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#
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"""This module contains Google Dataplex sensors."""
from typing import TYPE_CHECKING, Optional, Sequence, Tuple, Union
if TYPE_CHECKING:
from airflow.utils.context import Context
from google.api_core.gapic_v1.method import DEFAULT, _MethodDefault
from google.api_core.retry import Retry
from airflow.exceptions import AirflowException
from airflow.providers.google.cloud.hooks.dataplex import DataplexHook
from airflow.sensors.base import BaseSensorOperator
[docs]class TaskState:
"""Dataplex Task states"""
[docs]class DataplexTaskStateSensor(BaseSensorOperator):
"""
Check the status of the Dataplex task
:param project_id: Required. The ID of the Google Cloud project that the task belongs to.
:param region: Required. The ID of the Google Cloud region that the task belongs to.
:param lake_id: Required. The ID of the Google Cloud lake that the task belongs to.
:param dataplex_task_id: Required. Task identifier.
:param api_version: The version of the api that will be requested for example 'v3'.
:param retry: A retry object used to retry requests. If `None` is specified, requests
will not be retried.
:param metadata: Additional metadata that is provided to the method.
:param gcp_conn_id: The connection ID to use when fetching connection info.
:param delegate_to: The account to impersonate, if any. For this to work, the service accountmaking the
request must have domain-wide delegation enabled.
:param impersonation_chain: Optional service account to impersonate using short-term
credentials, or chained list of accounts required to get the access_token
of the last account in the list, which will be impersonated in the request.
If set as a string, the account must grant the originating account
the Service Account Token Creator IAM role.
If set as a sequence, the identities from the list must grant
Service Account Token Creator IAM role to the directly preceding identity, with first
account from the list granting this role to the originating account (templated).
"""
[docs] template_fields = ['dataplex_task_id']
def __init__(
self,
project_id: str,
region: str,
lake_id: str,
dataplex_task_id: str,
api_version: str = "v1",
retry: Union[Retry, _MethodDefault] = DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
gcp_conn_id: str = "google_cloud_default",
delegate_to: Optional[str] = None,
impersonation_chain: Optional[Union[str, Sequence[str]]] = None,
*args,
**kwargs,
) -> None:
super().__init__(*args, **kwargs)
self.project_id = project_id
self.region = region
self.lake_id = lake_id
self.dataplex_task_id = dataplex_task_id
self.api_version = api_version
self.retry = retry
self.metadata = metadata
self.gcp_conn_id = gcp_conn_id
self.delegate_to = delegate_to
self.impersonation_chain = impersonation_chain
[docs] def poke(self, context: "Context") -> bool:
self.log.info("Waiting for task %s to be %s", self.dataplex_task_id, TaskState.ACTIVE)
hook = DataplexHook(
gcp_conn_id=self.gcp_conn_id,
delegate_to=self.delegate_to,
api_version=self.api_version,
impersonation_chain=self.impersonation_chain,
)
task = hook.get_task(
project_id=self.project_id,
region=self.region,
lake_id=self.lake_id,
dataplex_task_id=self.dataplex_task_id,
retry=self.retry,
metadata=self.metadata,
)
task_status = task.state
if task_status == TaskState.DELETING:
raise AirflowException(f"Task is going to be deleted {self.dataplex_task_id}")
self.log.info("Current status of the Dataplex task %s => %s", self.dataplex_task_id, task_status)
return task_status == TaskState.ACTIVE
