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"""This module contains Google Dataplex sensors."""
from __future__ import annotations
import time
from typing import TYPE_CHECKING, Sequence
if TYPE_CHECKING:
from google.api_core.retry import Retry
from airflow.utils.context import Context
from google.api_core.exceptions import GoogleAPICallError
from google.api_core.gapic_v1.method import DEFAULT, _MethodDefault
from google.cloud.dataplex_v1.types import DataScanJob
from airflow.exceptions import AirflowException
from airflow.providers.google.cloud.hooks.dataplex import (
AirflowDataQualityScanException,
AirflowDataQualityScanResultTimeoutException,
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 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: Retry | _MethodDefault = DEFAULT,
metadata: Sequence[tuple[str, str]] = (),
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = 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.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,
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
[docs]class DataplexDataQualityJobStatusSensor(BaseSensorOperator):
"""
Check the status of the Dataplex DataQuality job.
: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 data_scan_id: Required. Data Quality scan identifier.
:param job_id: Required. Job ID.
: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 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).
:param result_timeout: Value in seconds for which operator will wait for the Data Quality scan result.
Throws exception if there is no result found after specified amount of seconds.
:param fail_on_dq_failure: If set to true and not all Data Quality scan rules have been passed,
an exception is thrown. If set to false and not all Data Quality scan rules have been passed,
execution will finish with success.
:return: Boolean indicating if the job run has reached the ``DataScanJob.State.SUCCEEDED``.
"""
[docs] template_fields = ["job_id"]
def __init__(
self,
project_id: str,
region: str,
data_scan_id: str,
job_id: str,
api_version: str = "v1",
retry: Retry | _MethodDefault = DEFAULT,
metadata: Sequence[tuple[str, str]] = (),
gcp_conn_id: str = "google_cloud_default",
impersonation_chain: str | Sequence[str] | None = None,
fail_on_dq_failure: bool = False,
result_timeout: float = 60.0 * 10,
start_sensor_time: float | None = None,
*args,
**kwargs,
) -> None:
super().__init__(*args, **kwargs)
self.project_id = project_id
self.region = region
self.data_scan_id = data_scan_id
self.job_id = job_id
self.api_version = api_version
self.retry = retry
self.metadata = metadata
self.gcp_conn_id = gcp_conn_id
self.impersonation_chain = impersonation_chain
self.fail_on_dq_failure = fail_on_dq_failure
self.result_timeout = result_timeout
self.start_sensor_time = start_sensor_time
def _duration(self):
if not self.start_sensor_time:
self.start_sensor_time = time.monotonic()
return time.monotonic() - self.start_sensor_time
[docs] def poke(self, context: Context) -> bool:
self.log.info("Waiting for job %s to be %s", self.job_id, DataScanJob.State.SUCCEEDED)
if self.result_timeout:
duration = self._duration()
if duration > self.result_timeout:
raise AirflowDataQualityScanResultTimeoutException(
f"Timeout: Data Quality scan {self.job_id} is not ready after {self.result_timeout}s"
)
hook = DataplexHook(
gcp_conn_id=self.gcp_conn_id,
api_version=self.api_version,
impersonation_chain=self.impersonation_chain,
)
try:
job = hook.get_data_scan_job(
project_id=self.project_id,
region=self.region,
data_scan_id=self.data_scan_id,
job_id=self.job_id,
timeout=self.timeout,
retry=self.retry,
metadata=self.metadata,
)
except GoogleAPICallError as e:
raise AirflowException(
f"Error occurred when trying to retrieve Data Quality scan job: {self.data_scan_id}", e
)
job_status = job.state
self.log.info(
"Current status of the Dataplex Data Quality scan job %s => %s", self.job_id, job_status
)
if job_status == DataScanJob.State.FAILED:
raise AirflowException(f"Data Quality scan job failed: {self.job_id}")
if job_status == DataScanJob.State.CANCELLED:
raise AirflowException(f"Data Quality scan job cancelled: {self.job_id}")
if self.fail_on_dq_failure:
if job_status == DataScanJob.State.SUCCEEDED and not job.data_quality_result.passed:
raise AirflowDataQualityScanException(
f"Data Quality job {self.job_id} execution failed due to failure of its scanning "
f"rules: {self.data_scan_id}"
)
return job_status == DataScanJob.State.SUCCEEDED
