start_data_ingestion_job `async` ¶

start_data_ingestion_job(
    dataset_name: DatasetIdentifier,
    ingestion_input_configuration: IngestionInputConfiguration,
    role_arn: IamRoleArn,
    client_token: IdempotenceToken,
    *,
    config_overrides: Optional[AsyncLookoutEquipmentClientConfig] = None,
) -> StartDataIngestionJobResponse

Starts a data ingestion job. Amazon Lookout for Equipment returns the job status.

Parameters:

dataset_name (DatasetIdentifier) –

The name of the dataset being used by the data ingestion job.
ingestion_input_configuration (IngestionInputConfiguration) –

Specifies information for the input data for the data ingestion job, including dataset S3 location.
role_arn (IamRoleArn) –

The Amazon Resource Name (ARN) of a role with permission to access the data source for the data ingestion job.
client_token (IdempotenceToken) –

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

Raises:

AccessDeniedException –

The request could not be completed because you do not have access to the resource.
ConflictException –

The request could not be completed due to a conflict with the current state of the target resource.
InternalServerException –

Processing of the request has failed because of an unknown error, exception or failure.
ResourceNotFoundException –

The resource requested could not be found. Verify the resource ID and retry your request.
ServiceQuotaExceededException –

Resource limitations have been exceeded.
ThrottlingException –

The request was denied due to request throttling.
ValidationException –

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.
UnknownServiceError –

The service returned an error code this client does not model.

Source code in docs_src/capo_lookoutequipment/_services/async_lookout_equipment.py

async def start_data_ingestion_job(
    self,
    dataset_name: "capo_lookoutequipment.types.dataset_identifier.DatasetIdentifier",
    ingestion_input_configuration: "capo_lookoutequipment.types.ingestion_input_configuration.IngestionInputConfiguration",
    role_arn: "capo_lookoutequipment.types.iam_role_arn.IamRoleArn",
    client_token: "capo_lookoutequipment.types.idempotence_token.IdempotenceToken",
    *,
    config_overrides: Optional[AsyncLookoutEquipmentClientConfig] = None,
) -> "capo_lookoutequipment.types.start_data_ingestion_job_response.StartDataIngestionJobResponse":
    """<p>Starts a data ingestion job. Amazon Lookout for Equipment returns the job status. </p>

    Args:
        dataset_name: <p>The name of the dataset being used by the data ingestion job. </p>
        ingestion_input_configuration: <p> Specifies information for the input data for the data ingestion job, including dataset S3 location. </p>
        role_arn: <p> The Amazon Resource Name (ARN) of a role with permission to access the data source for the data ingestion job. </p>
        client_token: <p> A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one. </p>

    Raises:
        capo_lookoutequipment.errors.access_denied_exception.AccessDeniedException: <p>The request could not be completed because you do not have access to the resource. </p>
        capo_lookoutequipment.errors.conflict_exception.ConflictException: <p> The request could not be completed due to a conflict with the current state of the target resource. </p>
        capo_lookoutequipment.errors.internal_server_exception.InternalServerException: <p> Processing of the request has failed because of an unknown error, exception or failure. </p>
        capo_lookoutequipment.errors.resource_not_found_exception.ResourceNotFoundException: <p> The resource requested could not be found. Verify the resource ID and retry your request. </p>
        capo_lookoutequipment.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p> Resource limitations have been exceeded. </p>
        capo_lookoutequipment.errors.throttling_exception.ThrottlingException: <p>The request was denied due to request throttling.</p>
        capo_lookoutequipment.errors.validation_exception.ValidationException: <p> The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized. </p>
        capo_lookoutequipment.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_lookoutequipment.types.start_data_ingestion_job_request.StartDataIngestionJobRequest]",
    ) -> AsyncOperationResponse[
        "capo_lookoutequipment.types.start_data_ingestion_job_response.StartDataIngestionJobResponse"
    ]:
        import capo_lookoutequipment._operations.aws_lookout_equipment_frontend_service.start_data_ingestion_job

        (
            output,
            http_response,
        ) = await capo_lookoutequipment._operations.aws_lookout_equipment_frontend_service.start_data_ingestion_job.async_start_data_ingestion_job(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("StartDataIngestionJob")
    )
    input_: capo_lookoutequipment.types.start_data_ingestion_job_request.StartDataIngestionJobRequest = {
        "dataset_name": dataset_name,
        "ingestion_input_configuration": ingestion_input_configuration,
        "role_arn": role_arn,
        "client_token": client_token,
    }

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output

start_data_ingestion_job async ¶

start_data_ingestion_job `async` ¶