stop_ingestion_job ¶

def stop_ingestion_job(
    self,
    knowledge_base_id: "capo_bedrock_agent.types.id.Id",
    data_source_id: "capo_bedrock_agent.types.id.Id",
    ingestion_job_id: "capo_bedrock_agent.types.id.Id",
    *,
    config_overrides: Optional[BedrockAgentClientConfig] = None,
) -> (
    "capo_bedrock_agent.types.stop_ingestion_job_response.StopIngestionJobResponse"
):
    """<p>Stops a currently running data ingestion job. You can send a <code>StartIngestionJob</code> request again to ingest the rest of your data when you are ready.</p>

    Args:
        knowledge_base_id: <p>The unique identifier of the knowledge base for the data ingestion job you want to stop.</p>
        data_source_id: <p>The unique identifier of the data source for the data ingestion job you want to stop.</p>
        ingestion_job_id: <p>The unique identifier of the data ingestion job you want to stop.</p>

    Raises:
        capo_bedrock_agent.errors.access_denied_exception.AccessDeniedException: <p>The request is denied because of missing access permissions.</p>
        capo_bedrock_agent.errors.conflict_exception.ConflictException: <p>There was a conflict performing an operation.</p>
        capo_bedrock_agent.errors.internal_server_exception.InternalServerException: <p>An internal server error occurred. Retry your request.</p>
        capo_bedrock_agent.errors.resource_not_found_exception.ResourceNotFoundException: <p>The specified resource Amazon Resource Name (ARN) was not found. Check the Amazon Resource Name (ARN) and try your request again.</p>
        capo_bedrock_agent.errors.throttling_exception.ThrottlingException: <p>The number of requests exceeds the limit. Resubmit your request later.</p>
        capo_bedrock_agent.errors.validation_exception.ValidationException: <p>Input validation failed. Check your request parameters and retry the request.</p>
        capo_bedrock_agent.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_bedrock_agent.types.stop_ingestion_job_request.StopIngestionJobRequest]",
    ) -> OperationResponse[
        "capo_bedrock_agent.types.stop_ingestion_job_response.StopIngestionJobResponse"
    ]:
        import capo_bedrock_agent._operations.amazon_bedrock_agent_build_time_lambda.stop_ingestion_job

        output, http_response = (
            capo_bedrock_agent._operations.amazon_bedrock_agent_build_time_lambda.stop_ingestion_job.stop_ingestion_job(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("StopIngestionJob")
    )
    input_: capo_bedrock_agent.types.stop_ingestion_job_request.StopIngestionJobRequest = {
        "knowledge_base_id": knowledge_base_id,
        "data_source_id": data_source_id,
        "ingestion_job_id": ingestion_job_id,
    }

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