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fix(ingestion/airflow-plugin): airflow remove old tasks #10485

Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
import asyncio
import copy
import functools
import logging
Expand All @@ -8,6 +9,7 @@

import airflow
import datahub.emitter.mce_builder as builder
from airflow.models.serialized_dag import SerializedDagModel
from datahub.api.entities.datajob import DataJob
from datahub.api.entities.dataprocess.dataprocess_instance import InstanceRunResult
from datahub.emitter.mcp import MetadataChangeProposalWrapper
Expand Down Expand Up @@ -68,6 +70,7 @@ def hookimpl(f: _F) -> _F: # type: ignore[misc] # noqa: F811
"1",
)
_RUN_IN_THREAD_TIMEOUT = 30
_DATAHUB_CLEANUP_DAG = "Datahub_Cleanup"


def get_airflow_plugin_listener() -> Optional["DataHubListener"]:
Expand Down Expand Up @@ -541,6 +544,48 @@ def on_dag_start(self, dag_run: "DagRun") -> None:

self.emitter.emit(event)

if dag.dag_id == _DATAHUB_CLEANUP_DAG:
assert self.graph

logger.debug("Initiating the cleanup of obsselete data from datahub")

ingested_dataflow_urns = list(
self.graph.get_urns_by_filter(
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I think you should filter for cluster as well; otherwise if user has multiple Airflow instance you will delete dags which you shouldn't.

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I am filtering the entire URN which is already having the cluster i.e. urn:li:dataFlow:(airflow,simple_dag,prod)
So, still we need to match/filter cluster explicitly? or my understanding is wrong.

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If you check here we use cluster or env to generate the DataFlow Urns, so it is part of the urn. ->

self.urn = DataFlowUrn.create_from_ids(

This means if the env or cluster is set and has multiple Airflow environments like DEV and PROD, then your query will return the urns for both PROD and DEV, which we don't want in this case as these are different Airflow environment.

You should add cluster/env as a filter parameter.

platform="airflow", entity_types=["dataFlow"]
)
)
ingested_datajob_urns = list(
self.graph.get_urns_by_filter(
platform="airflow", entity_types=["dataJob"]
)
)

all_airflow_dags = SerializedDagModel.read_all_dags().values()

airflow_flow_urns: List = []
airflow_job_urns: List = []

for dag in all_airflow_dags:
flow_urn = builder.make_data_flow_urn(
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cluster should be passed in if exists

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same as other comment

orchestrator="airflow", flow_id=dag.dag_id
)
airflow_flow_urns.append(flow_urn)

for task in dag.tasks:
airflow_job_urns.append(
builder.make_data_job_urn_with_flow(str(flow_urn), task.task_id)
)

obsolete_pipelines = set(ingested_dataflow_urns) - set(airflow_flow_urns)
obsolete_tasks = set(ingested_datajob_urns) - set(airflow_job_urns)

obsolete_urns = obsolete_pipelines.union(obsolete_tasks)

asyncio.run(self._soft_delete_obsolete_urns(obsolete_urns=obsolete_urns))

logger.debug(f"total pipelines removed = {len(obsolete_pipelines)}")
logger.debug(f"total tasks removed = {len(obsolete_tasks)}")

if HAS_AIRFLOW_DAG_LISTENER_API:

@hookimpl
Expand Down Expand Up @@ -577,3 +622,13 @@ def on_dataset_changed(self, dataset: "Dataset") -> None:
logger.debug(
f"DataHub listener got notification about dataset change for {dataset}"
)

async def _soft_delete_obsolete_urns(self, obsolete_urns):
delete_tasks = [self._delete_obsolete_data(urn) for urn in obsolete_urns]
await asyncio.gather(*delete_tasks)

async def _delete_obsolete_data(self, obsolete_urn):
assert self.graph

if self.graph.exists(str(obsolete_urn)):
self.graph.soft_delete_entity(str(obsolete_urn))
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