update_feature_group ¶

def update_feature_group(
    self,
    *,
    config_overrides: Optional[SageMakerClientConfig] = None,
    feature_group_name: Optional[
        "capo_sagemaker.types.feature_group_name_or_arn.FeatureGroupNameOrArn"
    ] = None,
    feature_additions: Optional[
        "capo_sagemaker.types.feature_additions.FeatureAdditions"
    ] = None,
    online_store_config: Optional[
        "capo_sagemaker.types.online_store_config_update.OnlineStoreConfigUpdate"
    ] = None,
    throughput_config: Optional[
        "capo_sagemaker.types.throughput_config_update.ThroughputConfigUpdate"
    ] = None,
) -> (
    "capo_sagemaker.types.update_feature_group_response.UpdateFeatureGroupResponse"
):
    """<p>Updates the feature group by either adding features or updating the online store configuration. Use one of the following request parameters at a time while using the <code>UpdateFeatureGroup</code> API.</p> <p>You can add features for your feature group using the <code>FeatureAdditions</code> request parameter. Features cannot be removed from a feature group.</p> <p>You can update the online store configuration by using the <code>OnlineStoreConfig</code> request parameter. If a <code>TtlDuration</code> is specified, the default <code>TtlDuration</code> applies for all records added to the feature group <i>after the feature group is updated</i>. If a record level <code>TtlDuration</code> exists from using the <code>PutRecord</code> API, the record level <code>TtlDuration</code> applies to that record instead of the default <code>TtlDuration</code>. To remove the default <code>TtlDuration</code> from an existing feature group, use the <code>UpdateFeatureGroup</code> API and set the <code>TtlDuration</code> <code>Unit</code> and <code>Value</code> to <code>null</code>.</p>

    Args:
        feature_group_name: <p>The name or Amazon Resource Name (ARN) of the feature group that you're updating.</p>
        feature_additions: <p>Updates the feature group. Updating a feature group is an asynchronous operation. When you get an HTTP 200 response, you've made a valid request. It takes some time after you've made a valid request for Feature Store to update the feature group.</p>
        online_store_config: <p>Updates the feature group online store configuration.</p>

    Raises:
        capo_sagemaker.errors.resource_limit_exceeded.ResourceLimitExceeded: <p> You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created. </p>
        capo_sagemaker.errors.resource_not_found.ResourceNotFound: <p>Resource being access is not found.</p>
        capo_sagemaker.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_sagemaker.types.update_feature_group_request.UpdateFeatureGroupRequest]",
    ) -> OperationResponse[
        "capo_sagemaker.types.update_feature_group_response.UpdateFeatureGroupResponse"
    ]:
        import capo_sagemaker._operations.sage_maker.update_feature_group

        output, http_response = (
            capo_sagemaker._operations.sage_maker.update_feature_group.update_feature_group(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("UpdateFeatureGroup")
    )
    input_: capo_sagemaker.types.update_feature_group_request.UpdateFeatureGroupRequest = {}
    if feature_group_name is not None:
        input_["feature_group_name"] = feature_group_name
    if feature_additions is not None:
        input_["feature_additions"] = feature_additions
    if online_store_config is not None:
        input_["online_store_config"] = online_store_config
    if throughput_config is not None:
        input_["throughput_config"] = throughput_config

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