Há mais exemplos de AWS SDK disponíveis no repositório [AWS Doc SDK Examples](https://github.com/awsdocs/aws-doc-sdk-examples) GitHub .

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# Use `RunJobFlow` com um AWS SDK
<a name="emr_example_emr_RunJobFlow_section"></a>

Os exemplos de código a seguir mostram como usar o `RunJobFlow`.

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#### [ Python ]

**SDK para Python (Boto3)**  
 Tem mais sobre GitHub. Encontre o exemplo completo e saiba como configurar e executar no [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/emr#code-examples). 

```
def run_job_flow(
    name,
    log_uri,
    keep_alive,
    applications,
    job_flow_role,
    service_role,
    security_groups,
    steps,
    emr_client,
):
    """
    Runs a job flow with the specified steps. A job flow creates a cluster of
    instances and adds steps to be run on the cluster. Steps added to the cluster
    are run as soon as the cluster is ready.

    This example uses the 'emr-5.30.1' release. A list of recent releases can be
    found here:
        https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-release-components.html.

    :param name: The name of the cluster.
    :param log_uri: The URI where logs are stored. This can be an Amazon S3 bucket URL,
                    such as 's3://my-log-bucket'.
    :param keep_alive: When True, the cluster is put into a Waiting state after all
                       steps are run. When False, the cluster terminates itself when
                       the step queue is empty.
    :param applications: The applications to install on each instance in the cluster,
                         such as Hive or Spark.
    :param job_flow_role: The IAM role assumed by the cluster.
    :param service_role: The IAM role assumed by the service.
    :param security_groups: The security groups to assign to the cluster instances.
                            Amazon EMR adds all needed rules to these groups, so
                            they can be empty if you require only the default rules.
    :param steps: The job flow steps to add to the cluster. These are run in order
                  when the cluster is ready.
    :param emr_client: The Boto3 EMR client object.
    :return: The ID of the newly created cluster.
    """
    try:
        response = emr_client.run_job_flow(
            Name=name,
            LogUri=log_uri,
            ReleaseLabel="emr-5.30.1",
            Instances={
                "MasterInstanceType": "m5.xlarge",
                "SlaveInstanceType": "m5.xlarge",
                "InstanceCount": 3,
                "KeepJobFlowAliveWhenNoSteps": keep_alive,
                "EmrManagedMasterSecurityGroup": security_groups["manager"].id,
                "EmrManagedSlaveSecurityGroup": security_groups["worker"].id,
            },
            Steps=[
                {
                    "Name": step["name"],
                    "ActionOnFailure": "CONTINUE",
                    "HadoopJarStep": {
                        "Jar": "command-runner.jar",
                        "Args": [
                            "spark-submit",
                            "--deploy-mode",
                            "cluster",
                            step["script_uri"],
                            *step["script_args"],
                        ],
                    },
                }
                for step in steps
            ],
            Applications=[{"Name": app} for app in applications],
            JobFlowRole=job_flow_role.name,
            ServiceRole=service_role.name,
            EbsRootVolumeSize=10,
            VisibleToAllUsers=True,
        )
        cluster_id = response["JobFlowId"]
        logger.info("Created cluster %s.", cluster_id)
    except ClientError:
        logger.exception("Couldn't create cluster.")
        raise
    else:
        return cluster_id
```
+  Para obter detalhes da API, consulte a [RunJobFlow](https://docs.aws.amazon.com/goto/boto3/elasticmapreduce-2009-03-31/RunJobFlow)Referência da API *AWS SDK for Python (Boto3*). 

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#### [ SAP ABAP ]

**SDK para SAP ABAP**  
 Tem mais sobre GitHub. Encontre o exemplo completo e saiba como configurar e executar no [AWS Code Examples Repository](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/emr#code-examples). 

```
    TRY.
        " Create instances configuration
        DATA(lo_instances) = NEW /aws1/cl_emrjobflowinstsconfig(
          iv_masterinstancetype = 'm5.xlarge'
          iv_slaveinstancetype = 'm5.xlarge'
          iv_instancecount = 3
          iv_keepjobflowalivewhennos00 = iv_keep_alive
          iv_emrmanagedmastersecgroup = iv_primary_sec_grp
          iv_emrmanagedslavesecgroup = iv_secondary_sec_grp
        ).

        DATA(lo_result) = lo_emr->runjobflow(
          iv_name = iv_name
          iv_loguri = iv_log_uri
          iv_releaselabel = 'emr-5.30.1'
          io_instances = lo_instances
          it_steps = it_steps
          it_applications = it_applications
          iv_jobflowrole = iv_job_flow_role
          iv_servicerole = iv_service_role
          iv_ebsrootvolumesize = 10
          iv_visibletoallusers = abap_true
        ).

        ov_cluster_id = lo_result->get_jobflowid( ).
        MESSAGE 'EMR cluster created successfully.' TYPE 'I'.
      CATCH /aws1/cx_emrinternalservererr INTO DATA(lo_internal_error).
        DATA(lv_error) = lo_internal_error->if_message~get_text( ).
        MESSAGE lv_error TYPE 'E'.
      CATCH /aws1/cx_emrclientexc INTO DATA(lo_client_error).
        lv_error = lo_client_error->if_message~get_text( ).
        MESSAGE lv_error TYPE 'E'.
    ENDTRY.
```
+  Para obter detalhes da API, consulte a [RunJobFlow](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)referência da *API AWS SDK for SAP ABAP*. 

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