aws sagemaker add-association
Creates an association between the source and the destination. A source can be associated with multiple destinations, and a destination can be associated with multiple sources. An association is a lineage tracking entity. For more information, see Amazon SageMaker ML Lineage Tracking
Options
| Name | Description |
|---|---|
--source-arn <string> | The ARN of the source |
--destination-arn <string> | The Amazon Resource Name (ARN) of the destination |
--association-type <string> | The type of association. The following are suggested uses for each type. Amazon SageMaker places no restrictions on their use. ContributedTo - The source contributed to the destination or had a part in enabling the destination. For example, the training data contributed to the training job. AssociatedWith - The source is connected to the destination. For example, an approval workflow is associated with a model deployment. DerivedFrom - The destination is a modification of the source. For example, a digest output of a channel input for a processing job is derived from the original inputs. Produced - The source generated the destination. For example, a training job produced a model artifact |
--cli-input-json <string> | Performs service operation based on the JSON string provided. The JSON string follows the format provided by ``--generate-cli-skeleton``. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally |
--generate-cli-skeleton <string> | Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value ``input``, prints a sample input JSON that can be used as an argument for ``--cli-input-json``. If provided with the value ``output``, it validates the command inputs and returns a sample output JSON for that command |