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.models import BaseOperator
from airflow.providers.amazon.aws.hooks.quicksight import QuickSightHook
if TYPE_CHECKING:
from airflow.utils.context import Context
[docs]DEFAULT_CONN_ID = "aws_default"
[docs]class QuickSightCreateIngestionOperator(BaseOperator):
"""
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. (templated)
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 the default boto3 configuration would be used (and must be
maintained on each worker node).
:param region: Which AWS region the connection should use. (templated)
If this is None or empty then the default boto3 behaviour is used.
"""
[docs] template_fields: Sequence[str] = (
"data_set_id",
"ingestion_id",
"ingestion_type",
"wait_for_completion",
"check_interval",
"aws_conn_id",
"region",
)
def __init__(
self,
data_set_id: str,
ingestion_id: str,
ingestion_type: str = "FULL_REFRESH",
wait_for_completion: bool = True,
check_interval: int = 30,
aws_conn_id: str = DEFAULT_CONN_ID,
region: str | None = None,
**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
self.aws_conn_id = aws_conn_id
self.region = region
super().__init__(**kwargs)
[docs] def execute(self, context: Context):
hook = QuickSightHook(
aws_conn_id=self.aws_conn_id,
region_name=self.region,
)
self.log.info("Running the Amazon QuickSight SPICE Ingestion on Dataset ID: %s", self.data_set_id)
return 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,
)