Source code for airflow.providers.google.cloud.triggers.bigquery_dts

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from __future__ import annotations

import asyncio
from typing import Any, AsyncIterator, Sequence

from google.cloud.bigquery_datatransfer_v1 import TransferRun, TransferState

from airflow.providers.google.cloud.hooks.bigquery_dts import AsyncBiqQueryDataTransferServiceHook
from airflow.triggers.base import BaseTrigger, TriggerEvent


[docs]class BigQueryDataTransferRunTrigger(BaseTrigger): """ Triggers class to watch the Transfer Run state to define when the job is done. :param project_id: The BigQuery project id where the transfer configuration should be :param config_id: ID of the config of the Transfer Run which should be watched. :param run_id: ID of the Transfer Run which should be watched. :param poll_interval: Optional. Interval which defines how often triggers check status of the job. :param gcp_conn_id: The connection ID used to connect to Google Cloud. :param location: BigQuery Transfer Service location for regional transfers. :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). """ def __init__( self, project_id: str | None, config_id: str, run_id: str, poll_interval: int = 10, gcp_conn_id: str = "google_cloud_default", location: str | None = None, impersonation_chain: str | Sequence[str] | None = None, ): super().__init__() self.project_id = project_id self.config_id = config_id self.run_id = run_id self.poll_interval = poll_interval self.gcp_conn_id = gcp_conn_id self.location = location self.impersonation_chain = impersonation_chain
[docs] def serialize(self) -> tuple[str, dict[str, Any]]: """Serializes class arguments and classpath.""" return ( "airflow.providers.google.cloud.triggers.bigquery_dts.BigQueryDataTransferRunTrigger", { "project_id": self.project_id, "config_id": self.config_id, "run_id": self.run_id, "poll_interval": self.poll_interval, "gcp_conn_id": self.gcp_conn_id, "location": self.location, "impersonation_chain": self.impersonation_chain, }, )
[docs] async def run(self) -> AsyncIterator[TriggerEvent]: """If the Transfer Run is in a terminal state, then yield TriggerEvent object.""" hook = self._get_async_hook() try: while True: transfer_run: TransferRun = await hook.get_transfer_run( project_id=self.project_id, config_id=self.config_id, run_id=self.run_id, location=self.location, ) state = transfer_run.state self.log.info("Current state is %s", state) if state == TransferState.SUCCEEDED: self.log.info("Job has completed its work.") yield TriggerEvent( { "status": "success", "run_id": self.run_id, "message": "Job completed", "config_id": self.config_id, } ) return elif state == TransferState.FAILED: self.log.info("Job has failed") yield TriggerEvent( { "status": "failed", "run_id": self.run_id, "message": "Job has failed", } ) return if state == TransferState.CANCELLED: self.log.info("Job has been cancelled.") yield TriggerEvent( { "status": "cancelled", "run_id": self.run_id, "message": "Job was cancelled", } ) return else: self.log.info("Job is still working...") self.log.info("Waiting for %s seconds", self.poll_interval) await asyncio.sleep(self.poll_interval) except Exception as e: yield TriggerEvent( { "status": "failed", "message": f"Trigger failed with exception: {e}", } )
def _get_async_hook(self) -> AsyncBiqQueryDataTransferServiceHook: return AsyncBiqQueryDataTransferServiceHook( gcp_conn_id=self.gcp_conn_id, location=self.location, impersonation_chain=self.impersonation_chain, )

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