试图使用AWS SDK for Java在EMR上运行Spark，但它跳过了存储在S3上的远程JAR

Question

我试图使用SDK for Java在EMR上运行Spark，但我在使用存储在S3上的JAR时遇到了一些问题。以下是相关代码：

public String launchCluster() throws Exception {
    StepFactory stepFactory = new StepFactory();

    // Creates a cluster flow step for debugging
    StepConfig enableDebugging = new StepConfig().withName("Enable debugging")
            .withActionOnFailure("TERMINATE_JOB_FLOW")
            .withHadoopJarStep(stepFactory.newEnableDebuggingStep());

    // Here is the original code before I tried command-runner.jar. 
    // When using this, I get a ClassNotFoundException for 
    // org.apache.spark.SparkConf. This is because for some reason, 
    // the super-jar that I'm generating doesn't include apache spark. 
    // Even so, I believe EMR should already have Spark installed if
    // I configure this correctly...

    //        HadoopJarStepConfig runExampleConfig = new HadoopJarStepConfig()
    //                .withJar(JAR_LOCATION)
    //                .withMainClass(MAIN_CLASS);

    HadoopJarStepConfig runExampleConfig = new HadoopJarStepConfig()
            .withJar("command-runner.jar")
            .withArgs(
                    "spark-submit",
                    "--master", "yarn",
                    "--deploy-mode", "cluster",
                    "--class", SOME_MAIN_CLASS,
                    SOME_S3_PATH_TO_SUPERJAR,
                    "-useSparkLocal", "false"
            );

    StepConfig customExampleStep = new StepConfig().withName("Example Step")
            .withActionOnFailure("TERMINATE_JOB_FLOW")
            .withHadoopJarStep(runExampleConfig);

    // Create Applications so that the request knows to launch
    // the cluster with support for Hadoop and Spark.

    // Unsure if Hadoop is necessary...
    Application hadoopApp = new Application().withName("Hadoop");
    Application sparkApp = new Application().withName("Spark");

    RunJobFlowRequest request = new RunJobFlowRequest().withName("spark-cluster")
            .withReleaseLabel("emr-5.15.0")
            .withSteps(enableDebugging, customExampleStep)
            .withApplications(hadoopApp, sparkApp)
            .withLogUri(LOG_URI)
            .withServiceRole("EMR_DefaultRole")
            .withJobFlowRole("EMR_EC2_DefaultRole")
            .withVisibleToAllUsers(true)
            .withInstances(new JobFlowInstancesConfig()
                    .withInstanceCount(3)
                    .withKeepJobFlowAliveWhenNoSteps(true)
                    .withMasterInstanceType("m3.xlarge")
                    .withSlaveInstanceType("m3.xlarge")
            );
    return result.getJobFlowId();
}

步骤完成后没有出错，但实际上并没有输出任何内容。...当我检查日志时，stderr包含以下
警告：Skip remote jar s3://somebucket/myservice-1.0-super.jar.
和
18/07/17 22:08:31警告客户端：既没有设置spark.yarn.jars也没有设置spark.yarn.archive，回到spark_home下的上载库。

我不确定基于日志的问题是什么。我相信我正在集群上正确地安装Spark。另外，为了提供一些上下文--当我直接使用存储在S3上的超级JAR而不是命令运行器使用withjar时（没有使用withargs)，它会正确地获取JAR，但随后它没有安装Spark--我为SparkConf获得了一个ClassNotFoundException（和JavaSparkContextion，这取决于Spark作业代码首先尝试创建的内容）。

任何指示将非常感谢！

Answer 1

我认为，如果您使用的是最近的EMR版本（例如EMR-5.17.0)，那么--master参数应该是yarn-cluster而不是runexampleConfig语句中的yarn。我也有同样的问题，在这次改变后，它对我来说很好。