Uso de AWS SDK for Java para crear un clúster de Amazon EMR

AWS SDK for Java Incluye tres paquetes con la funcionalidad Amazon EMR:

• com.amazonaws.services.elasticmapreduce

• com.amazonaws.services.elasticmapreduce.model

• com.amazonaws.services.elasticmapreduce.util

Para obtener más información sobre estos paquetes, consulte la referencia de la API de AWS SDK for Java.

En el siguiente ejemplo se ilustra cómo los SDK pueden simplificar la programación con Amazon EMR. El código de muestra siguiente utiliza el objeto StepFactory, una clase helper para crear los tipos de pasos de Amazon EMR comunes, para crear un clúster de Hive interactivo con la depuración habilitada.

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());

	}

}

Como mínimo, debe asignar un rol de servicio y un rol de flujo de trabajo correspondientes a EMR_ DefaultRole y EMR_EC2_, respectivamente. DefaultRole Para ello, puede invocar este comando para la misma cuenta. AWS CLI En primer lugar, vea si ya existen los roles:

aws iam list-roles | grep EMR

Se mostrarán tanto el perfil de la instancia (EMR_EC2_DefaultRole) como el rol de servicio (EMR_DefaultRole), si existen:

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

Si los roles predeterminados no existen, puede utilizar el siguiente comando para crearlos:

aws emr create-default-roles