Source code for airflow.providers.amazon.aws.operators.quicksight
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from __future__ import annotations
from typing import TYPE_CHECKING, Sequence
from airflow.providers.amazon.aws.hooks.quicksight import QuickSightHook
from airflow.providers.amazon.aws.operators.base_aws import AwsBaseOperator
from airflow.providers.amazon.aws.utils.mixins import aws_template_fields
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]class QuickSightCreateIngestionOperator(AwsBaseOperator[QuickSightHook]):
"""
Creates and starts a new SPICE ingestion for a dataset; also helps to Refresh existing SPICE datasets.
.. seealso::
For more information on how to use this operator, take a look at the guide:
:ref:`howto/operator:QuickSightCreateIngestionOperator`
: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. Values Can be INCREMENTAL_REFRESH or FULL_REFRESH.
Default FULL_REFRESH.
:param wait_for_completion: If wait is set to True, the time interval, in seconds,
that the operation waits to check the status of the Amazon QuickSight Ingestion.
:param check_interval: if wait is set to be true, this is the time interval
in seconds which the operator will check the status of the Amazon QuickSight Ingestion
:param aws_conn_id: The Airflow connection used for AWS credentials.
If this is ``None`` or empty then the default boto3 behaviour is used. If
running Airflow in a distributed manner and aws_conn_id is None or
empty, then default boto3 configuration would be used (and must be
maintained on each worker node).
:param region_name: AWS region_name. If not specified then the default boto3 behaviour is used.
:param verify: Whether or not to verify SSL certificates. See:
https://boto3.amazonaws.com/v1/documentation/api/latest/reference/core/session.html
:param botocore_config: Configuration dictionary (key-values) for botocore client. See:
https://botocore.amazonaws.com/v1/documentation/api/latest/reference/config.html
"""
[docs] aws_hook_class = QuickSightHook
[docs] template_fields: Sequence[str] = aws_template_fields(
"data_set_id",
"ingestion_id",
"ingestion_type",
"wait_for_completion",
"check_interval",
)
def __init__(
self,
data_set_id: str,
ingestion_id: str,
ingestion_type: str = "FULL_REFRESH",
wait_for_completion: bool = True,
check_interval: int = 30,
**kwargs,
):
super().__init__(**kwargs)
self.data_set_id = data_set_id
self.ingestion_id = ingestion_id
self.ingestion_type = ingestion_type
self.wait_for_completion = wait_for_completion
self.check_interval = check_interval
[docs] def execute(self, context: Context):
self.log.info("Running the Amazon QuickSight SPICE Ingestion on Dataset ID: %s", self.data_set_id)
return self.hook.create_ingestion(
data_set_id=self.data_set_id,
ingestion_id=self.ingestion_id,
ingestion_type=self.ingestion_type,
wait_for_completion=self.wait_for_completion,
check_interval=self.check_interval,
)