Yarn簇exitcode上的Spark运行=13:

yqkkidmi  于 2021-05-29  发布在  Hadoop
关注(0)|答案(4)|浏览(525)

我是一个spark/Yarn新手,当我提交关于Yarn簇的spark作业时遇到exitcode=13。当spark作业在本地模式下运行时,一切正常。
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 *
6yoyoihd

6yoyoihd1#

似乎您已将代码中的主机设置为本地 SparkConf.setMaster("local[*]") 您必须在代码中取消设置主控形状,并在以后发布时进行设置
spark-submit spark-submit --master yarn-client ...

dxpyg8gm

dxpyg8gm2#

如果它能帮助某人
这个错误的另一种可能性是当您错误地输入--class参数时

bis0qfac

bis0qfac3#

我有完全相同的问题,但上面的答案不起作用。或者,当我用 spark-submit --deploy-mode client 一切正常。

nkcskrwz

nkcskrwz4#

我在集群模式下运行sparksql作业时遇到了同样的错误。其他解决方案都不适合我,但在hadoop中查看job history服务器日志时,我发现了这个堆栈跟踪。

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)
...

看看spark的源代码,你会发现基本上am在等待 spark.driver.port 属性由执行用户类的线程设置。
因此,它可能是一个暂时的问题,或者您应该调查您的代码超时的原因。

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