create_intermediate_table ¶

def create_intermediate_table(
    self,
    membership_identifier: "capo_cleanrooms.types.membership_identifier.MembershipIdentifier",
    name: "capo_cleanrooms.types.display_name.DisplayName",
    population_analysis_configuration: "capo_cleanrooms.types.population_analysis_configuration.PopulationAnalysisConfiguration",
    *,
    config_overrides: Optional[CleanRoomsClientConfig] = None,
    description: Optional[
        "capo_cleanrooms.types.resource_description.ResourceDescription"
    ] = None,
    kms_key_arn: Optional["capo_cleanrooms.types.kms_key_arn.KMSKeyArn"] = None,
    retention_in_days: Optional[int] = None,
    tags: Optional["capo_cleanrooms.types.tag_map.TagMap"] = None,
) -> "capo_cleanrooms.types.create_intermediate_table_output.CreateIntermediateTableOutput":
    """<p>Creates an intermediate table in a membership. The intermediate table is owned by the member with the CAN_QUERY ability. To populate the table with results, use <code>PopulateIntermediateTable</code>.</p>

    Args:
        membership_identifier: <p>The unique identifier of the membership where the intermediate table is created.</p>
        name: <p>The display name for the intermediate table.</p>
        description: <p>A description of the intermediate table.</p>
        population_analysis_configuration: <p>The configuration that defines the analysis used to populate the intermediate table.</p>
        kms_key_arn: <p>The Amazon Resource Name (ARN) of the customer-managed KMS key used to encrypt the intermediate table data.</p>
        retention_in_days: <p>The number of days to retain populated data versions.</p>
        tags: <p>An optional label that you can assign to a resource when you create it. Each tag consists of a key and an optional value, both of which you define. When you use tagging, you can also use tag-based access control in IAM policies to control access to this resource.</p>

    Raises:
        capo_cleanrooms.errors.access_denied_exception.AccessDeniedException: <p>Caller does not have sufficient access to perform this action.</p>
        capo_cleanrooms.errors.conflict_exception.ConflictException: <p>Updating or deleting a resource can cause an inconsistent state.</p>
        capo_cleanrooms.errors.internal_server_exception.InternalServerException: <p>Unexpected error during processing of request.</p>
        capo_cleanrooms.errors.resource_not_found_exception.ResourceNotFoundException: <p>Request references a resource which does not exist.</p>
        capo_cleanrooms.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>Request denied because service quota has been exceeded.</p>
        capo_cleanrooms.errors.throttling_exception.ThrottlingException: <p>Request was denied due to request throttling.</p>
        capo_cleanrooms.errors.validation_exception.ValidationException: <p>The input fails to satisfy the specified constraints.</p>
        capo_cleanrooms.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_cleanrooms.types.create_intermediate_table_input.CreateIntermediateTableInput]",
    ) -> OperationResponse[
        "capo_cleanrooms.types.create_intermediate_table_output.CreateIntermediateTableOutput"
    ]:
        import capo_cleanrooms._operations.aws_bastion_control_plane_service_lambda.create_intermediate_table

        output, http_response = (
            capo_cleanrooms._operations.aws_bastion_control_plane_service_lambda.create_intermediate_table.create_intermediate_table(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    def _redact_input(
        input_: "capo_cleanrooms.types.create_intermediate_table_input.CreateIntermediateTableInput",
    ) -> dict[str, Any]:
        import capo_cleanrooms.types.create_intermediate_table_input

        return (
            capo_cleanrooms.types.create_intermediate_table_input.redact_sensitive(
                input_
            )
        )

    def _redact_output(
        output: "capo_cleanrooms.types.create_intermediate_table_output.CreateIntermediateTableOutput",
    ) -> dict[str, Any]:
        import capo_cleanrooms.types.create_intermediate_table_output

        return (
            capo_cleanrooms.types.create_intermediate_table_output.redact_sensitive(
                output
            )
        )

    interceptors_, options_ = self.operation_options(
        config_overrides,
        OperationLogging(
            "CreateIntermediateTable",
            redact_input=_redact_input,
            redact_output=_redact_output,
        ),
    )
    input_: capo_cleanrooms.types.create_intermediate_table_input.CreateIntermediateTableInput = {
        "membership_identifier": membership_identifier,
        "name": name,
        "population_analysis_configuration": population_analysis_configuration,
    }
    if description is not None:
        input_["description"] = description
    if kms_key_arn is not None:
        input_["kms_key_arn"] = kms_key_arn
    if retention_in_days is not None:
        input_["retention_in_days"] = retention_in_days
    if tags is not None:
        input_["tags"] = tags

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