# Submit a job run with `StartJobRun`
<a name="emr-eks-jobs-submit"></a>

**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](emr-eks-jobs-CLI.md#emr-eks-jobs-parameters).

   ```
   {
     "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}}"
         }
       }
     }
   }
   ```

1. 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}}" }}}'
   ```

1. 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}}" }}}'
   ```