I'm running a job on a test Spark standalone in cluster mode, but I'm finding myself unable to monitor the status of the driver.
Here is a minimal example using spark-2.4.3 (master and one worker running on the same node, started running sbin/start-all.sh on a freshly unarchived installation using the default conf, no conf/slaves set), executing spark-submit from the node itself:
$ spark-submit --master spark://ip-172-31-15-245:7077 --deploy-mode cluster \
--class org.apache.spark.examples.SparkPi \
/home/ubuntu/spark/examples/jars/spark-examples_2.11-2.4.3.jar 100
log4j:WARN No appenders could be found for logger (org.apache.hadoop.util.NativeCodeLoader).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
19/06/27 09:08:28 INFO SecurityManager: Changing view acls to: ubuntu
19/06/27 09:08:28 INFO SecurityManager: Changing modify acls to: ubuntu
19/06/27 09:08:28 INFO SecurityManager: Changing view acls groups to:
19/06/27 09:08:28 INFO SecurityManager: Changing modify acls groups to:
19/06/27 09:08:28 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(ubuntu); groups with view permissions: Set(); users with modify permissions: Set(ubuntu); groups with modify permissions: Set()
19/06/27 09:08:28 INFO Utils: Successfully started service 'driverClient' on port 36067.
19/06/27 09:08:28 INFO TransportClientFactory: Successfully created connection to ip-172-31-15-245/172.31.15.245:7077 after 29 ms (0 ms spent in bootstraps)
19/06/27 09:08:28 INFO ClientEndpoint: Driver successfully submitted as driver-20190627090828-0008
19/06/27 09:08:28 INFO ClientEndpoint: ... waiting before polling master for driver state
19/06/27 09:08:33 INFO ClientEndpoint: ... polling master for driver state
19/06/27 09:08:33 INFO ClientEndpoint: State of driver-20190627090828-0008 is RUNNING
19/06/27 09:08:33 INFO ClientEndpoint: Driver running on 172.31.15.245:41057 (worker-20190627083412-172.31.15.245-41057)
19/06/27 09:08:33 INFO ShutdownHookManager: Shutdown hook called
19/06/27 09:08:33 INFO ShutdownHookManager: Deleting directory /tmp/spark-34082661-f0de-4c56-92b7-648ea24fa59c
> spark-submit --master spark://ip-172-31-15-245:7077 --status driver-20190627090828-0008
19/06/27 09:09:27 WARN RestSubmissionClient: Unable to connect to server spark://ip-172-31-15-245:7077.
Exception in thread "main" org.apache.spark.deploy.rest.SubmitRestConnectionException: Unable to connect to server
at org.apache.spark.deploy.rest.RestSubmissionClient$$anonfun$requestSubmissionStatus$3.apply(RestSubmissionClient.scala:165)
at org.apache.spark.deploy.rest.RestSubmissionClient$$anonfun$requestSubmissionStatus$3.apply(RestSubmissionClient.scala:148)
at scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:733)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:732)
at org.apache.spark.deploy.rest.RestSubmissionClient.requestSubmissionStatus(RestSubmissionClient.scala:148)
at org.apache.spark.deploy.SparkSubmit.requestStatus(SparkSubmit.scala:111)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:88)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:924)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:933)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: org.apache.spark.deploy.rest.SubmitRestConnectionException: No response from server
at org.apache.spark.deploy.rest.RestSubmissionClient.readResponse(RestSubmissionClient.scala:285)
at org.apache.spark.deploy.rest.RestSubmissionClient.org$apache$spark$deploy$rest$RestSubmissionClient$$get(RestSubmissionClient.scala:195)
at org.apache.spark.deploy.rest.RestSubmissionClient$$anonfun$requestSubmissionStatus$3.apply(RestSubmissionClient.scala:152)
... 11 more
Caused by: java.util.concurrent.TimeoutException: Futures timed out after [10 seconds]
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:223)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:227)
at scala.concurrent.Await$$anonfun$result$1.apply(package.scala:190)
at scala.concurrent.BlockContext$DefaultBlockContext$.blockOn(BlockContext.scala:53)
at scala.concurrent.Await$.result(package.scala:190)
at org.apache.spark.deploy.rest.RestSubmissionClient.readResponse(RestSubmissionClient.scala:278)
... 13 more
Spark is in good health (I'm able to run other jobs after the one above), the driver-20190627090828-0008 appears as "FINISHED" in the web UI.
Is there something I am missing?
UPDATE:
on the master log all I get is
19/07/01 09:40:24 INFO master.Master: 172.31.15.245:42308 got disassociated, removing it.
Related
I'm trying to run spark on kubernetes(using minikube with VirtualBox or docker driver, I tested in both) and now I have an error that I don't know how to solve.
The error is a "SparkException: External scheduler cannot be instantiated". I'm new in Kubernetes world, so I really don't know if this is a newbie error, but trying to resolve by myself I failed.
Please help me.
In the next lines, follow the command and the error.
I use this spark submit command:
spark-submit --master k8s://https://192.168.99.102:8443 \
--deploy-mode cluster \
--name spark-pi \
--class org.apache.spark.examples.SparkPi \
--conf spark.executor.instances=2 \
--executor-memory 1024m \
--conf spark.kubernetes.container.image=spark:latest \
local:///opt/spark/examples/jars/spark-examples_2.12-3.0.0.jar
And i got this error in the pod:
20/06/23 15:24:56 INFO SparkContext: Submitted application: Spark Pi
20/06/23 15:24:56 INFO SecurityManager: Changing view acls to: 185,luan
20/06/23 15:24:56 INFO SecurityManager: Changing modify acls to: 185,luan
20/06/23 15:24:56 INFO SecurityManager: Changing view acls groups to:
20/06/23 15:24:56 INFO SecurityManager: Changing modify acls groups to:
20/06/23 15:24:56 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(185, luan); groups with view permissions: Set(); users with modify permissions: Set(185, luan); groups with modify permissions: Set()
20/06/23 15:24:57 INFO Utils: Successfully started service 'sparkDriver' on port 7078.
20/06/23 15:24:57 INFO SparkEnv: Registering MapOutputTracker
20/06/23 15:24:57 INFO SparkEnv: Registering BlockManagerMaster
20/06/23 15:24:57 INFO BlockManagerMasterEndpoint: Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
20/06/23 15:24:57 INFO BlockManagerMasterEndpoint: BlockManagerMasterEndpoint up
20/06/23 15:24:57 INFO SparkEnv: Registering BlockManagerMasterHeartbeat
20/06/23 15:24:57 INFO DiskBlockManager: Created local directory at /var/data/spark-4f7b787b-ec75-4ae5-b703-f9f90ef130cb/blockmgr-1ef6d02a-48f6-4bd7-9d7d-fe2518850f5e
20/06/23 15:24:57 INFO MemoryStore: MemoryStore started with capacity 413.9 MiB
20/06/23 15:24:57 INFO SparkEnv: Registering OutputCommitCoordinator
20/06/23 15:24:57 INFO Utils: Successfully started service 'SparkUI' on port 4040.
20/06/23 15:24:57 INFO SparkUI: Bound SparkUI to 0.0.0.0, and started at http://spark-pi-a8278472e1c83236-driver-svc.default.svc:4040
20/06/23 15:24:57 INFO SparkContext: Added JAR local:///opt/spark/examples/jars/spark-examples_2.12-3.0.0.jar at file:/opt/spark/examples/jars/spark-examples_2.12-3.0.0.jar with timestamp 1592925897650
20/06/23 15:24:57 WARN SparkContext: The jar local:///opt/spark/examples/jars/spark-examples_2.12-3.0.0.jar has been added already. Overwriting of added jars is not supported in the current version.
20/06/23 15:24:57 INFO SparkKubernetesClientFactory: Auto-configuring K8S client using current context from users K8S config file
20/06/23 15:24:58 ERROR SparkContext: Error initializing SparkContext.
org.apache.spark.SparkException: External scheduler cannot be instantiated
at org.apache.spark.SparkContext$.org$apache$spark$SparkContext$$createTaskScheduler(SparkContext.scala:2934)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:528)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2555)
at org.apache.spark.sql.SparkSession$Builder.$anonfun$getOrCreate$1(SparkSession.scala:930)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:921)
at org.apache.spark.examples.SparkPi$.main(SparkPi.scala:30)
at org.apache.spark.examples.SparkPi.main(SparkPi.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:928)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:203)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1007)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1016)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: io.fabric8.kubernetes.client.KubernetesClientException: Failure executing: GET at: https://kubernetes.default.svc/api/v1/namespaces/default/pods/spark-pi-a8278472e1c83236-driver. Message: Forbidden!Configured service account doesn't have access. Service account may have been revoked. pods "spark-pi-a8278472e1c83236-driver" is forbidden: User "system:serviceaccount:default:default" cannot get resource "pods" in API group "" in the namespace "default".
at io.fabric8.kubernetes.client.dsl.base.OperationSupport.requestFailure(OperationSupport.java:568)
at io.fabric8.kubernetes.client.dsl.base.OperationSupport.assertResponseCode(OperationSupport.java:505)
at io.fabric8.kubernetes.client.dsl.base.OperationSupport.handleResponse(OperationSupport.java:471)
at io.fabric8.kubernetes.client.dsl.base.OperationSupport.handleResponse(OperationSupport.java:430)
at io.fabric8.kubernetes.client.dsl.base.OperationSupport.handleGet(OperationSupport.java:395)
at io.fabric8.kubernetes.client.dsl.base.OperationSupport.handleGet(OperationSupport.java:376)
at io.fabric8.kubernetes.client.dsl.base.BaseOperation.handleGet(BaseOperation.java:845)
at io.fabric8.kubernetes.client.dsl.base.BaseOperation.getMandatory(BaseOperation.java:214)
at io.fabric8.kubernetes.client.dsl.base.BaseOperation.get(BaseOperation.java:168)
at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.$anonfun$driverPod$1(ExecutorPodsAllocator.scala:59)
at scala.Option.map(Option.scala:230)
at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.<init>(ExecutorPodsAllocator.scala:58)
at org.apache.spark.scheduler.cluster.k8s.KubernetesClusterManager.createSchedulerBackend(KubernetesClusterManager.scala:113)
at org.apache.spark.SparkContext$.org$apache$spark$SparkContext$$createTaskScheduler(SparkContext.scala:2928)
... 19 more
20/06/23 15:24:58 INFO SparkUI: Stopped Spark web UI at http://spark-pi-a8278472e1c83236-driver-svc.default.svc:4040
20/06/23 15:24:58 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
20/06/23 15:24:58 INFO MemoryStore: MemoryStore cleared
20/06/23 15:24:58 INFO BlockManager: BlockManager stopped
20/06/23 15:24:58 INFO BlockManagerMaster: BlockManagerMaster stopped
20/06/23 15:24:58 WARN MetricsSystem: Stopping a MetricsSystem that is not running
20/06/23 15:24:58 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
20/06/23 15:24:58 INFO SparkContext: Successfully stopped SparkContext
Exception in thread "main" org.apache.spark.SparkException: External scheduler cannot be instantiated
at org.apache.spark.SparkContext$.org$apache$spark$SparkContext$$createTaskScheduler(SparkContext.scala:2934)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:528)
at org.apache.spark.SparkContext$.getOrCreate(SparkContext.scala:2555)
at org.apache.spark.sql.SparkSession$Builder.$anonfun$getOrCreate$1(SparkSession.scala:930)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:921)
at org.apache.spark.examples.SparkPi$.main(SparkPi.scala:30)
at org.apache.spark.examples.SparkPi.main(SparkPi.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:928)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:203)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1007)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1016)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: io.fabric8.kubernetes.client.KubernetesClientException: Failure executing: GET at: https://kubernetes.default.svc/api/v1/namespaces/default/pods/spark-pi-a8278472e1c83236-driver. Message: Forbidden!Configured service account doesn't have access. Service account may have been revoked. pods "spark-pi-a8278472e1c83236-driver" is forbidden: User "system:serviceaccount:default:default" cannot get resource "pods" in API group "" in the namespace "default".
at io.fabric8.kubernetes.client.dsl.base.OperationSupport.requestFailure(OperationSupport.java:568)
at io.fabric8.kubernetes.client.dsl.base.OperationSupport.assertResponseCode(OperationSupport.java:505)
at io.fabric8.kubernetes.client.dsl.base.OperationSupport.handleResponse(OperationSupport.java:471)
at io.fabric8.kubernetes.client.dsl.base.OperationSupport.handleResponse(OperationSupport.java:430)
at io.fabric8.kubernetes.client.dsl.base.OperationSupport.handleGet(OperationSupport.java:395)
at io.fabric8.kubernetes.client.dsl.base.OperationSupport.handleGet(OperationSupport.java:376)
at io.fabric8.kubernetes.client.dsl.base.BaseOperation.handleGet(BaseOperation.java:845)
at io.fabric8.kubernetes.client.dsl.base.BaseOperation.getMandatory(BaseOperation.java:214)
at io.fabric8.kubernetes.client.dsl.base.BaseOperation.get(BaseOperation.java:168)
at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.$anonfun$driverPod$1(ExecutorPodsAllocator.scala:59)
at scala.Option.map(Option.scala:230)
at org.apache.spark.scheduler.cluster.k8s.ExecutorPodsAllocator.<init>(ExecutorPodsAllocator.scala:58)
at org.apache.spark.scheduler.cluster.k8s.KubernetesClusterManager.createSchedulerBackend(KubernetesClusterManager.scala:113)
at org.apache.spark.SparkContext$.org$apache$spark$SparkContext$$createTaskScheduler(SparkContext.scala:2928)
... 19 more
20/06/23 15:24:58 INFO ShutdownHookManager: Shutdown hook called
20/06/23 15:24:58 INFO ShutdownHookManager: Deleting directory /var/data/spark-4f7b787b-ec75-4ae5-b703-f9f90ef130cb/spark-616edc5e-b42d-4c77-9f11-8465b4d69642
20/06/23 15:24:58 INFO ShutdownHookManager: Deleting directory /tmp/spark-71e3bd59-3b7d-4d72-a442-b0ad0c7092fb
Thank You!
Ps: Im using Spark 3.0 - new version, minikube - 1.11.0
Based on the log file:
Message: Forbidden!Configured service account doesn't have access. Service account may have been revoked. pods "spark-pi-a8278472e1c83236-driver" is forbidden: User "system:serviceaccount:default:default" cannot get resource "pods" in API group "" in the namespace "default".
It looks like the default:default service account doesn't have edit permissions. You can run this to create the ClusterRoleBinding to add the permissions.
$ kubectl create clusterrolebinding default \
--clusterrole=edit --serviceaccount=default:default --namespace=default
You can take a look at this cheat sheet.
i am trying to deploy Spark 2.0 Streaming over Amazon EMR 5.0.
it seems that the application is getting stuck at endless loop with the log
"endless loop of "INFO Client: Application report for application_14111979683_1111 (state: ACCEPTED)"
and then exit.
Here is how i am trying to submit it through the command line:
aws emr add-steps --cluster-id --steps
Type=Spark,Name="Spark
Program",ActionOnFailure=CONTINUE,Args=[--deploy-mode,cluster,--class,,s3://.jar]
any idea ?
thanks,
Eran
16/08/30 15:43:27 INFO SecurityManager: Changing view acls to: hadoop
16/08/30 15:43:27 INFO SecurityManager: Changing modify acls to: hadoop
16/08/30 15:43:27 INFO SecurityManager: Changing view acls groups to:
16/08/30 15:43:27 INFO SecurityManager: Changing modify acls groups to:
16/08/30 15:43:27 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(hadoop); groups with view permissions: Set(); users with modify permissions: Set(hadoop); groups with modify permissions: Set()
16/08/30 15:43:27 INFO Client: Submitting application application_14111979683_1111 to ResourceManager
16/08/30 15:43:27 INFO YarnClientImpl: Submitted application application_14111979683_1111
16/08/30 15:43:28 INFO Client: Application report for application_14111979683_1111 (state: ACCEPTED)
16/08/30 15:43:28 INFO Client:
client token: N/A
diagnostics: N/A
ApplicationMaster host: N/A
ApplicationMaster RPC port: -1
queue: default
start time: 1472571807467
final status: UNDEFINED
tracking URL: http://xxxxxx:20888/proxy/application_14111979683_1111/
user: hadoop
16/08/30 15:43:29 INFO Client: Application report for application_14111979683_1111 (state: ACCEPTED)
and this the exception thrown:
16/08/31 08:14:48 INFO Client:
client token: N/A
diagnostics: Application application_1472630652740_0001 failed 2 times due to AM Container for appattempt_1472630652740_0001_000002 exited with exitCode: 13
For more detailed output, check application tracking page:http://ip-10-0-0-8.eu-west-1.compute.internal:8088/cluster/app/application_1472630652740_0001Then, click on links to logs of each attempt.
Diagnostics: Exception from container-launch.
Container id: container_1472630652740_0001_02_000001
Exit code: 13
Stack trace: ExitCodeException exitCode=13:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:545)
at org.apache.hadoop.util.Shell.run(Shell.java:456)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:722)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
EMR is actually a wrapper to Yarn.
so, we need to add "--master yarn" as an argument to the deployment command line.
Example:
aws emr add-steps --cluster-id j-XXXXXXXXX --steps Type=Spark,Name="Spark Program",ActionOnFailure=CONTINUE,Args=[--deploy-mode,cluster,--master,yarn,--class,com.xxx.MyMainClass,s3://]
Another thing which is needed, is removing 'sparkConf.setMaster("local[*]")',
from the initialization of spark conf.
While starting the worker node I get the following error :
Spark Command: /usr/lib/jvm/default-java/bin/java -cp /home/ubuntu/spark-1.5.1-bin-hadoop2.6/sbin/../conf/:/home/ubuntu/spark-1.5.1-bin-hadoop2.6/lib/spark-assembly-1.5.1-hadoop2.6.0.jar:/home/ubuntu/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-core-3.2.10.jar:/home/ubuntu/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-rdbms-3.2.9.jar:/home/ubuntu/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-api-jdo-3.2.6.jar -Xms1g -Xmx1g -XX:MaxPermSize=256m org.apache.spark.deploy.worker.Worker --webui-port 8081 spark://ip-1-70-44-5:7077
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
15/10/16 19:19:10 INFO Worker: Registered signal handlers for [TERM, HUP, INT]
15/10/16 19:19:11 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
15/10/16 19:19:11 INFO SecurityManager: Changing view acls to: ubuntu
15/10/16 19:19:11 INFO SecurityManager: Changing modify acls to: ubuntu
15/10/16 19:19:11 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(ubuntu); users with modify permissions: Set(ubuntu)
15/10/16 19:19:12 INFO Slf4jLogger: Slf4jLogger started
15/10/16 19:19:12 INFO Remoting: Starting remoting
15/10/16 19:19:12 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkWorker#1.70.44.4:55126]
15/10/16 19:19:12 INFO Utils: Successfully started service 'sparkWorker' on port 55126.
15/10/16 19:19:12 INFO Worker: Starting Spark worker 1.70.44.4:55126 with 2 cores, 2.9 GB RAM
15/10/16 19:19:12 INFO Worker: Running Spark version 1.5.1
15/10/16 19:19:12 INFO Worker: Spark home: /home/ubuntu/spark-1.5.1-bin-hadoop2.6
15/10/16 19:19:12 INFO Utils: Successfully started service 'WorkerUI' on port 8081.
15/10/16 19:19:12 INFO WorkerWebUI: Started WorkerWebUI at http://1.70.44.4:8081
15/10/16 19:19:12 INFO Worker: Connecting to master ip-1-70-44-5:7077...
15/10/16 19:19:24 INFO Worker: Retrying connection to master (attempt # 1)
15/10/16 19:19:24 ERROR SparkUncaughtExceptionHandler: Uncaught exception in thread Thread[sparkWorker-akka.actor.default-dispatcher-5,5,main]
java.util.concurrent.RejectedExecutionException: Task java.util.concurrent.FutureTask#1c5651e9 rejected from java.util.concurrent.ThreadPoolExecutor#671ba687[Running, pool size = 1, active threads = 0, queued tasks = 0, completed tasks = 0]
at java.util.concurrent.ThreadPoolExecutor$AbortPolicy.rejectedExecution(ThreadPoolExecutor.java:2048)
at java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.java:821)
at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:1372)
at java.util.concurrent.AbstractExecutorService.submit(AbstractExecutorService.java:110)
at org.apache.spark.deploy.worker.Worker$$anonfun$org$apache$spark$deploy$worker$Worker$$tryRegisterAllMasters$1.apply(Worker.scala:211)
at org.apache.spark.deploy.worker.Worker$$anonfun$org$apache$spark$deploy$worker$Worker$$tryRegisterAllMasters$1.apply(Worker.scala:210)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
at org.apache.spark.deploy.worker.Worker.org$apache$spark$deploy$worker$Worker$$tryRegisterAllMasters(Worker.scala:210)
at org.apache.spark.deploy.worker.Worker$$anonfun$org$apache$spark$deploy$worker$Worker$$reregisterWithMaster$1.apply$mcV$sp(Worker.scala:288)
at org.apache.spark.util.Utils$.tryOrExit(Utils.scala:1119)
at org.apache.spark.deploy.worker.Worker.org$apache$spark$deploy$worker$Worker$$reregisterWithMaster(Worker.scala:234)
at org.apache.spark.deploy.worker.Worker$$anonfun$receive$1.applyOrElse(Worker.scala:521)
at org.apache.spark.rpc.akka.AkkaRpcEnv.org$apache$spark$rpc$akka$AkkaRpcEnv$$processMessage(AkkaRpcEnv.scala:177)
at org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1$$anonfun$receiveWithLogging$1$$anonfun$applyOrElse$4.apply$mcV$sp(AkkaRpcEnv.scala:126)
at org.apache.spark.rpc.akka.AkkaRpcEnv.org$apache$spark$rpc$akka$AkkaRpcEnv$$safelyCall(AkkaRpcEnv.scala:197)
at org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1$$anonfun$receiveWithLogging$1.applyOrElse(AkkaRpcEnv.scala:125)
at scala.runtime.AbstractPartialFunction$mcVL$sp.apply$mcVL$sp(AbstractPartialFunction.scala:33)
at scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:33)
at scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:25)
at org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:59)
at org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:42)
at scala.PartialFunction$class.applyOrElse(PartialFunction.scala:118)
at org.apache.spark.util.ActorLogReceive$$anon$1.applyOrElse(ActorLogReceive.scala:42)
at akka.actor.Actor$class.aroundReceive(Actor.scala:467)
at org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1.aroundReceive(AkkaRpcEnv.scala:92)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
at akka.actor.ActorCell.invoke(ActorCell.scala:487)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)
at akka.dispatch.Mailbox.run(Mailbox.scala:220)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:397)
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)
15/10/16 19:19:24 INFO ShutdownHookManager: Shutdown hook called
I have added the hostnames to the conf/slaves file. I dont know which enviroment variables to set in spark-env.sh so right not its not being used.
Any pointers to the solution ?
Also, if I should use spark-env.sh then which enviroment vvariables should I run ?
setup details :
2 ubuntu14 machines having 2 cores each.
Please advise.
thanks
So, after some tinkering around I found that slave was not able to communicate with Master on the given port. I changed the security access rules and enabled all TCP traffic on all ports . This solved the problem.
To check if the port is open :
telnet master.ip master.port
The default port is 7077.
My spark-env.sh :
export SPARK_WORKER_INSTANCES=2
export SPARK_MASTER_IP=<ip address>
I'm afraid your hostname may be invalid to Spark, and you hava to change your spark-env.sh.
You can set the variable SPARK_MASTER_IP to be the real ip of master, instead of its hostname.
e.g.
export SPARK_MASTER_IP=1.70.44.5
INSTEAD OF
export SPARK_MASTER_IP=ip-1-70-44-5
Using the yarn-client to run spark program.
I've build the spark on yarn environment.
the scripts is
./bin/spark-submit --class WordCountTest \
--master yarn-client \
--num-executors 1 \
--executor-cores 1 \
--queue root.hadoop \
/root/Desktop/test2.jar \
10
when running I get the following exception.
15/05/12 17:42:01 INFO spark.SparkContext: Running Spark version 1.3.1
15/05/12 17:42:01 WARN spark.SparkConf:
SPARK_CLASSPATH was detected (set to ':/usr/local/hadoop/hadoop-2.5.2/share/hadoop/common/hadoop-lzo-0.4.20-SNAPSHOT.jar').
This is deprecated in Spark 1.0+.
Please instead use:
- ./spark-submit with --driver-class-path to augment the driver classpath
- spark.executor.extraClassPath to augment the executor classpath
15/05/12 17:42:01 WARN spark.SparkConf: Setting 'spark.executor.extraClassPath' to ':/usr/local/hadoop/hadoop-2.5.2/share/hadoop/common/hadoop-lzo-0.4.20-SNAPSHOT.jar' as a work-around.
15/05/12 17:42:01 WARN spark.SparkConf: Setting 'spark.driver.extraClassPath' to ':/usr/local/hadoop/hadoop-2.5.2/share/hadoop/common/hadoop-lzo-0.4.20-SNAPSHOT.jar' as a work-around.
15/05/12 17:42:01 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
15/05/12 17:42:02 INFO spark.SecurityManager: Changing view acls to: root
15/05/12 17:42:02 INFO spark.SecurityManager: Changing modify acls to: root
15/05/12 17:42:02 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(root); users with modify permissions: Set(root)
15/05/12 17:42:02 INFO slf4j.Slf4jLogger: Slf4jLogger started
15/05/12 17:42:02 INFO Remoting: Starting remoting
15/05/12 17:42:03 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkDriver#master:49338]
15/05/12 17:42:03 INFO util.Utils: Successfully started service 'sparkDriver' on port 49338.
15/05/12 17:42:03 INFO spark.SparkEnv: Registering MapOutputTracker
15/05/12 17:42:03 INFO spark.SparkEnv: Registering BlockManagerMaster
15/05/12 17:42:03 INFO storage.DiskBlockManager: Created local directory at /tmp/spark-57f5fb29-784d-4730-92b8-c2e8be97c038/blockmgr-752988bc-b2d0-42f7-891d-5d3edbb4526d
15/05/12 17:42:03 INFO storage.MemoryStore: MemoryStore started with capacity 267.3 MB
15/05/12 17:42:04 INFO spark.HttpFileServer: HTTP File server directory is /tmp/spark-2f2a46eb-9259-4c6e-b9af-7159efb0b3e9/httpd-3c50fe1e-430e-4077-9cd0-58246e182d98
15/05/12 17:42:04 INFO spark.HttpServer: Starting HTTP Server
15/05/12 17:42:04 INFO server.Server: jetty-8.y.z-SNAPSHOT
15/05/12 17:42:04 INFO server.AbstractConnector: Started SocketConnector#0.0.0.0:41749
15/05/12 17:42:04 INFO util.Utils: Successfully started service 'HTTP file server' on port 41749.
15/05/12 17:42:04 INFO spark.SparkEnv: Registering OutputCommitCoordinator
15/05/12 17:42:05 INFO server.Server: jetty-8.y.z-SNAPSHOT
15/05/12 17:42:05 INFO server.AbstractConnector: Started SelectChannelConnector#0.0.0.0:4040
15/05/12 17:42:05 INFO util.Utils: Successfully started service 'SparkUI' on port 4040.
15/05/12 17:42:05 INFO ui.SparkUI: Started SparkUI at http://master:4040
15/05/12 17:42:05 INFO spark.SparkContext: Added JAR file:/root/Desktop/test2.jar at http://192.168.147.201:41749/jars/test2.jar with timestamp 1431423725289
15/05/12 17:42:05 WARN cluster.YarnClientSchedulerBackend: NOTE: SPARK_WORKER_MEMORY is deprecated. Use SPARK_EXECUTOR_MEMORY or --executor-memory through spark-submit instead.
15/05/12 17:42:06 INFO client.RMProxy: Connecting to ResourceManager at master/192.168.147.201:8032
15/05/12 17:42:06 INFO yarn.Client: Requesting a new application from cluster with 2 NodeManagers
15/05/12 17:42:06 INFO yarn.Client: Verifying our application has not requested more than the maximum memory capability of the cluster (8192 MB per container)
15/05/12 17:42:06 INFO yarn.Client: Will allocate AM container, with 896 MB memory including 384 MB overhead
15/05/12 17:42:06 INFO yarn.Client: Setting up container launch context for our AM
15/05/12 17:42:06 INFO yarn.Client: Preparing resources for our AM container
15/05/12 17:42:07 WARN yarn.Client: SPARK_JAR detected in the system environment. This variable has been deprecated in favor of the spark.yarn.jar configuration variable.
15/05/12 17:42:07 INFO yarn.Client: Uploading resource file:/usr/local/spark/spark-1.3.1-bin-hadoop2.5.0-cdh5.3.2/lib/spark-assembly-1.3.1-hadoop2.5.0-cdh5.3.2.jar -> hdfs://master:9000/user/root/.sparkStaging/application_1431423592173_0003/spark-assembly-1.3.1-hadoop2.5.0-cdh5.3.2.jar
15/05/12 17:42:11 INFO yarn.Client: Setting up the launch environment for our AM container
15/05/12 17:42:11 WARN yarn.Client: SPARK_JAR detected in the system environment. This variable has been deprecated in favor of the spark.yarn.jar configuration variable.
15/05/12 17:42:11 INFO spark.SecurityManager: Changing view acls to: root
15/05/12 17:42:11 INFO spark.SecurityManager: Changing modify acls to: root
15/05/12 17:42:11 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(root); users with modify permissions: Set(root)
15/05/12 17:42:11 INFO yarn.Client: Submitting application 3 to ResourceManager
15/05/12 17:42:11 INFO impl.YarnClientImpl: Submitted application application_1431423592173_0003
15/05/12 17:42:12 INFO yarn.Client: Application report for application_1431423592173_0003 (state: FAILED)
15/05/12 17:42:12 INFO yarn.Client:
client token: N/A
diagnostics: Application application_1431423592173_0003 submitted by user root to unknown queue: root.hadoop
ApplicationMaster host: N/A
ApplicationMaster RPC port: -1
queue: root.hadoop
start time: 1431423731271
final status: FAILED
tracking URL: N/A
user: root
Exception in thread "main" org.apache.spark.SparkException: Yarn application has already ended! It might have been killed or unable to launch application master.
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.waitForApplication(YarnClientSchedulerBackend.scala:113)
at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:59)
at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:141)
at org.apache.spark.SparkContext.<init>(SparkContext.scala:381)
at WordCountTest$.main(WordCountTest.scala:14)
at WordCountTest.main(WordCountTest.scala)
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:606)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:569)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:166)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:189)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:110)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
My code very simple, just as following:
object WordCountTest {
def main (args: Array[String]): Unit = {
Logger.getLogger("org.apache.spark").setLevel(Level.WARN)
Logger.getLogger("org.eclipse.jetty.server").setLevel(Level.OFF)
val sparkConf = new SparkConf().setAppName("WordCountTest Prog")
val sc = new SparkContext(sparkConf)
val sqlContext = new SQLContext(sc)
val file = sc.textFile("/data/test/pom.xml")
val counts = file.flatMap(line => line.split(" ")).map(word => (word, 1)).reduceByKey(_ + _)
println(counts)
counts.saveAsTextFile("/data/test/pom_count.txt")
}
}
I've debug this problem for 2 days. Help!Help! Thx.
Try changing queue name to hadoop
in my case,
change “--queue thequeue” to “--queue default”
it work
运行:
./bin/spark-submit --class org.apache.spark.examples.SparkPi --master yarn --deploy-mode cluster --driver-memory 4g --executor-memory 2g --executor-cores 1 --queue thequeue lib/spark-examples*.jar 10
时报如下错误,只需要将“--queue thequeue”改成“--queue default”即可。
I've been setting up a Spark standalone cluster setup following this link. I have 2 machines; The first one (ubuntu0) serve as both the master and a worker, and the second one (ubuntu1) is just a worker. Password-less ssh has been properly configured for both machines already and was tested by doing SSH manually on both sides.
Now when I tried to ./start-all.ssh, both master and worker on the master machine (ubuntu0) were started properly. This is signified by (1)WebUI being accessible (localhost:8081 on my part) and (2) Worker registered/displayed on the WebUI.
However, the other worker on the second machine (ubuntu1), was not started. The error displayed was:
ubuntu1: ssh: connect to host ubuntu1 port 22: Connection timed out
Now this is quite weird already given that I've properly configured the ssh to be password-less on both sides. Given this, I accessed the second machine and tried to start the worker manually using these commands:
./spark-class org.apache.spark.deploy.worker.Worker spark://ubuntu0:7707
./spark-class org.apache.spark.deploy.worker.Worker spark://<ip>:7707
However, below is the result:
14/05/23 13:49:08 INFO Utils: Using Spark's default log4j profile:
org/apache/spark/log4j-defaults.properties
14/05/23 13:49:08 WARN Utils: Your hostname, ubuntu1 resolves to a loopback address:
127.0.1.1; using 192.168.122.1 instead (on interface virbr0)
14/05/23 13:49:08 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
14/05/23 13:49:09 INFO Slf4jLogger: Slf4jLogger started
14/05/23 13:49:09 INFO Remoting: Starting remoting
14/05/23 13:49:09 INFO Remoting: Remoting started; listening on addresses :
[akka.tcp://sparkWorker#ubuntu1.local:42739]
14/05/23 13:49:09 INFO Worker: Starting Spark worker ubuntu1.local:42739 with 8 cores,
4.8 GB RAM
14/05/23 13:49:09 INFO Worker: Spark home: /home/ubuntu1/jaysonp/spark/spark-0.9.1
14/05/23 13:49:09 INFO WorkerWebUI: Started Worker web UI at http://ubuntu1.local:8081
14/05/23 13:49:09 INFO Worker: Connecting to master spark://ubuntu0:7707...
14/05/23 13:49:29 INFO Worker: Connecting to master spark://ubuntu0:7707...
14/05/23 13:49:49 INFO Worker: Connecting to master spark://ubuntu0:7707...
14/05/23 13:50:09 ERROR Worker: All masters are unresponsive! Giving up.
Below are the contents of my master and slave\worker spark-env.ssh:
SPARK_MASTER_IP=192.168.3.222
STANDALONE_SPARK_MASTER_HOST=`hostname -f`
How should I resolve this? Thanks in advance!
For those who are still encountering error(s) when it comes to starting workers on different machines, I just want to share that using IP addresses in conf/slaves worked for me.
Hope this helps!
I have add similar issues today running spark 1.5.1 on RHEL 6.7.
I have 2 machines, their hostname being
- master.domain.com
- slave.domain.com
I installed a standalone version of spark (pre-build against hadoop 2.6) and installed my Oracle jdk-8u66.
Spark download:
wget http://d3kbcqa49mib13.cloudfront.net/spark-1.5.1-bin-hadoop2.6.tgz
Java download
wget --no-cookies --no-check-certificate --header "Cookie: gpw_e24=http%3A%2F%2Fwww.oracle.com%2F; oraclelicense=accept-securebackup-cookie" "http://download.oracle.com/otn-pub/java/jdk/8u66-b17/jdk-8u66-linux-x64.tar.gz"
after spark and java are unpacked in my home directory I did the following:
on 'master.domain.com' I ran:
./sbin/start-master.sh
The webUI become available at http://master.domain.com:8080 (no slave running)
on 'slave.domain.com' I did try:
./sbin/start-slave.sh spark://master.domain.com:7077 FAILED AS FOLLOW
Spark Command: /root/java/bin/java -cp /root/spark-1.5.1-bin-hadoop2.6/sbin/../conf/:/root/spark-1.5.1-bin-hadoop2.6/lib/spark-assembly-1.5.1-hadoop2.6.0.jar:/root/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-rdbms-3.2.9.jar:/root/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-api-jdo-3.2.6.jar:/root/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-core-3.2.10.jar -Xms1g -Xmx1g org.apache.spark.deploy.worker.Worker --webui-port 8081 spark://master.domain.com:7077
========================================
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
15/11/06 11:03:51 INFO Worker: Registered signal handlers for [TERM, HUP, INT]
15/11/06 11:03:51 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
15/11/06 11:03:51 INFO SecurityManager: Changing view acls to: root
15/11/06 11:03:51 INFO SecurityManager: Changing modify acls to: root
15/11/06 11:03:51 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(root); users with modify permissions: Set(root)
15/11/06 11:03:52 INFO Slf4jLogger: Slf4jLogger started
15/11/06 11:03:52 INFO Remoting: Starting remoting
15/11/06 11:03:52 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkWorker#10.80.70.38:50573]
15/11/06 11:03:52 INFO Utils: Successfully started service 'sparkWorker' on port 50573.
15/11/06 11:03:52 INFO Worker: Starting Spark worker 10.80.70.38:50573 with 8 cores, 6.7 GB RAM
15/11/06 11:03:52 INFO Worker: Running Spark version 1.5.1
15/11/06 11:03:52 INFO Worker: Spark home: /root/spark-1.5.1-bin-hadoop2.6
15/11/06 11:03:53 INFO Utils: Successfully started service 'WorkerUI' on port 8081.
15/11/06 11:03:53 INFO WorkerWebUI: Started WorkerWebUI at http://10.80.70.38:8081
15/11/06 11:03:53 INFO Worker: Connecting to master master.domain.com:7077...
15/11/06 11:04:05 INFO Worker: Retrying connection to master (attempt # 1)
15/11/06 11:04:05 ERROR SparkUncaughtExceptionHandler: Uncaught exception in thread Thread[sparkWorker-akka.actor.default-dispatcher-4,5,main]
java.util.concurrent.RejectedExecutionException: Task java.util.concurrent.FutureTask#48711bf5 rejected from java.util.concurrent.ThreadPoolExecutor#14db705b[Running, pool size = 1, active threads = 0, queued tasks = 0, completed tasks = 1]
at java.util.concurrent.ThreadPoolExecutor$AbortPolicy.rejectedExecution(ThreadPoolExecutor.java:2047)
at java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.java:823)
at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:1369)
at java.util.concurrent.AbstractExecutorService.submit(AbstractExecutorService.java:112)
at org.apache.spark.deploy.worker.Worker$$anonfun$org$apache$spark$deploy$worker$Worker$$tryRegisterAllMasters$1.apply(Worker.scala:211)
at org.apache.spark.deploy.worker.Worker$$anonfun$org$apache$spark$deploy$worker$Worker$$tryRegisterAllMasters$1.apply(Worker.scala:210)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
at org.apache.spark.deploy.worker.Worker.org$apache$spark$deploy$worker$Worker$$tryRegisterAllMasters(Worker.scala:210)
at org.apache.spark.deploy.worker.Worker$$anonfun$org$apache$spark$deploy$worker$Worker$$reregisterWithMaster$1.apply$mcV$sp(Worker.scala:288)
at org.apache.spark.util.Utils$.tryOrExit(Utils.scala:1119)
at org.apache.spark.deploy.worker.Worker.org$apache$spark$deploy$worker$Worker$$reregisterWithMaster(Worker.scala:234)
at org.apache.spark.deploy.worker.Worker$$anonfun$receive$1.applyOrElse(Worker.scala:521)
at org.apache.spark.rpc.akka.AkkaRpcEnv.org$apache$spark$rpc$akka$AkkaRpcEnv$$processMessage(AkkaRpcEnv.scala:177)
at org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1$$anonfun$receiveWithLogging$1$$anonfun$applyOrElse$4.apply$mcV$sp(AkkaRpcEnv.scala:126)
at org.apache.spark.rpc.akka.AkkaRpcEnv.org$apache$spark$rpc$akka$AkkaRpcEnv$$safelyCall(AkkaRpcEnv.scala:197)
at org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1$$anonfun$receiveWithLogging$1.applyOrElse(AkkaRpcEnv.scala:125)
at scala.runtime.AbstractPartialFunction$mcVL$sp.apply$mcVL$sp(AbstractPartialFunction.scala:33)
at scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:33)
at scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:25)
at org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:59)
at org.apache.spark.util.ActorLogReceive$$anon$1.apply(ActorLogReceive.scala:42)
at scala.PartialFunction$class.applyOrElse(PartialFunction.scala:118)
at org.apache.spark.util.ActorLogReceive$$anon$1.applyOrElse(ActorLogReceive.scala:42)
at akka.actor.Actor$class.aroundReceive(Actor.scala:467)
at org.apache.spark.rpc.akka.AkkaRpcEnv$$anonfun$actorRef$lzycompute$1$1$$anon$1.aroundReceive(AkkaRpcEnv.scala:92)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
at akka.actor.ActorCell.invoke(ActorCell.scala:487)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:238)
at akka.dispatch.Mailbox.run(Mailbox.scala:220)
at akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:397)
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)
15/11/06 11:04:05 INFO ShutdownHookManager: Shutdown hook called
start-slave spark://<master-IP>:7077 also FAILED as above.
start-slave spark://master:7077 WORKED and the worker shows in the master webUI
Spark Command: /root/java/bin/java -cp /root/spark-1.5.1-bin-hadoop2.6/sbin/../conf/:/root/spark-1.5.1-bin-hadoop2.6/lib/spark-assembly-1.5.1-hadoop2.6.0.jar:/root/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-rdbms-3.2.9.jar:/root/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-api-jdo-3.2.6.jar:/root/spark-1.5.1-bin-hadoop2.6/lib/datanucleus-core-3.2.10.jar -Xms1g -Xmx1g org.apache.spark.deploy.worker.Worker --webui-port 8081 spark://master:7077
========================================
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
15/11/06 11:08:15 INFO Worker: Registered signal handlers for [TERM, HUP, INT]
15/11/06 11:08:15 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
15/11/06 11:08:15 INFO SecurityManager: Changing view acls to: root
15/11/06 11:08:15 INFO SecurityManager: Changing modify acls to: root
15/11/06 11:08:15 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(root); users with modify permissions: Set(root)
15/11/06 11:08:16 INFO Slf4jLogger: Slf4jLogger started
15/11/06 11:08:16 INFO Remoting: Starting remoting
15/11/06 11:08:17 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkWorker#10.80.70.38:40780]
15/11/06 11:08:17 INFO Utils: Successfully started service 'sparkWorker' on port 40780.
15/11/06 11:08:17 INFO Worker: Starting Spark worker 10.80.70.38:40780 with 8 cores, 6.7 GB RAM
15/11/06 11:08:17 INFO Worker: Running Spark version 1.5.1
15/11/06 11:08:17 INFO Worker: Spark home: /root/spark-1.5.1-bin-hadoop2.6
15/11/06 11:08:17 INFO Utils: Successfully started service 'WorkerUI' on port 8081.
15/11/06 11:08:17 INFO WorkerWebUI: Started WorkerWebUI at http://10.80.70.38:8081
15/11/06 11:08:17 INFO Worker: Connecting to master master:7077...
15/11/06 11:08:17 INFO Worker: Successfully registered with master spark://master:7077
Note: I haven't added any extra config in conf/spark-env.sh
Note2: when looking in the master webUI, the spark master URL at the top is actually the one that worked for me, so I'd say in doubts just use that one.
I hope this helps ;)
Using hostname in /cong/slaves worked well for me.
Here are some steps I would take it,
Checked SSH public key
scp /etc/spark/conf.dist/spark-env.sh to your workers
My part of setting in spark-env.sh
export STANDALONE_SPARK_MASTER_HOST=hostname
export SPARK_MASTER_IP=$STANDALONE_SPARK_MASTER_HOST
I guess you missed something in your configuration, that's what I learned from your log.
Check your /etc/hosts, make sure ubuntu1 in your master's host list and its Ip is match the slave's IP address.
Add export SPARK_LOCAL_IP='ubuntu1' in the spark-env.sh file of your slave