无法将Spark应用程序提交到群集,卡在" UNDEFINED"

时间:2014-11-12 09:42:29

标签: apache-spark

我使用此命令将 spark应用程序引导至纱线群集

export YARN_CONF_DIR=conf
bin/spark-submit --class "Mining"
  --master yarn-cluster
  --executor-memory 512m ./target/scala-2.10/mining-assembly-0.1.jar

在网络界面中,它停留在 UNDEFINED

enter image description here

在控制台中,它坚持

<code>14/11/12 16:37:55 INFO yarn.Client: Application report from ASM: 
     application identifier: application_1415704754709_0017
     appId: 17
     clientToAMToken: null
     appDiagnostics: 
     appMasterHost: example.com
     appQueue: default
     appMasterRpcPort: 0
     appStartTime: 1415784586000
     yarnAppState: RUNNING
     distributedFinalState: UNDEFINED
     appTrackingUrl: http://example.com:8088/proxy/application_1415704754709_0017/
     appUser: rain
</code>

更新

深入了解网络用户界面Logs for container中的http://example.com:8042/node/containerlogs/container_1415704754709_0017_01_000001/rain/stderr/?start=0,我发现了这个

14/11/12 02:11:47 WARN YarnClusterScheduler: Initial job has not accepted 
any resources; check your cluster UI to ensure that workers are registered
and have sufficient memory
14/11/12 02:11:47 DEBUG Client: IPC Client (1211012646) connection to
spark.mvs.vn/192.168.64.142:8030 from rain sending #24418
14/11/12 02:11:47 DEBUG Client: IPC Client (1211012646) connection to
spark.mvs.vn/192.168.64.142:8030 from rain got value #24418

我发现此问题已解决http://hortonworks.com/hadoop-tutorial/using-apache-spark-hdp/

The Hadoop cluster must have sufficient memory for the request.

For example, submitting the following job with 1GB memory allocated for
executor and Spark driver fails with the above error in the HDP 2.1 Sandbox.
Reduce the memory asked for the executor and the Spark driver to 512m and
re-start the cluster.

我正在尝试这个解决方案,希望它会起作用。

1 个答案:

答案 0 :(得分:3)

解决方案

最后我发现it caused by memory problem

当我在界面的Web UI中将yarn.nodemanager.resource.memory-mb更改为3072(其值为2048)并重新启动群集时,它工作正常。

enter image description here

我很高兴看到这个

enter image description here

拥有3GB的纱线节点管理员,我的峰会是

bin/spark-submit
    --class "Mining"
    --master yarn-cluster
    --executor-memory 512m
    --driver-memory 512m
    --num-executors 2
    --executor-cores 1
    ./target/scala-2.10/mining-assembly-0.1.jar`