start_id_mapping_job ¶

def start_id_mapping_job(
    self,
    workflow_name: "capo_entityresolution.types.entity_name_or_id_mapping_workflow_arn.EntityNameOrIdMappingWorkflowArn",
    *,
    config_overrides: Optional[EntityResolutionClientConfig] = None,
    output_source_config: Optional[
        "capo_entityresolution.types.id_mapping_job_output_source_config.IdMappingJobOutputSourceConfig"
    ] = None,
    job_type: Optional["capo_entityresolution.types.job_type.JobType"] = None,
) -> "capo_entityresolution.types.start_id_mapping_job_output.StartIdMappingJobOutput":
    """<p>Starts the <code>IdMappingJob</code> of a workflow. The workflow must have previously been created using the <code>CreateIdMappingWorkflow</code> endpoint.</p>

    Args:
        workflow_name: <p>The name of the ID mapping job to be retrieved.</p>
        output_source_config: <p>A list of <code>OutputSource</code> objects.</p>
        job_type: <p> The job type for the ID mapping job.</p> <p>If the <code>jobType</code> value is set to <code>INCREMENTAL</code>, only new or changed data is processed since the last job run. This is the default value if the <code>CreateIdMappingWorkflow</code> API is configured with an <code>incrementalRunConfig</code>.</p> <p>If the <code>jobType</code> value is set to <code>BATCH</code>, all data is processed from the input source, regardless of previous job runs. This is the default value if the <code>CreateIdMappingWorkflow</code> API isn't configured with an <code>incrementalRunConfig</code>.</p> <p>If the <code>jobType</code> value is set to <code>DELETE_ONLY</code>, only deletion requests from <code>BatchDeleteUniqueIds</code> are processed.</p>

    Raises:
        capo_entityresolution.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action. </p>
        capo_entityresolution.errors.conflict_exception.ConflictException: <p>The request couldn't be processed because of conflict in the current state of the resource. Example: Workflow already exists, Schema already exists, Workflow is currently running, etc. </p>
        capo_entityresolution.errors.exceeds_limit_exception.ExceedsLimitException: <p>The request was rejected because it attempted to create resources beyond the current Entity Resolution account limits. The error message describes the limit exceeded. </p>
        capo_entityresolution.errors.internal_server_exception.InternalServerException: <p>This exception occurs when there is an internal failure in the Entity Resolution service. </p>
        capo_entityresolution.errors.resource_not_found_exception.ResourceNotFoundException: <p>The resource couldn't be found. </p>
        capo_entityresolution.errors.throttling_exception.ThrottlingException: <p>The request was denied due to request throttling. </p>
        capo_entityresolution.errors.validation_exception.ValidationException: <p>The input fails to satisfy the constraints specified by Entity Resolution. </p>
        capo_entityresolution.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_entityresolution.types.start_id_mapping_job_input.StartIdMappingJobInput]",
    ) -> OperationResponse[
        "capo_entityresolution.types.start_id_mapping_job_output.StartIdMappingJobOutput"
    ]:
        import capo_entityresolution._operations.aws_venice_service.start_id_mapping_job

        output, http_response = (
            capo_entityresolution._operations.aws_venice_service.start_id_mapping_job.start_id_mapping_job(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("StartIdMappingJob")
    )
    input_: capo_entityresolution.types.start_id_mapping_job_input.StartIdMappingJobInput = {
        "workflow_name": workflow_name
    }
    if output_source_config is not None:
        input_["output_source_config"] = output_source_config
    if job_type is not None:
        input_["job_type"] = job_type

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