abhishekbhakat commented on code in PR #54775:
URL: https://github.com/apache/airflow/pull/54775#discussion_r2318243252
##########
airflow/jobs/scheduler_job_runner.py:
##########
@@ -1350,7 +1350,11 @@ def _create_dag_runs(self, dag_models:
Collection[DagModel], session: Session) -
)
for dag_model in dag_models:
- dag = self.dagbag.get_dag(dag_model.dag_id, session=session)
+ try:
+ dag = self.dagbag.get_dag(dag_model.dag_id, session=session)
+ except Exception:
Review Comment:
I can raise specifically for serialization error. Which I'll have to import
in job runner.
But I feel like broad exception handling is insurance against scheduler
failure.
No matter what error arises, scheduler should never fail.
More specific exception handling belongs in DAG parsing logic or DAG
serialization methods.
We can log the exception message. Let me know if you still think we should
raise a specific exception.
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