create_scheduled_query async ¶

async def create_scheduled_query(
    self,
    name: "capo_timestream_query.types.scheduled_query_name.ScheduledQueryName",
    query_string: "capo_timestream_query.types.query_string.QueryString",
    schedule_configuration: "capo_timestream_query.types.schedule_configuration.ScheduleConfiguration",
    notification_configuration: "capo_timestream_query.types.notification_configuration.NotificationConfiguration",
    scheduled_query_execution_role_arn: "capo_timestream_query.types.amazon_resource_name.AmazonResourceName",
    error_report_configuration: "capo_timestream_query.types.error_report_configuration.ErrorReportConfiguration",
    *,
    config_overrides: Optional[AsyncTimestreamQueryClientConfig] = None,
    target_configuration: Optional[
        "capo_timestream_query.types.target_configuration.TargetConfiguration"
    ] = None,
    client_token: Optional[
        "capo_timestream_query.types.client_token.ClientToken"
    ] = None,
    tags: Optional["capo_timestream_query.types.tag_list.TagList"] = None,
    kms_key_id: Optional[
        "capo_timestream_query.types.string_value2048.StringValue2048"
    ] = None,
) -> "capo_timestream_query.types.create_scheduled_query_response.CreateScheduledQueryResponse":
    """<p> Create a scheduled query that will be run on your behalf at the configured schedule. Timestream assumes the execution role provided as part of the <code>ScheduledQueryExecutionRoleArn</code> parameter to run the query. You can use the <code>NotificationConfiguration</code> parameter to configure notification for your scheduled query operations.</p>

    Args:
        name: <p>Name of the scheduled query.</p>
        query_string: <p>The query string to run. Parameter names can be specified in the query string <code>@</code> character followed by an identifier. The named Parameter <code>@scheduled_runtime</code> is reserved and can be used in the query to get the time at which the query is scheduled to run.</p> <p>The timestamp calculated according to the ScheduleConfiguration parameter, will be the value of <code>@scheduled_runtime</code> paramater for each query run. For example, consider an instance of a scheduled query executing on 2021-12-01 00:00:00. For this instance, the <code>@scheduled_runtime</code> parameter is initialized to the timestamp 2021-12-01 00:00:00 when invoking the query.</p>
        schedule_configuration: <p>The schedule configuration for the query.</p>
        notification_configuration: <p>Notification configuration for the scheduled query. A notification is sent by Timestream when a query run finishes, when the state is updated or when you delete it. </p>
        target_configuration: <p>Configuration used for writing the result of a query.</p>
        client_token: <p>Using a ClientToken makes the call to CreateScheduledQuery idempotent, in other words, making the same request repeatedly will produce the same result. Making multiple identical CreateScheduledQuery requests has the same effect as making a single request. </p> <ul> <li> <p> If CreateScheduledQuery is called without a <code>ClientToken</code>, the Query SDK generates a <code>ClientToken</code> on your behalf.</p> </li> <li> <p> After 8 hours, any request with the same <code>ClientToken</code> is treated as a new request. </p> </li> </ul>
        scheduled_query_execution_role_arn: <p>The ARN for the IAM role that Timestream will assume when running the scheduled query. </p>
        tags: <p>A list of key-value pairs to label the scheduled query.</p>
        kms_key_id: <p>The Amazon KMS key used to encrypt the scheduled query resource, at-rest. If the Amazon KMS key is not specified, the scheduled query resource will be encrypted with a Timestream owned Amazon KMS key. To specify a KMS key, use the key ID, key ARN, alias name, or alias ARN. When using an alias name, prefix the name with <i>alias/</i> </p> <p>If ErrorReportConfiguration uses <code>SSE_KMS</code> as encryption type, the same KmsKeyId is used to encrypt the error report at rest.</p>
        error_report_configuration: <p>Configuration for error reporting. Error reports will be generated when a problem is encountered when writing the query results. </p>

    Raises:
        capo_timestream_query.errors.access_denied_exception.AccessDeniedException: <p>You do not have the necessary permissions to access the account settings.</p>
        capo_timestream_query.errors.conflict_exception.ConflictException: <p> Unable to poll results for a cancelled query. </p>
        capo_timestream_query.errors.internal_server_exception.InternalServerException: <p>An internal server error occurred while processing the request.</p>
        capo_timestream_query.errors.invalid_endpoint_exception.InvalidEndpointException: <p>The requested endpoint is invalid.</p>
        capo_timestream_query.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>You have exceeded the service quota.</p>
        capo_timestream_query.errors.throttling_exception.ThrottlingException: <p>The request was throttled due to excessive requests.</p>
        capo_timestream_query.errors.validation_exception.ValidationException: <p> Invalid or malformed request. </p>
        capo_timestream_query.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_timestream_query.types.create_scheduled_query_request.CreateScheduledQueryRequest]",
    ) -> AsyncOperationResponse[
        "capo_timestream_query.types.create_scheduled_query_response.CreateScheduledQueryResponse"
    ]:
        import capo_timestream_query._operations.timestream_20181101.create_scheduled_query

        (
            output,
            http_response,
        ) = await capo_timestream_query._operations.timestream_20181101.create_scheduled_query.async_create_scheduled_query(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    def _redact_input(
        input_: "capo_timestream_query.types.create_scheduled_query_request.CreateScheduledQueryRequest",
    ) -> dict[str, Any]:
        import capo_timestream_query.types.create_scheduled_query_request

        return capo_timestream_query.types.create_scheduled_query_request.redact_sensitive(
            input_
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging("CreateScheduledQuery", redact_input=_redact_input),
    )
    input_: capo_timestream_query.types.create_scheduled_query_request.CreateScheduledQueryRequest = {
        "name": name,
        "query_string": query_string,
        "schedule_configuration": schedule_configuration,
        "notification_configuration": notification_configuration,
        "scheduled_query_execution_role_arn": scheduled_query_execution_role_arn,
        "error_report_configuration": error_report_configuration,
    }
    if target_configuration is not None:
        input_["target_configuration"] = target_configuration
    if client_token is None:
        client_token = str(uuid.uuid4())
    input_["client_token"] = client_token
    if tags is not None:
        input_["tags"] = tags
    if kms_key_id is not None:
        input_["kms_key_id"] = kms_key_id

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