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from __future__ import annotations
import asyncio
from typing import Any, AsyncIterator, Sequence
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]]:
"""Serializes 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]
"""Gets 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,
)
