使用 Amazon SDK for Java 创建 Amazon EMR 集群 - Amazon EMR
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使用 Amazon SDK for Java 创建 Amazon EMR 集群

Amazon SDK for Java 提供具有 Amazon EMR 功能的三个包:

有关这些包的更多信息,请参阅 Amazon SDK for Java API 参考

以下示例说明了 SDK 如何使用 Amazon EMR 简化编程过程。下面的代码示例使用 StepFactory 对象(用于创建通用 Amazon EMR 步骤类型的帮助程序类)创建一个启用了调试的交互式 Hive 集群。

import com.amazonaws.AmazonClientException; import com.amazonaws.auth.AWSCredentials; import com.amazonaws.auth.AWSStaticCredentialsProvider; import com.amazonaws.auth.profile.ProfileCredentialsProvider; import com.amazonaws.services.elasticmapreduce.AmazonElasticMapReduce; import com.amazonaws.services.elasticmapreduce.AmazonElasticMapReduceClientBuilder; import com.amazonaws.services.elasticmapreduce.model.*; import com.amazonaws.services.elasticmapreduce.util.StepFactory; public class Main { public static void main(String[] args) { AWSCredentialsProvider profile = null; try { credentials_profile = new ProfileCredentialsProvider("default"); // specifies any named profile in .aws/credentials as the credentials provider } catch (Exception e) { throw new AmazonClientException( "Cannot load credentials from .aws/credentials file. " + "Make sure that the credentials file exists and that the profile name is defined within it.", e); } // create an EMR client using the credentials and region specified in order to create the cluster AmazonElasticMapReduce emr = AmazonElasticMapReduceClientBuilder.standard() .withCredentials(credentials_profile) .withRegion(Regions.US_WEST_1) .build(); // create a step to enable debugging in the AWS Management Console StepFactory stepFactory = new StepFactory(); StepConfig enabledebugging = new StepConfig() .withName("Enable debugging") .withActionOnFailure("TERMINATE_JOB_FLOW") .withHadoopJarStep(stepFactory.newEnableDebuggingStep()); // specify applications to be installed and configured when EMR creates the cluster Application hive = new Application().withName("Hive"); Application spark = new Application().withName("Spark"); Application ganglia = new Application().withName("Ganglia"); Application zeppelin = new Application().withName("Zeppelin"); // create the cluster RunJobFlowRequest request = new RunJobFlowRequest() .withName("MyClusterCreatedFromJava") .withReleaseLabel("emr-5.20.0") // specifies the EMR release version label, we recommend the latest release .withSteps(enabledebugging) .withApplications(hive,spark,ganglia,zeppelin) .withLogUri("s3://path/to/my/emr/logs") // a URI in S3 for log files is required when debugging is enabled .withServiceRole("EMR_DefaultRole") // replace the default with a custom IAM service role if one is used .withJobFlowRole("EMR_EC2_DefaultRole") // replace the default with a custom EMR role for the EC2 instance profile if one is used .withInstances(new JobFlowInstancesConfig() .withEc2SubnetId("subnet-12ab34c56") .withEc2KeyName("myEc2Key") .withInstanceCount(3) .withKeepJobFlowAliveWhenNoSteps(true) .withMasterInstanceType("m4.large") .withSlaveInstanceType("m4.large")); RunJobFlowResult result = emr.runJobFlow(request); System.out.println("The cluster ID is " + result.toString()); } }

至少,您必须传递分别对应于 EMR_DefaultRole 和 EMR_EC2_DefaultRole 的服务角色和任务流角色。可以通过为同一个账户调用此 Amazon CLI 命令来实现此目的。首先,查看这两个角色是否已存在:

aws iam list-roles | grep EMR

将显示实例配置文件 (EMR_EC2_DefaultRole) 和服务角色 (EMR_DefaultRole) (如果存在) :

"RoleName": "EMR_DefaultRole", "Arn": "arn:aws:iam::AccountID:role/EMR_DefaultRole" "RoleName": "EMR_EC2_DefaultRole", "Arn": "arn:aws:iam::AccountID:role/EMR_EC2_DefaultRole"

如果默认角色不存在,则可以使用以下命令创建它们:

aws emr create-default-roles