set_termination_protection ¶

def set_termination_protection(
    self,
    *,
    config_overrides: Optional[EMRClientConfig] = None,
    job_flow_ids: Optional["capo_emr.types.xml_string_list.XmlStringList"] = None,
    termination_protected: Optional["capo_emr.types.boolean.Boolean"] = None,
) -> None:
    """<p>SetTerminationProtection locks a cluster (job flow) so the Amazon EC2 instances in the cluster cannot be terminated by user intervention, an API call, or in the event of a job-flow error. The cluster still terminates upon successful completion of the job flow. Calling <code>SetTerminationProtection</code> on a cluster is similar to calling the Amazon EC2 <code>DisableAPITermination</code> API on all Amazon EC2 instances in a cluster.</p> <p> <code>SetTerminationProtection</code> is used to prevent accidental termination of a cluster and to ensure that in the event of an error, the instances persist so that you can recover any data stored in their ephemeral instance storage.</p> <p> To terminate a cluster that has been locked by setting <code>SetTerminationProtection</code> to <code>true</code>, you must first unlock the job flow by a subsequent call to <code>SetTerminationProtection</code> in which you set the value to <code>false</code>. </p> <p> For more information, see <a href="https://docs.aws.amazon.com/emr/latest/ManagementGuide/UsingEMR_TerminationProtection.html">Managing Cluster Termination</a> in the <i>Amazon EMR Management Guide</i>. </p>

    Args:
        job_flow_ids: <p> A list of strings that uniquely identify the clusters to protect. This identifier is returned by <a>RunJobFlow</a> and can also be obtained from <a>DescribeJobFlows</a> . </p>
        termination_protected: <p>A Boolean that indicates whether to protect the cluster and prevent the Amazon EC2 instances in the cluster from shutting down due to API calls, user intervention, or job-flow error.</p>

    Raises:
        capo_emr.errors.internal_server_error.InternalServerError: <p>Indicates that an error occurred while processing the request and that the request was not completed.</p>
        capo_emr.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_emr.types.set_termination_protection_input.SetTerminationProtectionInput]",
    ) -> OperationResponse[None]:
        import capo_emr._operations.elastic_map_reduce.set_termination_protection

        output, http_response = (
            capo_emr._operations.elastic_map_reduce.set_termination_protection.set_termination_protection(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("SetTerminationProtection")
    )
    input_: capo_emr.types.set_termination_protection_input.SetTerminationProtectionInput = {}
    if job_flow_ids is not None:
        input_["job_flow_ids"] = job_flow_ids
    if termination_protected is not None:
        input_["termination_protected"] = termination_protected

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output