Question

我是火花/纱线的新手，当我在纱线集群上提交火花作业时，遇到exitCode = 13。当火花作业在本地模式下运行时，一切都很好。

我使用的命令是：

/usr/hdp/current/spark-client/bin/spark-submit --class com.test.sparkTest --master yarn --deploy-mode cluster --num-executors 40 --executor-cores 4 --driver-memory 17g --executor-memory 22g --files /usr/hdp/current/spark-client/conf/hive-site.xml /home/user/sparkTest.jar*

Spark错误日志：

16/04/12 17:59:30 INFO Client:
         client token: N/A
         diagnostics: Application application_1459460037715_23007 failed 2 times due to AM Container for appattempt_1459460037715_23007_000002 exited with  exitCode: 13
For more detailed output, check application tracking page:http://b-r06f2-prod.phx2.cpe.net:8088/cluster/app/application_1459460037715_23007Then, click on links to logs of each attempt.
Diagnostics: Exception from container-launch.
Container id: container_e40_1459460037715_23007_02_000001
Exit code: 13
Stack trace: ExitCodeException exitCode=13:
        at org.apache.hadoop.util.Shell.runCommand(Shell.java:576)
        at org.apache.hadoop.util.Shell.run(Shell.java:487)
        at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:753)
        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)


**Yarn logs**

    16/04/12 23:55:35 INFO mapreduce.TableInputFormatBase: Input split length: 977 M bytes.
16/04/12 23:55:41 INFO yarn.ApplicationMaster: Waiting for spark context initialization ...
16/04/12 23:55:51 INFO yarn.ApplicationMaster: Waiting for spark context initialization ...
16/04/12 23:56:01 INFO yarn.ApplicationMaster: Waiting for spark context initialization ...
16/04/12 23:56:11 INFO yarn.ApplicationMaster: Waiting for spark context initialization ...
16/04/12 23:56:11 INFO client.ConnectionManager$HConnectionImplementation: Closing zookeeper sessionid=0x152f0b4fc0e7488
16/04/12 23:56:11 INFO zookeeper.ZooKeeper: Session: 0x152f0b4fc0e7488 closed
16/04/12 23:56:11 INFO zookeeper.ClientCnxn: EventThread shut down
16/04/12 23:56:11 INFO executor.Executor: Finished task 0.0 in stage 1.0 (TID 2). 2003 bytes result sent to driver
16/04/12 23:56:11 INFO scheduler.TaskSetManager: Finished task 0.0 in stage 1.0 (TID 2) in 82134 ms on localhost (2/3)
16/04/12 23:56:17 INFO client.ConnectionManager$HConnectionImplementation: Closing zookeeper sessionid=0x4508c270df0980316/04/12 23:56:17 INFO zookeeper.ZooKeeper: Session: 0x4508c270df09803 closed *
...
    16/04/12 23:56:21 ERROR yarn.ApplicationMaster: SparkContext did not initialize after waiting for 100000 ms. Please check earlier log output for errors. Failing the application.
16/04/12 23:56:21 INFO yarn.ApplicationMaster: Final app status: FAILED, exitCode: 13, (reason: Timed out waiting for SparkContext.)
16/04/12 23:56:21 INFO spark.SparkContext: Invoking stop() from shutdown hook *

Answer 1

您似乎已将代码中的母版设置为本地

SparkConf.setMaster("local[*]")

您必须让代码中的母版未设置，并在稍后发布spark-submit时将其设置为

spark-submit --master yarn-client ...

Answer 2

我在集群模式下运行SparkSQL作业时遇到了同样的错误。没有其他解决方案对我有用，但是在Hadoop中的作业历史服务器日志中查找，我发现了该堆栈跟踪。

20/02/05 23:01:24 INFO hive.metastore: Connected to metastore.
20/02/05 23:03:03 ERROR yarn.ApplicationMaster: Uncaught exception: 
java.util.concurrent.TimeoutException: Futures timed out after [100000 milliseconds]
    at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:223)
    at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:227)
    at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:220)
    at org.apache.spark.deploy.yarn.ApplicationMaster.runDriver(ApplicationMaster.scala:468)
    at org.apache.spark.deploy.yarn.ApplicationMaster.org$apache$spark$deploy$yarn$ApplicationMaster$$runImpl(ApplicationMaster.scala:305)
    at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply$mcV$sp(ApplicationMaster.scala:245)
    at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
    at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
...

并查看Spark source code，您会发现AM基本上在等待执行用户类的线程设置spark.driver.port属性时超时。
因此，这可能是暂时性的问题，或者您应该出于超时原因调查代码。

Answer 3

如果它可以帮助某人

此错误的另一种可能性是当您错误地放置了-class 参数

时

Answer 4

我遇到了完全相同的问题，但以上答案无效。另外，当我与spark-submit --deploy-mode client一起运行时，一切正常。

Spark在Yarn集群exitCode = 13上运行：

4 个答案: