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Posted to issues@spark.apache.org by "Kaveen Raajan (JIRA)" <ji...@apache.org> on 2015/06/02 14:17:17 UTC

[jira] [Updated] (SPARK-7700) Spark 1.3.0 on YARN: Application failed 2 times due to AM Container

     [ https://issues.apache.org/jira/browse/SPARK-7700?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Kaveen Raajan updated SPARK-7700:
---------------------------------
    Attachment: Patch-1.patch

> Spark 1.3.0 on YARN: Application failed 2 times due to AM Container
> -------------------------------------------------------------------
>
>                 Key: SPARK-7700
>                 URL: https://issues.apache.org/jira/browse/SPARK-7700
>             Project: Spark
>          Issue Type: Story
>          Components: Build
>    Affects Versions: 1.3.1
>         Environment: windows 8 Single language
> Hadoop-2.5.2
> Protocol Buffer-2.5.0
> Scala-2.11
>            Reporter: Kaveen Raajan
>         Attachments: Patch-1.patch
>
>
> I build SPARK on yarn mode by giving following command. Build got succeeded.
> {panel}
> mvn -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 -Phive -Phive-0.12.0 -Phive-thriftserver -DskipTests clean package
> {panel}
> I set following property at spark-env.cmd file
> {panel}
> SET SPARK_JAR=hdfs://master:9000/user/spark/jar
> {panel}
> *Note:*  spark jar files are moved to hdfs specified location. Also spark classpath are added to hadoop-config.cmd and HADOOP_CONF_DIR are set at enviroment variable.
> I tried to execute following SparkPi example in yarn-cluster mode.
> {panel}
> spark-submit --class org.apache.spark.examples.SparkPi --master yarn-cluster --num-executors 3 --driver-memory 4g --executor-memory 2g --executor-cores 1 --queue default S:\Hadoop\Spark\spark-1.3.1\examples\target\spark-examples_2.10-1.3.1.jar 10
> {panel}
> My job able to submit at hadoop cluster, but it always in accepted state and Failed with following error
> {panel}
> 15/05/14 13:00:51 INFO client.RMProxy: Connecting to ResourceManager at /0.0.0.0:8032
> 15/05/14 13:00:51 INFO yarn.Client: Requesting a new application from cluster with 1 NodeManagers
> 15/05/14 13:00:51 INFO yarn.Client: Verifying our application has not requestedmore than the maximum memory capability of the cluster (8048 MB per container)
> 15/05/14 13:00:51 INFO yarn.Client: Will allocate AM container, with 4480 MB memory including 384 MB overhead
> 15/05/14 13:00:51 INFO yarn.Client: Setting up container launch context for ourAM
> 15/05/14 13:00:51 INFO yarn.Client: Preparing resources for our AM container
> 15/05/14 13:00:52 INFO yarn.Client: Source and destination file systems are thesame. Not copying hdfs://master:9000/user/spark/jar
> 15/05/14 13:00:52 INFO yarn.Client: Uploading resource file:/S:/Hadoop/Spark/spark-1.3.1/examples/target/spark-examples_2.10-1.3.1.jar -> hdfs://master:9000/user/HDFS/.sparkStaging/application_1431587916618_0003/spark-examples_2.10-1.3.1.jar
> 15/05/14 13:00:52 INFO yarn.Client: Setting up the launch environment for our AM container
> 15/05/14 13:00:52 INFO spark.SecurityManager: Changing view acls to: HDFS
> 15/05/14 13:00:52 INFO spark.SecurityManager: Changing modify acls to: HDFS
> 15/05/14 13:00:52 INFO spark.SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(HDFS); users with modify permissions: Set(HDFS)
> 15/05/14 13:00:52 INFO yarn.Client: Submitting application 3 to ResourceManager
> 15/05/14 13:00:52 INFO impl.YarnClientImpl: Submitted application application_1431587916618_0003
> 15/05/14 13:00:53 INFO yarn.Client: Application report for application_1431587916618_0003 (state: ACCEPTED)
> 15/05/14 13:00:53 INFO yarn.Client:
>          client token: N/A
>          diagnostics: N/A
>          ApplicationMaster host: N/A
>          ApplicationMaster RPC port: -1
>          queue: default
>          start time: 1431588652790
>          final status: UNDEFINED
>          tracking URL: http://master:8088/proxy/application_1431587916618_0003/
>          user: HDFS
> 15/05/14 13:00:54 INFO yarn.Client: Application report for application_1431587916618_0003 (state: ACCEPTED)
> 15/05/14 13:00:55 INFO yarn.Client: Application report for application_1431587916618_0003 (state: ACCEPTED)
> 15/05/14 13:00:56 INFO yarn.Client: Application report for application_1431587916618_0003 (state: ACCEPTED)
> 15/05/14 13:00:57 INFO yarn.Client: Application report for application_1431587916618_0003 (state: ACCEPTED)
> 15/05/14 13:00:58 INFO yarn.Client: Application report for application_1431587916618_0003 (state: ACCEPTED)
> 15/05/14 13:00:59 INFO yarn.Client: Application report for application_1431587916618_0003 (state: FAILED)
> 15/05/14 13:00:59 INFO yarn.Client:
>          client token: N/A
>          diagnostics: Application application_1431587916618_0003 failed 2 times
> due to AM Container for appattempt_1431587916618_0003_000002 exited with  exitCode: 1
> For more detailed output, check application tracking page:http://master:8088/proxy/application_1431587916618_0003/Then, click on links to logs of each attempt.
> Diagnostics: Exception from container-launch.
> Container id: container_1431587916618_0003_02_000001
> Exit code: 1
> Stack trace: ExitCodeException exitCode=1:
>         at org.apache.hadoop.util.Shell.runCommand(Shell.java:538)
>         at org.apache.hadoop.util.Shell.run(Shell.java:455)
>         at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:715)
>         at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:211)
>         at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
>         at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
>         at java.util.concurrent.FutureTask.run(FutureTask.java:262)
>         at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>         at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>         at java.lang.Thread.run(Thread.java:744)
> Shell output:         1 file(s) moved.
> Container exited with a non-zero exit code 1
> Failing this attempt. Failing the application.
>          ApplicationMaster host: N/A
>          ApplicationMaster RPC port: -1
>          queue: default
>          start time: 1431588652790
>          final status: FAILED
>          tracking URL: http://master:8088/cluster/app/application_1431587916618_0003
>          user: HDFS
> Exception in thread "main" org.apache.spark.SparkException: Application finished with failed status
>         at org.apache.spark.deploy.yarn.ClientBase$class.run(ClientBase.scala:522)
>         at org.apache.spark.deploy.yarn.Client.run(Client.scala:35)
>         at org.apache.spark.deploy.yarn.Client$.main(Client.scala:139)
>         at org.apache.spark.deploy.yarn.Client.main(Client.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$.launch(SparkSubmit.scala:360)
>         at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:76)
>         at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
> {panel}
> While debugging launch-container.cmd file I found that spark jar are not able to access by AM.
> {color:red}
> Error: Could not find or load main class '-Dspark.executor.memory=2g'
> {color}
> If I tried to *run spark-shell in yarn-client* mean same issue found with error message _yarn application already ended,might be killed or not able to launch application._
> Similar Issues are available at [http://blog.csdn.net/sunflower_cao/article/details/38046341]
> [http://stackoverflow.com/questions/29392318/spark-1-3-0-on-yarn-application-failed-2-times-due-to-am-container]
> Please guide me where I made a mistake to run hadoop on yarn mode.



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