如何从命令行检查Spark应用程序的状态?

时间:2016-05-24 17:49:12

标签: apache-spark

要检查Apache spark中正在运行的应用程序,可以从URL上的Web界面检查它们:

http://<master>:8080

我的问题是如何从终端检查正在运行的应用程序,是否有任何返回应用程序状态的命令?

4 个答案:

答案 0 :(得分:9)

如果是Spark Standalone或Apache Mesos集群管理器,则可以使用@sb0709's answer

对于YARN,您应该使用yarn application命令:

$ yarn application -help
usage: application
 -appStates <States>             Works with -list to filter applications
                                 based on input comma-separated list of
                                 application states. The valid application
                                 state can be one of the following:
                                 ALL,NEW,NEW_SAVING,SUBMITTED,ACCEPTED,RUN
                                 NING,FINISHED,FAILED,KILLED
 -appTypes <Types>               Works with -list to filter applications
                                 based on input comma-separated list of
                                 application types.
 -help                           Displays help for all commands.
 -kill <Application ID>          Kills the application.
 -list                           List applications. Supports optional use
                                 of -appTypes to filter applications based
                                 on application type, and -appStates to
                                 filter applications based on application
                                 state.
 -movetoqueue <Application ID>   Moves the application to a different
                                 queue.
 -queue <Queue Name>             Works with the movetoqueue command to
                                 specify which queue to move an
                                 application to.
 -status <Application ID>        Prints the status of the application.

答案 1 :(得分:5)

您可以使用spark-submit --status(如Mastering Apache Spark 2.0中所述)。

spark-submit --status [submission ID]

请参阅code of spark-submit以获取参考:

if (!master.startsWith("spark://") && !master.startsWith("mesos://")) {
  SparkSubmit.printErrorAndExit(
    "Requesting submission statuses is only supported in standalone or Mesos mode!")
}

答案 2 :(得分:0)

在我的情况下,我的spark应用程序远程运行在亚马逊的AWS EMR上。所以我使用Lynx命令行浏览器来访问spark应用程序的状态。 当您从一个终端提交了火花作业时,打开另一个终端并从新终端发出以下命令。

   **lynx http://localhost:<4043 or other spark job port>**

答案 3 :(得分:0)

我发现可以使用REST API提交,终止和获取Spark作业的状态。 REST API在端口6066上的master上公开。

  1. 要创建作业,请使用以下curl命令:

    curl -X POST http://spark-cluster-ip:6066/v1/submissions/create 
       --header "Content-Type:application/json;charset=UTF-8"
       --data 
        '{
            "action" : "CreateSubmissionRequest",
            "appArgs" : [ "blah" ],
            "appResource" : "path-to-jar-file",
            "clientSparkVersion" : "2.2.0",
            "environmentVariables" : { "SPARK_ENV_LOADED" : "1" },
            "mainClass" : "app-class",
            "sparkProperties" : { 
                "spark.jars" : "path-to-jar-file",
                "spark.driver.supervise" : "false",
                "spark.app.name" : "app-name",
                "spark.submit.deployMode" : "cluster",
                "spark.master" : "spark://spark-master-ip:6066" 
             }
         }'
    

    响应包括上述操作和submissionId

    的成功或失败
    {
       'submissionId': 'driver-20170829014216-0001',
       'serverSparkVersion': '2.2.0',
       'success': True,
       'message': 'Driver successfully submitted as driver-20170829014216-0001',
       'action': 'CreateSubmissionResponse'
    }
    
  2. 要删除作业,请使用上面获得的submissionId:

     curl -X POST http://spark-cluster-ip:6066/v1/submissions/kill/driver-driver-20170829014216-0001
    

    响应再次包含成功/失败状态:

    {
         'success': True,
         'message': 'Kill request for driver-20170829014216-0001 submitted',
         'action': 'KillSubmissionResponse',
         'serverSparkVersion': '2.2.0',
         'submissionId': 'driver-20170829014216-0001'
    }
    
  3. 要获取状态,请使用以下命令:

    curl http://spark-cluster-ip:6066/v1/submissions/status/driver-20170829014216-0001
    

    响应包括驱动程序状态 - 应用程序的当前状态:

    {
      "action" : "SubmissionStatusResponse",
      "driverState" : "RUNNING",
      "serverSparkVersion" : "2.2.0",
      "submissionId" : "driver-20170829203736-0004",
      "success" : true,
      "workerHostPort" : "10.32.1.18:38317",
      "workerId" : "worker-20170829013941-10.32.1.18-38317"
    }
    
  4. 我发现了REST API here