kacpermuda commented on code in PR #39520:
URL: https://github.com/apache/airflow/pull/39520#discussion_r1624774970
##########
airflow/providers/openlineage/utils/utils.py:
##########
@@ -262,20 +271,151 @@ def get_airflow_run_facet(
task_instance: TaskInstance,
task: BaseOperator,
task_uuid: str,
-):
+) -> dict[str, BaseFacet]:
return {
- "airflow": attrs.asdict(
- AirflowRunFacet(
- dag=DagInfo(dag),
- dagRun=DagRunInfo(dag_run),
- taskInstance=TaskInstanceInfo(task_instance),
- task=TaskInfo(task),
- taskUuid=task_uuid,
- )
+ "airflow": AirflowRunFacet(
+ dag=DagInfo(dag),
+ dagRun=DagRunInfo(dag_run),
+ taskInstance=TaskInstanceInfo(task_instance),
+ task=TaskInfo(task),
+ taskUuid=task_uuid,
+ )
+ }
+
+
+def get_airflow_job_facet(dag_run: DagRun) -> dict[str, BaseFacet]:
+ if not dag_run.dag:
+ return {}
+ return {
+ "airflowDag": AirflowJobFacet(
+ taskTree=_get_dag_tree(dag_run.dag),
+ taskGroups=_get_task_groups_details(dag_run.dag),
+ tasks=_get_tasks_details(dag_run.dag),
+ )
+ }
+
+
+def get_airflow_state_run_facet(dag_run: DagRun) -> dict[str, BaseFacet]:
+ return {
+ "airflowState": AirflowStateRunFacet(
+ dagRunState=dag_run.get_state(),
+ tasksState={
+ ti.task_id: ti.state
+ for ti in dag_run.fetch_task_instances(dag_id=dag_run.dag_id,
run_id=dag_run.run_id)
Review Comment:
There was a particular concern about this line as it calls Airflow internal
API and this method is called within DAG level listener methods (we are on a
scheduler). I've tested it in breeze, local env and astro cloud, using
different executors (Celery, Local, K8s) and under some pressure (100-2000
concurrent dag runs). **I've encountered NO issues**, but please let me know if
there is a better, more reliable way of testing it. AFAIK, this feature is
production ready.
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