update_kx_cluster_databases ¶

def update_kx_cluster_databases(
    self,
    environment_id: "capo_finspace.types.kx_environment_id.KxEnvironmentId",
    cluster_name: "capo_finspace.types.kx_cluster_name.KxClusterName",
    databases: "capo_finspace.types.kx_database_configurations.KxDatabaseConfigurations",
    *,
    config_overrides: Optional[finspaceClientConfig] = None,
    client_token: Optional[
        "capo_finspace.types.client_token_string.ClientTokenString"
    ] = None,
    deployment_configuration: Optional[
        "capo_finspace.types.kx_deployment_configuration.KxDeploymentConfiguration"
    ] = None,
) -> "capo_finspace.types.update_kx_cluster_databases_response.UpdateKxClusterDatabasesResponse":
    """<p>Updates the databases mounted on a kdb cluster, which includes the <code>changesetId</code> and all the dbPaths to be cached. This API does not allow you to change a database name or add a database if you created a cluster without one. </p> <p>Using this API you can point a cluster to a different changeset and modify a list of partitions being cached.</p>

    Args:
        environment_id: <p>The unique identifier of a kdb environment.</p>
        cluster_name: <p>A unique name for the cluster that you want to modify.</p>
        client_token: <p>A token that ensures idempotency. This token expires in 10 minutes.</p>
        databases: <p> The structure of databases mounted on the cluster.</p>
        deployment_configuration: <p> The configuration that allows you to choose how you want to update the databases on a cluster. </p>

    Raises:
        capo_finspace.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action.</p>
        capo_finspace.errors.conflict_exception.ConflictException: <p>There was a conflict with this action, and it could not be completed.</p>
        capo_finspace.errors.internal_server_exception.InternalServerException: <p>The request processing has failed because of an unknown error, exception or failure.</p>
        capo_finspace.errors.limit_exceeded_exception.LimitExceededException: <p>A service limit or quota is exceeded.</p>
        capo_finspace.errors.resource_not_found_exception.ResourceNotFoundException: <p>One or more resources can't be found.</p>
        capo_finspace.errors.throttling_exception.ThrottlingException: <p>The request was denied due to request throttling.</p>
        capo_finspace.errors.validation_exception.ValidationException: <p>The input fails to satisfy the constraints specified by an AWS service.</p>
        capo_finspace.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_finspace.types.update_kx_cluster_databases_request.UpdateKxClusterDatabasesRequest]",
    ) -> OperationResponse[
        "capo_finspace.types.update_kx_cluster_databases_response.UpdateKxClusterDatabasesResponse"
    ]:
        import capo_finspace._operations.aws_habanero_management_service.update_kx_cluster_databases

        output, http_response = (
            capo_finspace._operations.aws_habanero_management_service.update_kx_cluster_databases.update_kx_cluster_databases(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("UpdateKxClusterDatabases")
    )
    input_: capo_finspace.types.update_kx_cluster_databases_request.UpdateKxClusterDatabasesRequest = {
        "environment_id": environment_id,
        "cluster_name": cluster_name,
        "databases": databases,
    }
    if client_token is None:
        client_token = str(uuid.uuid4())
    input_["client_token"] = client_token
    if deployment_configuration is not None:
        input_["deployment_configuration"] = deployment_configuration

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