list_records ¶

def list_records(
    self,
    feature_group_name: "capo_sagemaker_featurestore_runtime.types.feature_group_name_or_arn.FeatureGroupNameOrArn",
    *,
    config_overrides: Optional[SageMakerFeatureStoreRuntimeClientConfig] = None,
    max_results: Optional[
        "capo_sagemaker_featurestore_runtime.types.list_records_max_results.ListRecordsMaxResults"
    ] = None,
    next_token: Optional[
        "capo_sagemaker_featurestore_runtime.types.list_records_next_token.ListRecordsNextToken"
    ] = None,
    include_soft_deleted_records: Optional[
        "capo_sagemaker_featurestore_runtime.types.boolean.Boolean"
    ] = None,
) -> "capo_sagemaker_featurestore_runtime.types.list_records_response.ListRecordsResponse":
    """<p>Lists the <code>RecordIdentifier</code> values of all records stored in a <code>FeatureGroup</code>'s <code>OnlineStore</code>. This enables you to discover which records exist without retrieving the full record data.</p>

    Args:
        feature_group_name: <p>The name or Amazon Resource Name (ARN) of the feature group to list records from.</p>
        max_results: <p>The maximum number of record identifiers to return in a single page of results. For the <code>InMemory</code> tier, this value is a hint and not a strict requirement. The response may contain more or fewer results than the specified <code>MaxResults</code>.</p>
        next_token: <p>A token to resume pagination of <code>ListRecords</code> results.</p>
        include_soft_deleted_records: <p>If set to <code>true</code>, the result includes records that have been soft deleted.</p>

    Raises:
        capo_sagemaker_featurestore_runtime.errors.access_forbidden.AccessForbidden: <p>You do not have permission to perform an action.</p>
        capo_sagemaker_featurestore_runtime.errors.internal_failure.InternalFailure: <p>An internal failure occurred. Try your request again. If the problem persists, contact Amazon Web Services customer support.</p>
        capo_sagemaker_featurestore_runtime.errors.resource_not_found.ResourceNotFound: <p>A resource that is required to perform an action was not found.</p>
        capo_sagemaker_featurestore_runtime.errors.service_unavailable.ServiceUnavailable: <p>The service is currently unavailable.</p>
        capo_sagemaker_featurestore_runtime.errors.validation_error.ValidationError: <p>There was an error validating your request.</p>
        capo_sagemaker_featurestore_runtime.errors.UnknownServiceError: The service returned an error code this client does not model.

    Examples:
        List record identifiers from a feature group

        >>> client.list_records(feature_group_name='my-feature-group', max_results=10)
    """

    def _handler(
        req: "OperationRequest[capo_sagemaker_featurestore_runtime.types.list_records_request.ListRecordsRequest]",
    ) -> OperationResponse[
        "capo_sagemaker_featurestore_runtime.types.list_records_response.ListRecordsResponse"
    ]:
        import capo_sagemaker_featurestore_runtime._operations.amazon_sage_maker_feature_store_runtime.list_records

        output, http_response = (
            capo_sagemaker_featurestore_runtime._operations.amazon_sage_maker_feature_store_runtime.list_records.list_records(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ListRecords")
    )
    input_: capo_sagemaker_featurestore_runtime.types.list_records_request.ListRecordsRequest = {
        "feature_group_name": feature_group_name
    }
    if max_results is not None:
        input_["max_results"] = max_results
    if next_token is not None:
        input_["next_token"] = next_token
    if include_soft_deleted_records is not None:
        input_["include_soft_deleted_records"] = include_soft_deleted_records

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