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

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from __future__ import annotations

import asyncio
from collections.abc import AsyncIterator, Sequence
from typing import Any

from airflow.providers.google.cloud.hooks.datafusion import DataFusionAsyncHook
from airflow.providers.google.cloud.utils.datafusion import DataFusionPipelineType
from airflow.triggers.base import BaseTrigger, TriggerEvent


[docs]class DataFusionStartPipelineTrigger(BaseTrigger): """ Trigger to perform checking the pipeline status until it reaches terminate state. :param pipeline_name: Your pipeline name. :param instance_url: Endpoint on which the REST APIs is accessible for the instance. :param pipeline_id: Unique pipeline ID associated with specific pipeline :param pipeline_type: Your pipeline type. :param namespace: if your pipeline belongs to a Basic edition instance, the namespace ID is always default. If your pipeline belongs to an Enterprise edition instance, you can create a namespace. :param gcp_conn_id: Reference to google cloud connection id :param poll_interval: polling period in seconds to check for the status :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, instance_url: str, namespace: str, pipeline_name: str, pipeline_id: str, pipeline_type: str, poll_interval: float = 3.0, gcp_conn_id: str = "google_cloud_default", impersonation_chain: str | Sequence[str] | None = None, success_states: list[str] | None = None, ): super().__init__() self.instance_url = instance_url self.namespace = namespace self.pipeline_name = pipeline_name self.pipeline_id = pipeline_id self.pipeline_type = pipeline_type self.poll_interval = poll_interval self.gcp_conn_id = gcp_conn_id self.impersonation_chain = impersonation_chain self.success_states = success_states
[docs] def serialize(self) -> tuple[str, dict[str, Any]]: """Serialize DataFusionStartPipelineTrigger arguments and classpath.""" return ( "airflow.providers.google.cloud.triggers.datafusion.DataFusionStartPipelineTrigger", { "gcp_conn_id": self.gcp_conn_id, "instance_url": self.instance_url, "namespace": self.namespace, "pipeline_name": self.pipeline_name, "pipeline_id": self.pipeline_id, "pipeline_type": self.pipeline_type, "success_states": self.success_states, }, )
[docs] async def run(self) -> AsyncIterator[TriggerEvent]: # type: ignore[override] """Get current pipeline status and yields a TriggerEvent.""" hook = self._get_async_hook() try: while True: # Poll for job execution status response_from_hook = await hook.get_pipeline_status( success_states=self.success_states, instance_url=self.instance_url, namespace=self.namespace, pipeline_name=self.pipeline_name, pipeline_id=self.pipeline_id, pipeline_type=DataFusionPipelineType.from_str(self.pipeline_type), ) if response_from_hook == "success": yield TriggerEvent( { "pipeline_id": self.pipeline_id, "status": "success", "message": "Pipeline is running", } ) return elif response_from_hook == "pending": self.log.info("Pipeline is not still in running state...") self.log.info("Sleeping for %s seconds.", self.poll_interval) await asyncio.sleep(self.poll_interval) else: yield TriggerEvent({"status": "error", "message": response_from_hook}) return except Exception as e: self.log.exception("Exception occurred while checking for pipeline state") yield TriggerEvent({"status": "error", "message": str(e)})
def _get_async_hook(self) -> DataFusionAsyncHook: return DataFusionAsyncHook( instance_url=self.instance_url, namespace=self.namespace, pipeline_name=self.pipeline_name, pipeline_id=self.pipeline_id, gcp_conn_id=self.gcp_conn_id, impersonation_chain=self.impersonation_chain, )

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