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"""This module contains Google Dataplex triggers."""
from __future__ import annotations
import asyncio
from typing import AsyncIterator, Sequence
from google.cloud.dataplex_v1.types import DataScanJob
from airflow.providers.google.cloud.hooks.dataplex import DataplexAsyncHook
from airflow.triggers.base import BaseTrigger, TriggerEvent
[docs]class DataplexDataQualityJobTrigger(BaseTrigger):
"""
DataplexDataQualityJobTrigger runs on the trigger worker and waits for the job to be `SUCCEEDED` state.
:param job_id: Optional. The ID of a Dataplex job.
:param data_scan_id: Required. DataScan identifier.
:param project_id: Google Cloud Project where the job is running.
:param region: The ID of the Google Cloud region that the job belongs to.
:param gcp_conn_id: Optional, the connection ID used to connect to Google Cloud Platform.
: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 polling_interval_seconds: polling period in seconds to check for the status.
"""
def __init__(
self,
job_id: str | None,
data_scan_id: str,
project_id: str | None,
region: str,
gcp_conn_id: str = "google_cloud_default",
polling_interval_seconds: int = 10,
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.job_id = job_id
self.data_scan_id = data_scan_id
self.project_id = project_id
self.region = region
self.gcp_conn_id = gcp_conn_id
self.polling_interval_seconds = polling_interval_seconds
self.impersonation_chain = impersonation_chain
[docs] def serialize(self):
return (
"airflow.providers.google.cloud.triggers.dataplex.DataplexDataQualityJobTrigger",
{
"job_id": self.job_id,
"data_scan_id": self.data_scan_id,
"project_id": self.project_id,
"region": self.region,
"gcp_conn_id": self.gcp_conn_id,
"impersonation_chain": self.impersonation_chain,
"polling_interval_seconds": self.polling_interval_seconds,
},
)
[docs] async def run(self) -> AsyncIterator[TriggerEvent]:
hook = DataplexAsyncHook(
gcp_conn_id=self.gcp_conn_id,
impersonation_chain=self.impersonation_chain,
)
while True:
job = await hook.get_data_scan_job(
project_id=self.project_id,
region=self.region,
job_id=self.job_id,
data_scan_id=self.data_scan_id,
)
state = job.state
if state in (DataScanJob.State.FAILED, DataScanJob.State.SUCCEEDED, DataScanJob.State.CANCELLED):
break
self.log.info(
"Current state is: %s, sleeping for %s seconds.",
DataScanJob.State(state).name,
self.polling_interval_seconds,
)
await asyncio.sleep(self.polling_interval_seconds)
yield TriggerEvent({"job_id": self.job_id, "job_state": state, "job": self._convert_to_dict(job)})
def _convert_to_dict(self, job: DataScanJob) -> dict:
"""Return a representation of a DataScanJob instance as a dict."""
return DataScanJob.to_dict(job)
[docs]class DataplexDataProfileJobTrigger(BaseTrigger):
"""
DataplexDataProfileJobTrigger runs on the trigger worker and waits for the job to be `SUCCEEDED` state.
:param job_id: Optional. The ID of a Dataplex job.
:param data_scan_id: Required. DataScan identifier.
:param project_id: Google Cloud Project where the job is running.
:param region: The ID of the Google Cloud region that the job belongs to.
:param gcp_conn_id: Optional, the connection ID used to connect to Google Cloud Platform.
: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 polling_interval_seconds: polling period in seconds to check for the status.
"""
def __init__(
self,
job_id: str | None,
data_scan_id: str,
project_id: str | None,
region: str,
gcp_conn_id: str = "google_cloud_default",
polling_interval_seconds: int = 10,
impersonation_chain: str | Sequence[str] | None = None,
**kwargs,
):
super().__init__(**kwargs)
self.job_id = job_id
self.data_scan_id = data_scan_id
self.project_id = project_id
self.region = region
self.gcp_conn_id = gcp_conn_id
self.polling_interval_seconds = polling_interval_seconds
self.impersonation_chain = impersonation_chain
[docs] def serialize(self):
return (
"airflow.providers.google.cloud.triggers.dataplex.DataplexDataProfileJobTrigger",
{
"job_id": self.job_id,
"data_scan_id": self.data_scan_id,
"project_id": self.project_id,
"region": self.region,
"gcp_conn_id": self.gcp_conn_id,
"impersonation_chain": self.impersonation_chain,
"polling_interval_seconds": self.polling_interval_seconds,
},
)
[docs] async def run(self) -> AsyncIterator[TriggerEvent]:
hook = DataplexAsyncHook(
gcp_conn_id=self.gcp_conn_id,
impersonation_chain=self.impersonation_chain,
)
while True:
job = await hook.get_data_scan_job(
project_id=self.project_id,
region=self.region,
job_id=self.job_id,
data_scan_id=self.data_scan_id,
)
state = job.state
if state in (DataScanJob.State.FAILED, DataScanJob.State.SUCCEEDED, DataScanJob.State.CANCELLED):
break
self.log.info(
"Current state is: %s, sleeping for %s seconds.",
DataScanJob.State(state).name,
self.polling_interval_seconds,
)
await asyncio.sleep(self.polling_interval_seconds)
yield TriggerEvent({"job_id": self.job_id, "job_state": state, "job": self._convert_to_dict(job)})
def _convert_to_dict(self, job: DataScanJob) -> dict:
"""Return a representation of a DataScanJob instance as a dict."""
return DataScanJob.to_dict(job)
