Source code for

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.

from __future__ import annotations

import asyncio
from typing import Any, Sequence

from import JobState

from import AsyncDataflowHook
from airflow.triggers.base import BaseTrigger, TriggerEvent

[docs]DEFAULT_DATAFLOW_LOCATION = "us-central1"
[docs]class TemplateJobStartTrigger(BaseTrigger): """Dataflow trigger to check if templated job has been finished. :param project_id: Required. the Google Cloud project ID in which the job was started. :param job_id: Required. ID of the job. :param location: Optional. the location where job is executed. If set to None then the value of DEFAULT_DATAFLOW_LOCATION will be used :param gcp_conn_id: The connection ID to use connecting to Google Cloud. :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 cancel_timeout: Optional. How long (in seconds) operator should wait for the pipeline to be successfully cancelled when task is being killed. """ def __init__( self, job_id: str, project_id: str | None, location: str = DEFAULT_DATAFLOW_LOCATION, gcp_conn_id: str = "google_cloud_default", poll_sleep: int = 10, impersonation_chain: str | Sequence[str] | None = None, cancel_timeout: int | None = 5 * 60, ): super().__init__() self.project_id = project_id self.job_id = job_id self.location = location self.gcp_conn_id = gcp_conn_id self.poll_sleep = poll_sleep self.impersonation_chain = impersonation_chain self.cancel_timeout = cancel_timeout
[docs] def serialize(self) -> tuple[str, dict[str, Any]]: """Serialize class arguments and classpath.""" return ( "", { "project_id": self.project_id, "job_id": self.job_id, "location": self.location, "gcp_conn_id": self.gcp_conn_id, "poll_sleep": self.poll_sleep, "impersonation_chain": self.impersonation_chain, "cancel_timeout": self.cancel_timeout, }, )
[docs] async def run(self): """ Fetch job status or yield certain Events. Main loop of the class in where it is fetching the job status and yields certain Event. If the job has status success then it yields TriggerEvent with success status, if job has status failed - with error status. In any other case Trigger will wait for specified amount of time stored in self.poll_sleep variable. """ hook = self._get_async_hook() try: while True: status = await hook.get_job_status( project_id=self.project_id, job_id=self.job_id, location=self.location, ) if status == JobState.JOB_STATE_DONE: yield TriggerEvent( { "job_id": self.job_id, "status": "success", "message": "Job completed", } ) return elif status == JobState.JOB_STATE_FAILED: yield TriggerEvent( { "status": "error", "message": f"Dataflow job with id {self.job_id} has failed its execution", } ) return elif status == JobState.JOB_STATE_STOPPED: yield TriggerEvent( { "status": "stopped", "message": f"Dataflow job with id {self.job_id} was stopped", } ) return else:"Job is still running...")"Current job status is: %s", status)"Sleeping for %s seconds.", self.poll_sleep) await asyncio.sleep(self.poll_sleep) except Exception as e: self.log.exception("Exception occurred while checking for job completion.") yield TriggerEvent({"status": "error", "message": str(e)})
def _get_async_hook(self) -> AsyncDataflowHook: return AsyncDataflowHook( gcp_conn_id=self.gcp_conn_id, poll_sleep=self.poll_sleep, impersonation_chain=self.impersonation_chain, cancel_timeout=self.cancel_timeout, )

Was this entry helpful?