Source code for airflow.providers.amazon.aws.hooks.quicksight

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from __future__ import annotations

import time

from botocore.exceptions import ClientError

from airflow import AirflowException
from airflow.compat.functools import cached_property
from airflow.providers.amazon.aws.hooks.base_aws import AwsBaseHook
from airflow.providers.amazon.aws.hooks.sts import StsHook


[docs]class QuickSightHook(AwsBaseHook): """ Interact with Amazon QuickSight. Provide thin wrapper around :external+boto3:py:class:`boto3.client("quicksight") <QuickSight.Client>`. Additional arguments (such as ``aws_conn_id``) may be specified and are passed down to the underlying AwsBaseHook. .. seealso:: - :class:`airflow.providers.amazon.aws.hooks.base_aws.AwsBaseHook` """
[docs] NON_TERMINAL_STATES = {"INITIALIZED", "QUEUED", "RUNNING"}
[docs] FAILED_STATES = {"FAILED"}
def __init__(self, *args, **kwargs): super().__init__(client_type="quicksight", *args, **kwargs) @cached_property
[docs] def sts_hook(self): return StsHook(aws_conn_id=self.aws_conn_id)
[docs] def create_ingestion( self, data_set_id: str, ingestion_id: str, ingestion_type: str, wait_for_completion: bool = True, check_interval: int = 30, ) -> dict: """ Creates and starts a new SPICE ingestion for a dataset. Refreshes the SPICE datasets .. seealso:: - :external+boto3:py:meth:`QuickSight.Client.create_ingestion` :param data_set_id: ID of the dataset used in the ingestion. :param ingestion_id: ID for the ingestion. :param ingestion_type: Type of ingestion . "INCREMENTAL_REFRESH"|"FULL_REFRESH" :param wait_for_completion: if the program should keep running until job finishes :param check_interval: the time interval in seconds which the operator will check the status of QuickSight Ingestion :return: Returns descriptive information about the created data ingestion having Ingestion ARN, HTTP status, ingestion ID and ingestion status. """ self.log.info("Creating QuickSight Ingestion for data set id %s.", data_set_id) quicksight_client = self.get_conn() try: aws_account_id = self.sts_hook.get_account_number() create_ingestion_response = quicksight_client.create_ingestion( DataSetId=data_set_id, IngestionId=ingestion_id, IngestionType=ingestion_type, AwsAccountId=aws_account_id, ) if wait_for_completion: self.wait_for_state( aws_account_id=aws_account_id, data_set_id=data_set_id, ingestion_id=ingestion_id, target_state={"COMPLETED"}, check_interval=check_interval, ) return create_ingestion_response except Exception as general_error: self.log.error("Failed to run Amazon QuickSight create_ingestion API, error: %s", general_error) raise
[docs] def get_status(self, aws_account_id: str, data_set_id: str, ingestion_id: str) -> str: """ Get the current status of QuickSight Create Ingestion API. .. seealso:: - :external+boto3:py:meth:`QuickSight.Client.describe_ingestion` :param aws_account_id: An AWS Account ID :param data_set_id: QuickSight Data Set ID :param ingestion_id: QuickSight Ingestion ID :return: An QuickSight Ingestion Status """ try: describe_ingestion_response = self.get_conn().describe_ingestion( AwsAccountId=aws_account_id, DataSetId=data_set_id, IngestionId=ingestion_id ) return describe_ingestion_response["Ingestion"]["IngestionStatus"] except KeyError as e: raise AirflowException(f"Could not get status of the Amazon QuickSight Ingestion: {e}") except ClientError as e: raise AirflowException(f"AWS request failed: {e}")
[docs] def get_error_info(self, aws_account_id: str, data_set_id: str, ingestion_id: str) -> dict | None: """ Gets info about the error if any. :param aws_account_id: An AWS Account ID :param data_set_id: QuickSight Data Set ID :param ingestion_id: QuickSight Ingestion ID :return: Error info dict containing the error type (key 'Type') and message (key 'Message') if available. Else, returns None. """ describe_ingestion_response = self.get_conn().describe_ingestion( AwsAccountId=aws_account_id, DataSetId=data_set_id, IngestionId=ingestion_id ) # using .get() to get None if the key is not present, instead of an exception. return describe_ingestion_response["Ingestion"].get("ErrorInfo")
[docs] def wait_for_state( self, aws_account_id: str, data_set_id: str, ingestion_id: str, target_state: set, check_interval: int, ): """ Check status of a QuickSight Create Ingestion API :param aws_account_id: An AWS Account ID :param data_set_id: QuickSight Data Set ID :param ingestion_id: QuickSight Ingestion ID :param target_state: Describes the QuickSight Job's Target State :param check_interval: the time interval in seconds which the operator will check the status of QuickSight Ingestion :return: response of describe_ingestion call after Ingestion is is done """ sec = 0 status = self.get_status(aws_account_id, data_set_id, ingestion_id) while status in self.NON_TERMINAL_STATES and status != target_state: self.log.info("Current status is %s", status) if status in self.FAILED_STATES: info = self.get_error_info(aws_account_id, data_set_id, ingestion_id) raise AirflowException(f"The Amazon QuickSight Ingestion failed. Error info: {info}") if status == "CANCELLED": raise AirflowException("The Amazon QuickSight SPICE ingestion cancelled!") # wait and try again time.sleep(check_interval) sec += check_interval status = self.get_status(aws_account_id, data_set_id, ingestion_id) self.log.info("QuickSight Ingestion completed") return status

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