get_dashboard_for_job_run ¶

def get_dashboard_for_job_run(
    self,
    application_id: "capo_emr_serverless.types.application_id.ApplicationId",
    job_run_id: "capo_emr_serverless.types.job_run_id.JobRunId",
    *,
    config_overrides: Optional[EMRServerlessClientConfig] = None,
    attempt: Optional[
        "capo_emr_serverless.types.attempt_number.AttemptNumber"
    ] = None,
    access_system_profile_logs: Optional[bool] = None,
) -> "capo_emr_serverless.types.get_dashboard_for_job_run_response.GetDashboardForJobRunResponse":
    """<p>Creates and returns a URL that you can use to access the application UIs for a job run.</p> <p>For jobs in a running state, the application UI is a live user interface such as the Spark or Tez web UI. For completed jobs, the application UI is a persistent application user interface such as the Spark History Server or persistent Tez UI.</p> <note> <p>The URL is valid for one hour after you generate it. To access the application UI after that hour elapses, you must invoke the API again to generate a new URL.</p> </note>

    Args:
        application_id: <p>The ID of the application.</p>
        job_run_id: <p>The ID of the job run.</p>
        attempt: <p>An optimal parameter that indicates the amount of attempts for the job. If not specified, this value defaults to the attempt of the latest job.</p>
        access_system_profile_logs: <p>Allows access to system profile logs for Lake Formation-enabled jobs. Default is false.</p>

    Raises:
        capo_emr_serverless.errors.internal_server_exception.InternalServerException: <p>Request processing failed because of an error or failure with the service.</p>
        capo_emr_serverless.errors.resource_not_found_exception.ResourceNotFoundException: <p>The specified resource was not found.</p>
        capo_emr_serverless.errors.validation_exception.ValidationException: <p>The input fails to satisfy the constraints specified by an Amazon Web Services service.</p>
        capo_emr_serverless.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_emr_serverless.types.get_dashboard_for_job_run_request.GetDashboardForJobRunRequest]",
    ) -> OperationResponse[
        "capo_emr_serverless.types.get_dashboard_for_job_run_response.GetDashboardForJobRunResponse"
    ]:
        import capo_emr_serverless._operations.aws_toledo_web_service.get_dashboard_for_job_run

        output, http_response = (
            capo_emr_serverless._operations.aws_toledo_web_service.get_dashboard_for_job_run.get_dashboard_for_job_run(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("GetDashboardForJobRun")
    )
    input_: capo_emr_serverless.types.get_dashboard_for_job_run_request.GetDashboardForJobRunRequest = {
        "application_id": application_id,
        "job_run_id": job_run_id,
    }
    if attempt is not None:
        input_["attempt"] = attempt
    if access_system_profile_logs is not None:
        input_["access_system_profile_logs"] = access_system_profile_logs

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