Auto-termination is supported in Amazon EMR releases 5.30.0 and 6.1.0 and later. For more information, see Using an auto-termination policy.
Creates or updates an auto-termination policy for an Amazon EMR cluster. An auto-termination policy defines the amount of idle time in seconds after which a cluster automatically terminates. For alternative cluster termination options, see Control cluster termination.
Parameters:
-
cluster_id
(Optional[ClusterId], default:
None
)
–
Specifies the ID of the Amazon EMR cluster to which the auto-termination policy will be attached.
-
auto_termination_policy
(Optional[AutoTerminationPolicy], default:
None
)
–
Specifies the auto-termination policy to attach to the cluster.
Raises:
Source code in docs_src/capo_emr/_services/emr.py
| def put_auto_termination_policy(
self,
*,
config_overrides: Optional[EMRClientConfig] = None,
cluster_id: Optional["capo_emr.types.cluster_id.ClusterId"] = None,
auto_termination_policy: Optional[
"capo_emr.types.auto_termination_policy.AutoTerminationPolicy"
] = None,
) -> "capo_emr.types.put_auto_termination_policy_output.PutAutoTerminationPolicyOutput":
"""<note> <p>Auto-termination is supported in Amazon EMR releases 5.30.0 and 6.1.0 and later. For more information, see <a href="https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-auto-termination-policy.html">Using an auto-termination policy</a>.</p> </note> <p>Creates or updates an auto-termination policy for an Amazon EMR cluster. An auto-termination policy defines the amount of idle time in seconds after which a cluster automatically terminates. For alternative cluster termination options, see <a href="https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-plan-termination.html">Control cluster termination</a>.</p>
Args:
cluster_id: <p>Specifies the ID of the Amazon EMR cluster to which the auto-termination policy will be attached.</p>
auto_termination_policy: <p>Specifies the auto-termination policy to attach to the cluster.</p>
Raises:
capo_emr.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
def _handler(
req: "OperationRequest[capo_emr.types.put_auto_termination_policy_input.PutAutoTerminationPolicyInput]",
) -> OperationResponse[
"capo_emr.types.put_auto_termination_policy_output.PutAutoTerminationPolicyOutput"
]:
import capo_emr._operations.elastic_map_reduce.put_auto_termination_policy
output, http_response = (
capo_emr._operations.elastic_map_reduce.put_auto_termination_policy.put_auto_termination_policy(
req.options, req.input
)
)
return OperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("PutAutoTerminationPolicy")
)
input_: capo_emr.types.put_auto_termination_policy_input.PutAutoTerminationPolicyInput = {}
if cluster_id is not None:
input_["cluster_id"] = cluster_id
if auto_termination_policy is not None:
input_["auto_termination_policy"] = auto_termination_policy
response = execute_pipeline(
OperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output
|