Submit a job run with StartJobRun - Amazon EMR

Submit a job run with StartJobRun

To submit a job run with a JSON file with specified parameters
  1. Create a start-job-run-request.json file and specify the required parameters for your job run, as the following example JSON file demonstrates. For more information about the parameters, see Options for configuring a job run.

    { "name": "myjob", "virtualClusterId": "123456", "executionRoleArn": "iam_role_name_for_job_execution", "releaseLabel": "emr-6.2.0-latest", "jobDriver": { "sparkSubmitJobDriver": { "entryPoint": "entryPoint_location", "entryPointArguments": ["argument1", "argument2", ...], "sparkSubmitParameters": "--class <main_class> --conf spark.executor.instances=2 --conf spark.executor.memory=2G --conf spark.executor.cores=2 --conf spark.driver.cores=1" } }, "configurationOverrides": { "applicationConfiguration": [ { "classification": "spark-defaults", "properties": { "spark.driver.memory":"2G" } } ], "monitoringConfiguration": { "persistentAppUI": "ENABLED", "cloudWatchMonitoringConfiguration": { "logGroupName": "my_log_group", "logStreamNamePrefix": "log_stream_prefix" }, "s3MonitoringConfiguration": { "logUri": "s3://my_s3_log_location" } } } }
  2. Use the start-job-run command with a path to the start-job-run-request.json file stored locally.

    aws emr-containers start-job-run \ --cli-input-json file://./start-job-run-request.json
To start a job run using the start-job-run command
  1. Supply all the specified parameters in the StartJobRun command, as the following example demonstrates.

    aws emr-containers start-job-run \ --virtual-cluster-id 123456 \ --name myjob \ --execution-role-arn execution-role-arn \ --release-label emr-6.2.0-latest \ --job-driver '{"sparkSubmitJobDriver": {"entryPoint": "entryPoint_location", "entryPointArguments": ["argument1", "argument2", ...], "sparkSubmitParameters": "--class <main_class> --conf spark.executor.instances=2 --conf spark.executor.memory=2G --conf spark.executor.cores=2 --conf spark.driver.cores=1"}}' \ --configuration-overrides '{"applicationConfiguration": [{"classification": "spark-defaults", "properties": {"spark.driver.memory": "2G"}}], "monitoringConfiguration": {"cloudWatchMonitoringConfiguration": {"logGroupName": "log_group_name", "logStreamNamePrefix": "log_stream_prefix"}, "persistentAppUI":"ENABLED", "s3MonitoringConfiguration": {"logUri": "s3://my_s3_log_location" }}}'
  2. For Spark SQL, supply all the specified parameters in the StartJobRun command, as the following example demonstrates.

    aws emr-containers start-job-run \ --virtual-cluster-id 123456 \ --name myjob \ --execution-role-arn execution-role-arn \ --release-label emr-6.7.0-latest \ --job-driver '{"sparkSqlJobDriver": {"entryPoint": "entryPoint_location", "sparkSqlParameters": "--conf spark.executor.instances=2 --conf spark.executor.memory=2G --conf spark.executor.cores=2 --conf spark.driver.cores=1"}}' \ --configuration-overrides '{"applicationConfiguration": [{"classification": "spark-defaults", "properties": {"spark.driver.memory": "2G"}}], "monitoringConfiguration": {"cloudWatchMonitoringConfiguration": {"logGroupName": "log_group_name", "logStreamNamePrefix": "log_stream_prefix"}, "persistentAppUI":"ENABLED", "s3MonitoringConfiguration": {"logUri": "s3://my_s3_log_location" }}}'