Amazon EMR
Management Guide

Using the AWS SDK for Java to Create an Amazon EMR Cluster

The AWS SDK for Java provides three packages with Amazon EMR functionality:

For more information about these packages, see the AWS SDK for Java API Reference.

The following example illustrates how the SDKs can simplify programming with Amazon EMR. The code sample below uses the StepFactory object, a helper class for creating common Amazon EMR step types, to create an interactive Hive cluster with debugging enabled.

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) { AWSCredentials credentials_profile = null; try { credentials_profile = new ProfileCredentialsProvider("default").getCredentials(); // 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(new AWSStaticCredentialsProvider(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()); } }

At minimum, you must pass a service role and jobflow role corresponding to EMR_DefaultRole and EMR_EC2_DefaultRole, respectively. You can do this by invoking this AWS CLI command for the same account. First, look to see if the roles already exist:

aws iam list-roles | grep EMR

Both the instance profile (EMR_EC2_DefaultRole) and the service role (EMR_DefaultRole) will be displayed if they exist:

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

If the default roles do not exist, you can use the following AWS CLI command to create them:

aws emr create-default-roles