-experiments/target/spark-experiments-1.0-SNAPSHOT.jar"))
val sc = new SparkContext(conf)
try {
val logData = sc.textFile(logFile, 2).cache()
val numAs = logData.filter(line => line.contains("a")).count()
val numBs = logData.filter(line => line.contains("b")).count()
println("Lines with a: %s, Lines with b: %s".format(numAs, numBs))
} finally {
sc.stop()
}
}
}
I am using Spark 1.0.2 and Scala 2.10.4. In spark-env.sh I have
SPARK_WORKER_MEMORY=2g.
I am trying to run this as a standalone Java app in my IDE.
Note that this code *does* work when I either
- Change the master to "local" (works running from IDE)
- Run it using spark-submit
The application/driver log is:
14/09/08 10:03:55 INFO spark.SecurityManager: Changing view acls to: eric
14/09/08 10:03:55 INFO spark.SecurityManager: SecurityManager:
authentication disabled; ui acls disabled; users with view permissions:
Set(eric)
14/09/08 10:03:56 INFO slf4j.Slf4jLogger: Slf4jLogger started
14/09/08 10:03:56 INFO Remoting: Starting remoting
14/09/08 10:03:56 INFO Remoting: Remoting started; listening on addresses
:[akka.tcp://spark@10.0.1.5:61645]
14/09/08 10:03:56 INFO Remoting: Remoting now listens on addresses:
[akka.tcp://spark@10.0.1.5:61645]
14/09/08 10:03:56 INFO spark.SparkEnv: Registering MapOutputTracker
14/09/08 10:03:56 INFO spark.SparkEnv: Registering BlockManagerMaster
14/09/08 10:03:56 INFO storage.DiskBlockManager: Created local directory at
/var/folders/j1/5rzyf1x97q9_7gj3mdc79t3c0000gn/T/spark-local-20140908100356-2496
14/09/08 10:03:56 INFO storage.MemoryStore: MemoryStore started with
capacity 279.5 MB.
14/09/08 10:03:56 INFO network.ConnectionManager: Bound socket to port 61646
with id = ConnectionManagerId(10.0.1.5,61646)
14/09/08 10:03:56 INFO storage.BlockManagerMaster: Trying to register
BlockManager
14/09/08 10:03:56 INFO storage.BlockManagerInfo: Registering block manager
10.0.1.5:61646 with 279.5 MB RAM
14/09/08 10:03:56 INFO storage.BlockManagerMaster: Registered BlockManager
14/09/08 10:03:56 INFO spark.HttpServer: Starting HTTP Server
14/09/08 10:03:57 INFO server.Server: jetty-8.1.14.v20131031
14/09/08 10:03:57 INFO server.AbstractConnector: Started
SocketConnector@0.0.0.0:61647
14/09/08 10:03:57 INFO broadcast.HttpBroadcast: Broadcast server started at
http://10.0.1.5:61647
14/09/08 10:03:57 INFO spark.HttpFileServer: HTTP File server directory is
/var/folders/j1/5rzyf1x97q9_7gj3mdc79t3c0000gn/T/spark-d5637279-5caa-4c14-a00f-650f1dd915bc
14/09/08 10:03:57 INFO spark.HttpServer: Starting HTTP Server
14/09/08 10:03:57 INFO server.Server: jetty-8.1.14.v20131031
14/09/08 10:03:57 INFO server.AbstractConnector: Started
SocketConnector@0.0.0.0:61648
14/09/08 10:03:57 INFO server.Server: jetty-8.1.14.v20131031
14/09/08 10:03:57 INFO server.AbstractConnector: Started
SelectChannelConnector@0.0.0.0:4040
14/09/08 10:03:57 INFO ui.SparkUI: Started SparkUI at http://10.0.1.5:4040
2014-09-08 10:03:57.567 java[58736:1703] Unable to load realm info from
SCDynamicStore
14/09/08 10:03:57 INFO spark.SparkContext: Added JAR
/spark-experiments/target/spark-experiments-1.0-SNAPSHOT.jar at
http://10.0.1.5:61648/jars/spark-experiments-1.0-SNAPSHOT.jar with timestamp
1410185037723
14/09/08 10:03:57 INFO client.AppClient$ClientActor: Connecting to master
spark://myhost.local:7077...
14/09/08 10:03:57 INFO storage.MemoryStore: ensureFreeSpace(32960) called
with curMem=0, maxMem=293063884
14/09/08 10:03:57 INFO storage.MemoryStore: Block broadcast_0 stored as
values to memory (estimated size 32.2 KB, free 279.5 MB)
14/09/08 10:03:58 INFO cluster.SparkDeploySchedulerBackend: Connected to
Spark cluster with app ID app-20140908100358-0002
14/09/08 10:03:58 INFO client.AppClient$ClientActor: Executor added:
app-20140908100358-0002/0 on worker-20140908100129-10.0.1.5-61526
(10.0.1.5:61526) with 8 cores
14/09/08 10:03:58 INFO cluster.SparkDeploySchedulerBackend: Granted executor
ID app-20140908100358-0002/0 on hostPort 10.0.1.5:61526 with 8 cores, 512.0
MB RAM
14/09/08 10:03:58 WARN util.NativeCodeLoader: Unable to load native-hadoop
library for your platform... using builtin-java classes where applicable
14/09/08 10:03:58 WARN snappy.LoadSnappy: Snappy native library not loaded
14/09/08 10:03:58 INFO mapred.FileInputFormat: Total input paths to process
: 1
14/09/08 10:03:58 INFO client.AppClient$ClientActor: Executor updated:
app-20140908100358-0002/0 is now RUNNING
14/09/08 10:03:58 INFO spark.SparkContext: Starting job: count at
SimpleApp.scala:16
14/09/08 10:03:58 INFO scheduler.DAGScheduler: Got job 0 (count at
SimpleApp.scala:16) with 2 output partitions (allowLocal=false)
14/09/08 10:03:58 INFO scheduler.DAGScheduler: Final stage: Stage 0(count at
SimpleApp.scala:16)
14/09/08 10:03:58 INFO scheduler.DAGScheduler: Parents of final stage:
List()
14/09/08 10:03:58 INFO scheduler.DAGScheduler: Missing parents: List()
14/09/08 10:03:58 INFO scheduler.DAGScheduler: Submitting Stage 0
(FilteredRDD[2] at filter at SimpleApp.scala:16), which has no missing
parents
14/09/08 10:03:58 INFO scheduler.DAGScheduler: Submitting 2 missing tasks
from Stage 0 (FilteredRDD[2] at filter at SimpleApp.scala:16)
14/09/08 10:03:58 INFO scheduler.TaskSchedulerImpl: Adding task set 0.0 with
2 tasks
14/09/08 10:04:00 INFO cluster.SparkDeploySchedulerBackend: Registered
executor:
Actor[akka.tcp://sparkExecutor@10.0.1.5:61650/user/Executor#281350807] with
ID 0
14/09/08 10:04:01 INFO scheduler.TaskSetManager: Starting task 0.0:0 as TID
0 on executor 0: 10.0.1.5 (PROCESS_LOCAL)
14/09/08 10:04:01 INFO scheduler.TaskSetManager: Serialized task 0.0:0 as
1919 bytes in 2 ms
14/09/08 10:04:01 INFO scheduler.TaskSetManager: Starting task 0.0:1 as TID
1 on executor 0: 10.0.1.5 (PROCESS_LOCAL)
14/09/08 10:04:01 INFO scheduler.TaskSetManager: Serialized task 0.0:1 as
1919 bytes in 0 ms
14/09/08 10:04:01 INFO storage.BlockManagerInfo: Registering block manager
10.0.1.5:61655 with 294.4 MB RAM
14/09/08 10:04:02 INFO client.AppClient$ClientActor: Executor updated:
app-20140908100358-0002/0 is now EXITED (Command exited with code 52)
14/09/08 10:04:02 INFO cluster.SparkDeploySchedulerBackend: Executor 0
disconnected, so removing it
14/09/08 10:04:02 INFO cluster.SparkDeploySchedulerBackend: Executor
app-20140908100358-0002/0 removed: Command exited with code 52
14/09/08 10:04:02 ERROR scheduler.TaskSchedulerImpl: Lost executor 0 on
10.0.1.5: remote Akka client disassociated
14/09/08 10:04:02 INFO scheduler.TaskSetManager: Re-queueing tasks for 0
from TaskSet 0.0
14/09/08 10:04:02 WARN scheduler.TaskSetManager: Lost TID 1 (task 0.0:1)
14/09/08 10:04:02 WARN scheduler.TaskSetManager: Lost TID 0 (task 0.0:0)
14/09/08 10:04:02 INFO client.AppClient$ClientActor: Executor added:
app-20140908100358-0002/1 on worker-20140908100129-10.0.1.5-61526
(10.0.1.5:61526) with 8 cores
14/09/08 10:04:02 INFO cluster.SparkDeploySchedulerBackend: Granted executor
ID app-20140908100358-0002/1 on hostPort 10.0.1.5:61526 with 8 cores, 512.0
MB RAM
14/09/08 10:04:02 INFO scheduler.DAGScheduler: Executor lost: 0 (epoch 0)
14/09/08 10:04:02 INFO client.AppClient$ClientActor: Executor updated:
app-20140908100358-0002/1 is now RUNNING
14/09/08 10:04:02 INFO storage.BlockManagerMasterActor: Trying to remove
executor 0 from BlockManagerMaster.
14/09/08 10:04:02 INFO storage.BlockManagerMaster: Removed 0 successfully in
removeExecutor
14/09/08 10:04:05 INFO cluster.SparkDeploySchedulerBackend: Registered
executor:
Actor[akka.tcp://sparkExecutor@10.0.1.5:61668/user/Executor#162441524] with
ID 1
14/09/08 10:04:05 INFO scheduler.TaskSetManager: Starting task 0.0:0 as TID
2 on executor 1: 10.0.1.5 (PROCESS_LOCAL)
14/09/08 10:04:05 INFO scheduler.TaskSetManager: Serialized task 0.0:0 as
1919 bytes in 0 ms
14/09/08 10:04:05 INFO scheduler.TaskSetManager: Starting task 0.0:1 as TID
3 on executor 1: 10.0.1.5 (PROCESS_LOCAL)
14/09/08 10:04:05 INFO scheduler.TaskSetManager: Serialized task 0.0:1 as
1919 bytes in 0 ms
14/09/08 10:04:05 INFO storage.BlockManagerInfo: Registering block manager
10.0.1.5:61673 with 294.4 MB RAM
14/09/08 10:04:06 INFO cluster.SparkDeploySchedulerBackend: Executor 1
disconnected, so removing it
14/09/08 10:04:06 ERROR scheduler.TaskSchedulerImpl: Lost executor 1 on
10.0.1.5: remote Akka client disassociated
14/09/08 10:04:06 INFO scheduler.TaskSetManager: Re-queueing tasks for 1
from TaskSet 0.0
14/09/08 10:04:06 WARN scheduler.TaskSetManager: Lost TID 2 (task 0.0:0)
14/09/08 10:04:06 WARN scheduler.TaskSetManager: Lost TID 3 (task 0.0:1)
14/09/08 10:04:06 INFO scheduler.DAGScheduler: Executor lost: 1 (epoch 1)
14/09/08 10:04:06 INFO storage.BlockManagerMasterActor: Trying to remove
executor 1 from BlockManagerMaster.
14/09/08 10:04:06 INFO storage.BlockManagerMaster: Removed 1 successfully in
removeExecutor
14/09/08 10:04:06 INFO client.AppClient$ClientActor: Executor updated:
app-20140908100358-0002/1 is now EXITED (Command exited with code 52)
14/09/08 10:04:06 INFO cluster.SparkDeploySchedulerBackend: Executor
app-20140908100358-0002/1 removed: Command exited with code 52
14/09/08 10:04:06 INFO client.AppClient$ClientActor: Executor added:
app-20140908100358-0002/2 on worker-20140908100129-10.0.1.5-61526
(10.0.1.5:61526) with 8 cores
14/09/08 10:04:06 INFO cluster.SparkDeploySchedulerBackend: Granted executor
ID app-20140908100358-0002/2 on hostPort 10.0.1.5:61526 with 8 cores, 512.0
MB RAM
14/09/08 10:04:06 INFO client.AppClient$ClientActor: Executor updated:
app-20140908100358-0002/2 is now RUNNING
14/09/08 10:04:09 INFO cluster.SparkDeploySchedulerBackend: Registered
executor:
Actor[akka.tcp://sparkExecutor@10.0.1.5:61687/user/Executor#-1094963901]
with ID 2
14/09/08 10:04:09 INFO scheduler.TaskSetManager: Starting task 0.0:1 as TID
4 on executor 2: 10.0.1.5 (PROCESS_LOCAL)
14/09/08 10:04:09 INFO scheduler.TaskSetManager: Serialized task 0.0:1 as
1919 bytes in 0 ms
14/09/08 10:04:09 INFO scheduler.TaskSetManager: Starting task 0.0:0 as TID
5 on executor 2: 10.0.1.5 (PROCESS_LOCAL)
14/09/08 10:04:09 INFO scheduler.TaskSetManager: Serialized task 0.0:0 as
1919 bytes in 1 ms
14/09/08 10:04:10 INFO storage.BlockManagerInfo: Registering block manager
10.0.1.5:61692 with 294.4 MB RAM
14/09/08 10:04:11 INFO cluster.SparkDeploySchedulerBackend: Executor 2
disconnected, so removing it
14/09/08 10:04:11 ERROR scheduler.TaskSchedulerImpl: Lost executor 2 on
10.0.1.5: remote Akka client disassociated
14/09/08 10:04:11 INFO scheduler.TaskSetManager: Re-queueing tasks for 2
from TaskSet 0.0
14/09/08 10:04:11 WARN scheduler.TaskSetManager: Lost TID 5 (task 0.0:0)
14/09/08 10:04:11 WARN scheduler.TaskSetManager: Lost TID 4 (task 0.0:1)
14/09/08 10:04:11 INFO scheduler.DAGScheduler: Executor lost: 2 (epoch 2)
14/09/08 10:04:11 INFO storage.BlockManagerMasterActor: Trying to remove
executor 2 from BlockManagerMaster.
14/09/08 10:04:11 INFO storage.BlockManagerMaster: Removed 2 successfully in
removeExecutor
14/09/08 10:04:11 INFO client.AppClient$ClientActor: Executor updated:
app-20140908100358-0002/2 is now EXITED (Command exited with code 52)
14/09/08 10:04:11 INFO cluster.SparkDeploySchedulerBackend: Executor
app-20140908100358-0002/2 removed: Command exited with code 52
14/09/08 10:04:11 INFO client.AppClient$ClientActor: Executor added:
app-20140908100358-0002/3 on worker-20140908100129-10.0.1.5-61526
(10.0.1.5:61526) with 8 cores
14/09/08 10:04:11 INFO cluster.SparkDeploySchedulerBackend: Granted executor
ID app-20140908100358-0002/3 on hostPort 10.0.1.5:61526 with 8 cores, 512.0
MB RAM
14/09/08 10:04:11 INFO client.AppClient$ClientActor: Executor updated:
app-20140908100358-0002/3 is now RUNNING
14/09/08 10:04:14 INFO cluster.SparkDeploySchedulerBackend: Registered
executor:
Actor[akka.tcp://sparkExecutor@10.0.1.5:61705/user/Executor#-460934085] with
ID 3
14/09/08 10:04:14 INFO scheduler.TaskSetManager: Starting task 0.0:1 as TID
6 on executor 3: 10.0.1.5 (PROCESS_LOCAL)
14/09/08 10:04:14 INFO scheduler.TaskSetManager: Serialized task 0.0:1 as
1919 bytes in 0 ms
14/09/08 10:04:14 INFO scheduler.TaskSetManager: Starting task 0.0:0 as TID
7 on executor 3: 10.0.1.5 (PROCESS_LOCAL)
14/09/08 10:04:14 INFO scheduler.TaskSetManager: Serialized task 0.0:0 as
1919 bytes in 1 ms
14/09/08 10:04:14 INFO storage.BlockManagerInfo: Registering block manager
10.0.1.5:61710 with 294.4 MB RAM
14/09/08 10:04:15 INFO cluster.SparkDeploySchedulerBackend: Executor 3
disconnected, so removing it
14/09/08 10:04:15 ERROR scheduler.TaskSchedulerImpl: Lost executor 3 on
10.0.1.5: remote Akka client disassociated
14/09/08 10:04:15 INFO scheduler.TaskSetManager: Re-queueing tasks for 3
from TaskSet 0.0
14/09/08 10:04:15 WARN scheduler.TaskSetManager: Lost TID 7 (task 0.0:0)
14/09/08 10:04:15 ERROR scheduler.TaskSetManager: Task 0.0:0 failed 4 times;
aborting job
14/09/08 10:04:15 INFO scheduler.TaskSchedulerImpl: Removed TaskSet 0.0,
whose tasks have all completed, from pool
14/09/08 10:04:15 INFO scheduler.TaskSchedulerImpl: Cancelling stage 0
14/09/08 10:04:15 INFO scheduler.DAGScheduler: Failed to run count at
SimpleApp.scala:16
14/09/08 10:04:15 INFO client.AppClient$ClientActor: Executor updated:
app-20140908100358-0002/3 is now EXITED (Command exited with code 52)
14/09/08 10:04:15 INFO cluster.SparkDeploySchedulerBackend: Executor
app-20140908100358-0002/3 removed: Command exited with code 52
14/09/08 10:04:15 INFO client.AppClient$ClientActor: Executor added:
app-20140908100358-0002/4 on worker-20140908100129-10.0.1.5-61526
(10.0.1.5:61526) with 8 cores
14/09/08 10:04:15 INFO cluster.SparkDeploySchedulerBackend: Granted executor
ID app-20140908100358-0002/4 on hostPort 10.0.1.5:61526 with 8 cores, 512.0
MB RAM
14/09/08 10:04:15 INFO scheduler.DAGScheduler: Executor lost: 3 (epoch 3)
14/09/08 10:04:15 INFO storage.BlockManagerMasterActor: Trying to remove
executor 3 from BlockManagerMaster.
14/09/08 10:04:15 INFO storage.BlockManagerMaster: Removed 3 successfully in
removeExecutor
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/metrics/json,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/stages/stage/kill,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/static,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/executors/json,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/executors,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/environment/json,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/environment,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/storage/rdd/json,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/storage/rdd,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/storage/json,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/storage,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/stages/pool/json,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/stages/pool,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/stages/stage/json,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/stages/stage,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/stages/json,null}
14/09/08 10:04:15 INFO handler.ContextHandler: stopped
o.e.j.s.ServletContextHandler{/stages,null}
14/09/08 10:04:15 INFO client.AppClient$ClientActor: Executor updated:
app-20140908100358-0002/4 is now RUNNING
14/09/08 10:04:15 INFO ui.SparkUI: Stopped Spark web UI at
http://10.0.1.5:4040
14/09/08 10:04:15 INFO scheduler.DAGScheduler: Stopping DAGScheduler
14/09/08 10:04:15 INFO cluster.SparkDeploySchedulerBackend: Shutting down
all executors
14/09/08 10:04:15 INFO cluster.SparkDeploySchedulerBackend: Asking each
executor to shut down
14/09/08 10:04:16 INFO spark.MapOutputTrackerMasterActor:
MapOutputTrackerActor stopped!
14/09/08 10:04:16 INFO network.ConnectionManager: Selector thread was
interrupted!
14/09/08 10:04:16 INFO network.ConnectionManager: ConnectionManager stopped
14/09/08 10:04:16 INFO storage.MemoryStore: MemoryStore cleared
14/09/08 10:04:16 INFO storage.BlockManager: BlockManager stopped
14/09/08 10:04:16 INFO storage.BlockManagerMasterActor: Stopping
BlockManagerMaster
14/09/08 10:04:17 INFO storage.BlockManagerMaster: BlockManagerMaster
stopped
14/09/08 10:04:17 INFO spark.SparkContext: Successfully stopped SparkContext
Exception in thread "main" org.apache.spark.SparkException: Job aborted due
to stage failure: Task 0.0:0 failed 4 times, most recent failure: TID 7 on
host 10.0.1.5 failed for unknown reason
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1049)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1033)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1031)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1031)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:635)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:635)
at scala.Option.foreach(Option.scala:236)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:635)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1234)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at
akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at
scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at
scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at
scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
14/09/08 10:04:17 INFO remote.RemoteActorRefProvider$RemotingTerminator:
Shutting down remote daemon.
The stderr log from the executor is:
Spark Executor Command:
"/Library/Java/JavaVirtualMachines/jdk1.7.0_13.jdk/Contents/Home/bin/java"
"-cp"
"::/dev/spark-1.0.2-bin-hadoop2/conf:/dev/spark-1.0.2-bin-hadoop2/lib/spark-assembly-1.0.2-hadoop2.2.0.jar:/dev/spark-1.0.2-bin-hadoop2/lib/datanucleus-api-jdo-3.2.1.jar:/Users/dev/spark-1.0.2-bin-hadoop2/lib/datanucleus-core-3.2.2.jar:/dev/spark-1.0.2-bin-hadoop2/lib/datanucleus-rdbms-3.2.1.jar"
"-XX:MaxPermSize=128m" "-Xms512M" "-Xmx512M"
"org.apache.spark.executor.CoarseGrainedExecutorBackend"
"akka.tcp://spark@10.0.1.5:61645/user/CoarseGrainedScheduler" "1" "10.0.1.5"
"8" "akka.tcp://sparkWorker@10.0.1.5:61526/user/Worker"
"app-20140908100358-0002"
========================================
2014-09-08 10:04:04.202 java[58774:1703] Unable to load realm info from
SCDynamicStore
14/09/08 10:04:04 WARN NativeCodeLoader: Unable to load native-hadoop
library for your platform... using builtin-java classes where applicable
14/09/08 10:04:04 INFO SecurityManager: Changing view acls to: eric
14/09/08 10:04:04 INFO SecurityManager: SecurityManager: authentication
disabled; ui acls disabled; users with view permissions: Set(eric)
14/09/08 10:04:05 INFO Slf4jLogger: Slf4jLogger started
14/09/08 10:04:05 INFO Remoting: Starting remoting
14/09/08 10:04:05 INFO Remoting: Remoting started; listening on addresses
:[akka.tcp://sparkExecutor@10.0.1.5:61668]
14/09/08 10:04:05 INFO Remoting: Remoting now listens on addresses:
[akka.tcp://sparkExecutor@10.0.1.5:61668]
14/09/08 10:04:05 INFO CoarseGrainedExecutorBackend: Connecting to driver:
akka.tcp://spark@10.0.1.5:61645/user/CoarseGrainedScheduler
14/09/08 10:04:05 INFO WorkerWatcher: Connecting to worker
akka.tcp://sparkWorker@10.0.1.5:61526/user/Worker
14/09/08 10:04:05 INFO WorkerWatcher: Successfully connected to
akka.tcp://sparkWorker@10.0.1.5:61526/user/Worker
14/09/08 10:04:05 INFO CoarseGrainedExecutorBackend: Successfully registered
with driver
14/09/08 10:04:05 INFO SecurityManager: Changing view acls to: eric
14/09/08 10:04:05 INFO SecurityManager: SecurityManager: authentication
disabled; ui acls disabled; users with view permissions: Set(eric)
14/09/08 10:04:05 INFO Slf4jLogger: Slf4jLogger started
14/09/08 10:04:05 INFO Remoting: Starting remoting
14/09/08 10:04:05 INFO Remoting: Remoting started; listening on addresses
:[akka.tcp://spark@10.0.1.5:61671]
14/09/08 10:04:05 INFO Remoting: Remoting now listens on addresses:
[akka.tcp://spark@10.0.1.5:61671]
14/09/08 10:04:05 INFO SparkEnv: Connecting to MapOutputTracker:
akka.tcp://spark@10.0.1.5:61645/user/MapOutputTracker
14/09/08 10:04:05 INFO SparkEnv: Connecting to BlockManagerMaster:
akka.tcp://spark@10.0.1.5:61645/user/BlockManagerMaster
14/09/08 10:04:05 INFO DiskBlockManager: Created local directory at
/var/folders/j1/5rzyf1x97q9_7gj3mdc79t3c0000gn/T/spark-local-20140908100405-509f
14/09/08 10:04:05 INFO MemoryStore: MemoryStore started with capacity 294.4
MB.
14/09/08 10:04:05 INFO ConnectionManager: Bound socket to port 61673 with id
= ConnectionManagerId(10.0.1.5,61673)
14/09/08 10:04:05 INFO BlockManagerMaster: Trying to register BlockManager
14/09/08 10:04:05 INFO BlockManagerMaster: Registered BlockManager
14/09/08 10:04:05 INFO HttpFileServer: HTTP File server directory is
/var/folders/j1/5rzyf1x97q9_7gj3mdc79t3c0000gn/T/spark-3bb0c7fb-be2f-4efe-9dde-bcf8349a962a
14/09/08 10:04:05 INFO HttpServer: Starting HTTP Server
14/09/08 10:04:05 INFO CoarseGrainedExecutorBackend: Got assigned task 2
14/09/08 10:04:06 INFO CoarseGrainedExecutorBackend: Got assigned task 3
14/09/08 10:04:06 INFO Executor: Running task ID 2
14/09/08 10:04:06 INFO Executor: Running task ID 3
14/09/08 10:04:06 INFO Executor: Fetching
http://10.0.1.5:61648/jars/spark-experiments-1.0-SNAPSHOT.jar with timestamp
1410185037723
14/09/08 10:04:06 INFO Utils: Fetching
http://10.0.1.5:61648/jars/spark-experiments-1.0-SNAPSHOT.jar to
/var/folders/j1/5rzyf1x97q9_7gj3mdc79t3c0000gn/T/fetchFileTemp4194990807172315371.tmp
14/09/08 10:04:06 INFO Executor: Adding
file:/dev/spark-1.0.2-bin-hadoop2/work/app-20140908100358-0002/1/./spark-experiments-1.0-SNAPSHOT.jar
to class loader
14/09/08 10:04:06 INFO HttpBroadcast: Started reading broadcast variable 0
14/09/08 10:04:06 ERROR Executor: Exception in task ID 2
java.lang.OutOfMemoryError: Java heap space
at
org.apache.hadoop.io.WritableUtils.readCompressedStringArray(WritableUtils.java:183)
at
org.apache.hadoop.conf.Configuration.readFields(Configuration.java:2378)
at
org.apache.hadoop.io.ObjectWritable.readObject(ObjectWritable.java:285)
at
org.apache.hadoop.io.ObjectWritable.readFields(ObjectWritable.java:77)
at
org.apache.spark.SerializableWritable.readObject(SerializableWritable.scala:42)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:601)
at
java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1004)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1872)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1777)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1347)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:369)
at
org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:63)
at
org.apache.spark.broadcast.HttpBroadcast$.read(HttpBroadcast.scala:205)
at
org.apache.spark.broadcast.HttpBroadcast.readObject(HttpBroadcast.scala:89)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:601)
at
java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1004)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1872)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1777)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1347)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1970)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1894)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1777)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1347)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1970)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1894)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1777)
14/09/08 10:04:06 INFO HttpBroadcast: Started reading broadcast variable 0
14/09/08 10:04:06 ERROR ExecutorUncaughtExceptionHandler: Uncaught exception
in thread Thread[Executor task launch worker-0,5,main]
java.lang.OutOfMemoryError: Java heap space
at
org.apache.hadoop.io.WritableUtils.readCompressedStringArray(WritableUtils.java:183)
at
org.apache.hadoop.conf.Configuration.readFields(Configuration.java:2378)
at
org.apache.hadoop.io.ObjectWritable.readObject(ObjectWritable.java:285)
at
org.apache.hadoop.io.ObjectWritable.readFields(ObjectWritable.java:77)
at
org.apache.spark.SerializableWritable.readObject(SerializableWritable.scala:42)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:601)
at
java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1004)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1872)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1777)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1347)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:369)
at
org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:63)
at
org.apache.spark.broadcast.HttpBroadcast$.read(HttpBroadcast.scala:205)
at
org.apache.spark.broadcast.HttpBroadcast.readObject(HttpBroadcast.scala:89)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at
sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:601)
at
java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1004)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1872)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1777)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1347)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1970)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1894)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1777)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1347)
at
java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1970)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1894)
at
java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1777)
It seems like a serialization problem because there is plenty of heap space
(and it works with spark-submit).
Thanks!
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