SageMaker / Client / stop_pipeline_execution
stop_pipeline_execution#
- SageMaker.Client.stop_pipeline_execution(**kwargs)#
Stops a pipeline execution.
Callback Step
A pipeline execution won’t stop while a callback step is running. When you call
StopPipelineExecution
on a pipeline execution with a running callback step, SageMaker Pipelines sends an additional Amazon SQS message to the specified SQS queue. The body of the SQS message contains a “Status” field which is set to “Stopping”.You should add logic to your Amazon SQS message consumer to take any needed action (for example, resource cleanup) upon receipt of the message followed by a call to
SendPipelineExecutionStepSuccess
orSendPipelineExecutionStepFailure
.Only when SageMaker Pipelines receives one of these calls will it stop the pipeline execution.
Lambda Step
A pipeline execution can’t be stopped while a lambda step is running because the Lambda function invoked by the lambda step can’t be stopped. If you attempt to stop the execution while the Lambda function is running, the pipeline waits for the Lambda function to finish or until the timeout is hit, whichever occurs first, and then stops. If the Lambda function finishes, the pipeline execution status is
Stopped
. If the timeout is hit the pipeline execution status isFailed
.See also: AWS API Documentation
Request Syntax
response = client.stop_pipeline_execution( PipelineExecutionArn='string', ClientRequestToken='string' )
- Parameters:
PipelineExecutionArn (string) –
[REQUIRED]
The Amazon Resource Name (ARN) of the pipeline execution.
ClientRequestToken (string) –
[REQUIRED]
A unique, case-sensitive identifier that you provide to ensure the idempotency of the operation. An idempotent operation completes no more than once.
This field is autopopulated if not provided.
- Return type:
dict
- Returns:
Response Syntax
{ 'PipelineExecutionArn': 'string' }
Response Structure
(dict) –
PipelineExecutionArn (string) –
The Amazon Resource Name (ARN) of the pipeline execution.
Exceptions