Hay más ejemplos de AWS SDK disponibles en el GitHub repositorio de [ejemplos de AWS Doc SDK](https://github.com/awsdocs/aws-doc-sdk-examples).
Las traducciones son generadas a través de traducción automática. En caso de conflicto entre la traducción y la version original de inglés, prevalecerá la version en inglés.
# Ejemplos básicos de Amazon EMR mediante AWS SDKs
Los siguientes ejemplos de código muestran cómo utilizar los conceptos básicos de Amazon EMR con. AWS SDKs
**Contents**
+ [Acciones](emr_code_examples_actions.md)
+ [`AddJobFlowSteps`](emr_example_emr_AddJobFlowSteps_section.md)
+ [`DescribeCluster`](emr_example_emr_DescribeCluster_section.md)
+ [`DescribeStep`](emr_example_emr_DescribeStep_section.md)
+ [`ListSteps`](emr_example_emr_ListSteps_section.md)
+ [`RunJobFlow`](emr_example_emr_RunJobFlow_section.md)
+ [`TerminateJobFlows`](emr_example_emr_TerminateJobFlows_section.md)
# Acciones para Amazon EMR mediante AWS SDKs
Los siguientes ejemplos de código muestran cómo realizar acciones individuales de Amazon EMR con. AWS SDKs Cada ejemplo incluye un enlace a GitHub, donde puede encontrar instrucciones para configurar y ejecutar el código.
Estos fragmentos llaman a la API de Amazon EMR y son fragmentos de código de programas más grandes que se deben ejecutar en contexto. Puede ver las acciones en contexto en [Escenarios para el uso de Amazon EMR AWS SDKs](emr_code_examples_scenarios.md).
Los siguientes ejemplos incluyen solo las acciones que se utilizan con mayor frecuencia. Para ver una lista completa, consulte la [Referencia de la API de Amazon EMR](https://docs.aws.amazon.com/emr/latest/APIReference/Welcome.html).
**Topics**
+ [`AddJobFlowSteps`](emr_example_emr_AddJobFlowSteps_section.md)
+ [`DescribeCluster`](emr_example_emr_DescribeCluster_section.md)
+ [`DescribeStep`](emr_example_emr_DescribeStep_section.md)
+ [`ListSteps`](emr_example_emr_ListSteps_section.md)
+ [`RunJobFlow`](emr_example_emr_RunJobFlow_section.md)
+ [`TerminateJobFlows`](emr_example_emr_TerminateJobFlows_section.md)
# `AddJobFlowSteps`Úselo con un AWS SDK
Los siguientes ejemplos de código muestran cómo utilizar `AddJobFlowSteps`.
------
#### [ Python ]
**SDK para Python (Boto3)**
Hay más en marcha GitHub. Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/emr#code-examples).
Agregue un paso de Spark, que el clúster ejecuta en cuanto se agrega.
```
def add_step(cluster_id, name, script_uri, script_args, emr_client):
"""
Adds a job step to the specified cluster. This example adds a Spark
step, which is run by the cluster as soon as it is added.
:param cluster_id: The ID of the cluster.
:param name: The name of the step.
:param script_uri: The URI where the Python script is stored.
:param script_args: Arguments to pass to the Python script.
:param emr_client: The Boto3 EMR client object.
:return: The ID of the newly added step.
"""
try:
response = emr_client.add_job_flow_steps(
JobFlowId=cluster_id,
Steps=[
{
"Name": name,
"ActionOnFailure": "CONTINUE",
"HadoopJarStep": {
"Jar": "command-runner.jar",
"Args": [
"spark-submit",
"--deploy-mode",
"cluster",
script_uri,
*script_args,
],
},
}
],
)
step_id = response["StepIds"][0]
logger.info("Started step with ID %s", step_id)
except ClientError:
logger.exception("Couldn't start step %s with URI %s.", name, script_uri)
raise
else:
return step_id
```
Ejecute un comando del sistema de archivos de Amazon EMR (EMRFS) como paso de trabajo en un clúster. Esto se puede utilizar para automatizar los comandos de EMRFS en un clúster en lugar de ejecutarlos manualmente a través de una conexión SSH.
```
import boto3
from botocore.exceptions import ClientError
def add_emrfs_step(command, bucket_url, cluster_id, emr_client):
"""
Add an EMRFS command as a job flow step to an existing cluster.
:param command: The EMRFS command to run.
:param bucket_url: The URL of a bucket that contains tracking metadata.
:param cluster_id: The ID of the cluster to update.
:param emr_client: The Boto3 Amazon EMR client object.
:return: The ID of the added job flow step. Status can be tracked by calling
the emr_client.describe_step() function.
"""
job_flow_step = {
"Name": "Example EMRFS Command Step",
"ActionOnFailure": "CONTINUE",
"HadoopJarStep": {
"Jar": "command-runner.jar",
"Args": ["/usr/bin/emrfs", command, bucket_url],
},
}
try:
response = emr_client.add_job_flow_steps(
JobFlowId=cluster_id, Steps=[job_flow_step]
)
step_id = response["StepIds"][0]
print(f"Added step {step_id} to cluster {cluster_id}.")
except ClientError:
print(f"Couldn't add a step to cluster {cluster_id}.")
raise
else:
return step_id
def usage_demo():
emr_client = boto3.client("emr")
# Assumes the first waiting cluster has EMRFS enabled and has created metadata
# with the default name of 'EmrFSMetadata'.
cluster = emr_client.list_clusters(ClusterStates=["WAITING"])["Clusters"][0]
add_emrfs_step(
"sync", "s3://elasticmapreduce/samples/cloudfront", cluster["Id"], emr_client
)
if __name__ == "__main__":
usage_demo()
```
+ Para obtener más información sobre la API, consulta [AddJobFlowSteps](https://docs.aws.amazon.com/goto/boto3/elasticmapreduce-2009-03-31/AddJobFlowSteps)la *AWS Referencia de API de SDK for Python (Boto3*).
------
#### [ SAP ABAP ]
**SDK para SAP ABAP**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/emr#code-examples).
```
TRY.
" Build args list for Spark submit
DATA lt_args TYPE /aws1/cl_emrxmlstringlist_w=>tt_xmlstringlist.
APPEND NEW /aws1/cl_emrxmlstringlist_w( 'spark-submit' ) TO lt_args.
APPEND NEW /aws1/cl_emrxmlstringlist_w( '--deploy-mode' ) TO lt_args.
APPEND NEW /aws1/cl_emrxmlstringlist_w( 'cluster' ) TO lt_args.
APPEND NEW /aws1/cl_emrxmlstringlist_w( iv_script_uri ) TO lt_args.
APPEND LINES OF it_script_args TO lt_args.
" Create step configuration
DATA(lo_hadoop_jar_step) = NEW /aws1/cl_emrhadoopjarstepcfg(
iv_jar = 'command-runner.jar'
it_args = lt_args
).
DATA(lo_step_config) = NEW /aws1/cl_emrstepconfig(
iv_name = iv_name
iv_actiononfailure = 'CONTINUE'
io_hadoopjarstep = lo_hadoop_jar_step
).
DATA lt_steps TYPE /aws1/cl_emrstepconfig=>tt_stepconfiglist.
APPEND lo_step_config TO lt_steps.
DATA(lo_result) = lo_emr->addjobflowsteps(
iv_jobflowid = iv_cluster_id
it_steps = lt_steps
).
" Get first step ID
DATA(lt_step_ids) = lo_result->get_stepids( ).
READ TABLE lt_step_ids INDEX 1 INTO DATA(lo_step_id_obj).
IF sy-subrc = 0.
ov_step_id = lo_step_id_obj->get_value( ).
MESSAGE |Step added with ID { ov_step_id }| TYPE 'I'.
ENDIF.
CATCH /aws1/cx_emrinternalservererr INTO DATA(lo_internal_error).
DATA(lv_error) = lo_internal_error->if_message~get_text( ).
MESSAGE lv_error TYPE 'E'.
ENDTRY.
```
+ Para obtener más información sobre la API, consulte [AddJobFlowSteps](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)la *referencia sobre la API ABAP del AWS SDK para SAP*.
------
# Úselo `DescribeCluster` con un AWS SDK o CLI
Los siguientes ejemplos de código muestran cómo utilizar `DescribeCluster`.
------
#### [ CLI ]
**AWS CLI**
Comando:
```
aws emr describe-cluster --cluster-id j-XXXXXXXX
```
Salida:
```
For release-label based uniform instance groups cluster:
{
"Cluster": {
"Status": {
"Timeline": {
"ReadyDateTime": 1436475075.199,
"CreationDateTime": 1436474656.563,
},
"State": "WAITING",
"StateChangeReason": {
"Message": "Waiting for steps to run"
}
},
"Ec2InstanceAttributes": {
"ServiceAccessSecurityGroup": "sg-xxxxxxxx",
"EmrManagedMasterSecurityGroup": "sg-xxxxxxxx",
"IamInstanceProfile": "EMR_EC2_DefaultRole",
"Ec2KeyName": "myKey",
"Ec2AvailabilityZone": "us-east-1c",
"EmrManagedSlaveSecurityGroup": "sg-yyyyyyyyy"
},
"Name": "My Cluster",
"ServiceRole": "EMR_DefaultRole",
"Tags": [],
"TerminationProtected": true,
"UnhealthyNodeReplacement": true,
"ReleaseLabel": "emr-4.0.0",
"NormalizedInstanceHours": 96,
"InstanceGroups": [
{
"RequestedInstanceCount": 2,
"Status": {
"Timeline": {
"ReadyDateTime": 1436475074.245,
"CreationDateTime": 1436474656.564,
"EndDateTime": 1436638158.387
},
"State": "RUNNING",
"StateChangeReason": {
"Message": "",
}
},
"Name": "CORE",
"InstanceGroupType": "CORE",
"Id": "ig-YYYYYYY",
"Configurations": [],
"InstanceType": "m3.large",
"Market": "ON_DEMAND",
"RunningInstanceCount": 2
},
{
"RequestedInstanceCount": 1,
"Status": {
"Timeline": {
"ReadyDateTime": 1436475074.245,
"CreationDateTime": 1436474656.564,
"EndDateTime": 1436638158.387
},
"State": "RUNNING",
"StateChangeReason": {
"Message": "",
}
},
"Name": "MASTER",
"InstanceGroupType": "MASTER",
"Id": "ig-XXXXXXXXX",
"Configurations": [],
"InstanceType": "m3.large",
"Market": "ON_DEMAND",
"RunningInstanceCount": 1
}
],
"Applications": [
{
"Name": "Hadoop"
}
],
"VisibleToAllUsers": true,
"BootstrapActions": [],
"MasterPublicDnsName": "ec2-54-147-144-78.compute-1.amazonaws.com",
"AutoTerminate": false,
"Id": "j-XXXXXXXX",
"Configurations": [
{
"Properties": {
"fs.s3.consistent.retryPeriodSeconds": "20",
"fs.s3.enableServerSideEncryption": "true",
"fs.s3.consistent": "false",
"fs.s3.consistent.retryCount": "2"
},
"Classification": "emrfs-site"
}
]
}
}
For release-label based instance fleet cluster:
{
"Cluster": {
"Status": {
"Timeline": {
"ReadyDateTime": 1487897289.705,
"CreationDateTime": 1487896933.942
},
"State": "WAITING",
"StateChangeReason": {
"Message": "Waiting for steps to run"
}
},
"Ec2InstanceAttributes": {
"EmrManagedMasterSecurityGroup": "sg-xxxxx",
"RequestedEc2AvailabilityZones": [],
"RequestedEc2SubnetIds": [],
"IamInstanceProfile": "EMR_EC2_DefaultRole",
"Ec2AvailabilityZone": "us-east-1a",
"EmrManagedSlaveSecurityGroup": "sg-xxxxx"
},
"Name": "My Cluster",
"ServiceRole": "EMR_DefaultRole",
"Tags": [],
"TerminationProtected": false,
"UnhealthyNodeReplacement": false,
"ReleaseLabel": "emr-5.2.0",
"NormalizedInstanceHours": 472,
"InstanceCollectionType": "INSTANCE_FLEET",
"InstanceFleets": [
{
"Status": {
"Timeline": {
"ReadyDateTime": 1487897212.74,
"CreationDateTime": 1487896933.948
},
"State": "RUNNING",
"StateChangeReason": {
"Message": ""
}
},
"ProvisionedSpotCapacity": 1,
"Name": "MASTER",
"InstanceFleetType": "MASTER",
"LaunchSpecifications": {
"SpotSpecification": {
"TimeoutDurationMinutes": 60,
"TimeoutAction": "TERMINATE_CLUSTER"
}
},
"TargetSpotCapacity": 1,
"ProvisionedOnDemandCapacity": 0,
"InstanceTypeSpecifications": [
{
"BidPrice": "0.5",
"InstanceType": "m3.xlarge",
"WeightedCapacity": 1
}
],
"Id": "if-xxxxxxx",
"TargetOnDemandCapacity": 0
}
],
"Applications": [
{
"Version": "2.7.3",
"Name": "Hadoop"
}
],
"ScaleDownBehavior": "TERMINATE_AT_INSTANCE_HOUR",
"VisibleToAllUsers": true,
"BootstrapActions": [],
"MasterPublicDnsName": "ec2-xxx-xx-xxx-xx.compute-1.amazonaws.com",
"AutoTerminate": false,
"Id": "j-xxxxx",
"Configurations": []
}
}
For ami based uniform instance group cluster:
{
"Cluster": {
"Status": {
"Timeline": {
"ReadyDateTime": 1399400564.432,
"CreationDateTime": 1399400268.62
},
"State": "WAITING",
"StateChangeReason": {
"Message": "Waiting for steps to run"
}
},
"Ec2InstanceAttributes": {
"IamInstanceProfile": "EMR_EC2_DefaultRole",
"Ec2AvailabilityZone": "us-east-1c"
},
"Name": "My Cluster",
"Tags": [],
"TerminationProtected": true,
"UnhealthyNodeReplacement": true,
"RunningAmiVersion": "2.5.4",
"InstanceGroups": [
{
"RequestedInstanceCount": 1,
"Status": {
"Timeline": {
"ReadyDateTime": 1399400558.848,
"CreationDateTime": 1399400268.621
},
"State": "RUNNING",
"StateChangeReason": {
"Message": ""
}
},
"Name": "Master instance group",
"InstanceGroupType": "MASTER",
"InstanceType": "m1.small",
"Id": "ig-ABCD",
"Market": "ON_DEMAND",
"RunningInstanceCount": 1
},
{
"RequestedInstanceCount": 2,
"Status": {
"Timeline": {
"ReadyDateTime": 1399400564.439,
"CreationDateTime": 1399400268.621
},
"State": "RUNNING",
"StateChangeReason": {
"Message": ""
}
},
"Name": "Core instance group",
"InstanceGroupType": "CORE",
"InstanceType": "m1.small",
"Id": "ig-DEF",
"Market": "ON_DEMAND",
"RunningInstanceCount": 2
}
],
"Applications": [
{
"Version": "1.0.3",
"Name": "hadoop"
}
],
"BootstrapActions": [],
"VisibleToAllUsers": false,
"RequestedAmiVersion": "2.4.2",
"LogUri": "s3://myLogUri/",
"AutoTerminate": false,
"Id": "j-XXXXXXXX"
}
}
```
+ Para obtener más información sobre la API, consulte [DescribeCluster](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/emr/describe-cluster.html)la *Referencia de AWS CLI comandos*.
------
#### [ Python ]
**SDK para Python (Boto3)**
Hay más información al respecto GitHub. Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/emr#code-examples).
```
def describe_cluster(cluster_id, emr_client):
"""
Gets detailed information about a cluster.
:param cluster_id: The ID of the cluster to describe.
:param emr_client: The Boto3 EMR client object.
:return: The retrieved cluster information.
"""
try:
response = emr_client.describe_cluster(ClusterId=cluster_id)
cluster = response["Cluster"]
logger.info("Got data for cluster %s.", cluster["Name"])
except ClientError:
logger.exception("Couldn't get data for cluster %s.", cluster_id)
raise
else:
return cluster
```
+ Para obtener más información sobre la API, consulta [DescribeCluster](https://docs.aws.amazon.com/goto/boto3/elasticmapreduce-2009-03-31/DescribeCluster)la *AWS Referencia de API de SDK for Python (Boto3*).
------
#### [ SAP ABAP ]
**SDK para SAP ABAP**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/emr#code-examples).
```
TRY.
oo_result = lo_emr->describecluster(
iv_clusterid = iv_cluster_id
).
DATA(lo_cluster) = oo_result->get_cluster( ).
DATA(lv_cluster_name) = lo_cluster->get_name( ).
MESSAGE |Retrieved cluster information for { lv_cluster_name }| TYPE 'I'.
CATCH /aws1/cx_emrinternalserverex INTO DATA(lo_internal_error).
DATA(lv_error) = lo_internal_error->if_message~get_text( ).
MESSAGE lv_error TYPE 'E'.
CATCH /aws1/cx_emrinvalidrequestex INTO DATA(lo_invalid_error).
lv_error = lo_invalid_error->if_message~get_text( ).
MESSAGE lv_error TYPE 'E'.
ENDTRY.
```
+ Para obtener más información sobre la API, consulte [DescribeCluster](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)la *referencia sobre la API ABAP del AWS SDK para SAP*.
------
# Úselo `DescribeStep` con un AWS SDK o CLI
Los siguientes ejemplos de código muestran cómo utilizar `DescribeStep`.
------
#### [ CLI ]
**AWS CLI**
El siguiente comando describe un paso con el ID del paso `s-3LZC0QUT43AM` en un clúster con el ID de clúster `j-3SD91U2E1L2QX`:
```
aws emr describe-step --cluster-id j-3SD91U2E1L2QX --step-id s-3LZC0QUT43AM
```
Salida:
```
{
"Step": {
"Status": {
"Timeline": {
"EndDateTime": 1433200470.481,
"CreationDateTime": 1433199926.597,
"StartDateTime": 1433200404.959
},
"State": "COMPLETED",
"StateChangeReason": {}
},
"Config": {
"Args": [
"s3://us-west-2.elasticmapreduce/libs/hive/hive-script",
"--base-path",
"s3://us-west-2.elasticmapreduce/libs/hive/",
"--install-hive",
"--hive-versions",
"0.13.1"
],
"Jar": "s3://us-west-2.elasticmapreduce/libs/script-runner/script-runner.jar",
"Properties": {}
},
"Id": "s-3LZC0QUT43AM",
"ActionOnFailure": "TERMINATE_CLUSTER",
"Name": "Setup hive"
}
}
```
+ Para obtener más información sobre la API, consulte [DescribeStep](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/emr/describe-step.html)la *Referencia de AWS CLI comandos*.
------
#### [ Python ]
**SDK para Python (Boto3)**
Hay más información al respecto GitHub. Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/emr#code-examples).
```
def describe_step(cluster_id, step_id, emr_client):
"""
Gets detailed information about the specified step, including the current state of
the step.
:param cluster_id: The ID of the cluster.
:param step_id: The ID of the step.
:param emr_client: The Boto3 EMR client object.
:return: The retrieved information about the specified step.
"""
try:
response = emr_client.describe_step(ClusterId=cluster_id, StepId=step_id)
step = response["Step"]
logger.info("Got data for step %s.", step_id)
except ClientError:
logger.exception("Couldn't get data for step %s.", step_id)
raise
else:
return step
```
+ Para obtener más información sobre la API, consulta [DescribeStep](https://docs.aws.amazon.com/goto/boto3/elasticmapreduce-2009-03-31/DescribeStep)la *AWS Referencia de API de SDK for Python (Boto3*).
------
#### [ SAP ABAP ]
**SDK para SAP ABAP**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/emr#code-examples).
```
TRY.
oo_result = lo_emr->describestep(
iv_clusterid = iv_cluster_id
iv_stepid = iv_step_id
).
DATA(lo_step) = oo_result->get_step( ).
DATA(lv_step_name) = lo_step->get_name( ).
MESSAGE |Retrieved step information for { lv_step_name }| TYPE 'I'.
CATCH /aws1/cx_emrinternalserverex INTO DATA(lo_internal_error).
DATA(lv_error) = lo_internal_error->if_message~get_text( ).
MESSAGE lv_error TYPE 'E'.
CATCH /aws1/cx_emrinvalidrequestex INTO DATA(lo_invalid_error).
lv_error = lo_invalid_error->if_message~get_text( ).
MESSAGE lv_error TYPE 'E'.
ENDTRY.
```
+ Para obtener más información sobre la API, consulte [DescribeStep](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)la *referencia sobre la API ABAP del AWS SDK para SAP*.
------
# Úselo `ListSteps` con un AWS SDK o CLI
Los siguientes ejemplos de código muestran cómo utilizar `ListSteps`.
------
#### [ CLI ]
**AWS CLI**
El siguiente comando muestra todos los pasos de un clúster con el ID del clúster `j-3SD91U2E1L2QX`:
```
aws emr list-steps --cluster-id j-3SD91U2E1L2QX
```
+ Para obtener más información sobre la API, consulte [ListSteps](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/emr/list-steps.html)la *Referencia de AWS CLI comandos*.
------
#### [ Python ]
**SDK para Python (Boto3)**
Hay más información al respecto GitHub. Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/emr#code-examples).
```
def list_steps(cluster_id, emr_client):
"""
Gets a list of steps for the specified cluster. In this example, all steps are
returned, including completed and failed steps.
:param cluster_id: The ID of the cluster.
:param emr_client: The Boto3 EMR client object.
:return: The list of steps for the specified cluster.
"""
try:
response = emr_client.list_steps(ClusterId=cluster_id)
steps = response["Steps"]
logger.info("Got %s steps for cluster %s.", len(steps), cluster_id)
except ClientError:
logger.exception("Couldn't get steps for cluster %s.", cluster_id)
raise
else:
return steps
```
+ Para obtener más información sobre la API, consulta [ListSteps](https://docs.aws.amazon.com/goto/boto3/elasticmapreduce-2009-03-31/ListSteps)la *AWS Referencia de API de SDK for Python (Boto3*).
------
#### [ SAP ABAP ]
**SDK para SAP ABAP**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/emr#code-examples).
```
TRY.
oo_result = lo_emr->liststeps(
iv_clusterid = iv_cluster_id
).
DATA(lt_steps) = oo_result->get_steps( ).
DATA(lv_step_count) = lines( lt_steps ).
MESSAGE |Retrieved { lv_step_count } steps for cluster| TYPE 'I'.
CATCH /aws1/cx_emrinternalserverex INTO DATA(lo_internal_error).
DATA(lv_error) = lo_internal_error->if_message~get_text( ).
MESSAGE lv_error TYPE 'E'.
CATCH /aws1/cx_emrinvalidrequestex INTO DATA(lo_invalid_error).
lv_error = lo_invalid_error->if_message~get_text( ).
MESSAGE lv_error TYPE 'E'.
ENDTRY.
```
+ Para obtener más información sobre la API, consulte [ListSteps](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)la *referencia sobre la API ABAP del AWS SDK para SAP*.
------
# Úselo `RunJobFlow` con un SDK AWS
Los siguientes ejemplos de código muestran cómo utilizar `RunJobFlow`.
------
#### [ Python ]
**SDK para Python (Boto3)**
Hay más en marcha GitHub. Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](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 obtener más información sobre la API, consulta [RunJobFlow](https://docs.aws.amazon.com/goto/boto3/elasticmapreduce-2009-03-31/RunJobFlow)la *AWS Referencia de API de SDK for Python (Boto3*).
------
#### [ SAP ABAP ]
**SDK para SAP ABAP**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](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 obtener más información sobre la API, consulte [RunJobFlow](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)la *referencia sobre la API ABAP del AWS SDK para SAP*.
------
# Úselo `TerminateJobFlows` con un SDK AWS
Los siguientes ejemplos de código muestran cómo utilizar `TerminateJobFlows`.
------
#### [ Python ]
**SDK para Python (Boto3)**
Hay más en marcha GitHub. Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/emr#code-examples).
```
def terminate_cluster(cluster_id, emr_client):
"""
Terminates a cluster. This terminates all instances in the cluster and cannot
be undone. Any data not saved elsewhere, such as in an Amazon S3 bucket, is lost.
:param cluster_id: The ID of the cluster to terminate.
:param emr_client: The Boto3 EMR client object.
"""
try:
emr_client.terminate_job_flows(JobFlowIds=[cluster_id])
logger.info("Terminated cluster %s.", cluster_id)
except ClientError:
logger.exception("Couldn't terminate cluster %s.", cluster_id)
raise
```
+ Para obtener más información sobre la API, consulta [TerminateJobFlows](https://docs.aws.amazon.com/goto/boto3/elasticmapreduce-2009-03-31/TerminateJobFlows)la *AWS Referencia de API de SDK for Python (Boto3*).
------
#### [ SAP ABAP ]
**SDK para SAP ABAP**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/sap-abap/services/emr#code-examples).
```
TRY.
DATA lt_cluster_ids TYPE /aws1/cl_emrxmlstringlist_w=>tt_xmlstringlist.
APPEND NEW /aws1/cl_emrxmlstringlist_w( iv_cluster_id ) TO lt_cluster_ids.
lo_emr->terminatejobflows(
it_jobflowids = lt_cluster_ids
).
MESSAGE 'EMR cluster terminated 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'.
ENDTRY.
```
+ Para obtener más información sobre la API, consulte [TerminateJobFlows](https://docs.aws.amazon.com/sdk-for-sap-abap/v1/api/latest/index.html)la *referencia sobre la API ABAP del AWS SDK para SAP*.
------