jscheffl commented on code in PR #62878:
URL: https://github.com/apache/airflow/pull/62878#discussion_r3041764476
##########
airflow-core/src/airflow/jobs/scheduler_job_runner.py:
##########
@@ -763,25 +763,29 @@ def _executable_task_instances_to_queued(self, max_tis:
int, session: Session) -
starved_dags.add(dag_id)
continue
+ if dag_id in starved_dags:
+ continue
+
if task_instance.dag_model.has_task_concurrency_limits:
# Many dags don't have a task_concurrency, so where we can
avoid loading the full
# serialized DAG the better.
serialized_dag = self.scheduler_dag_bag.get_dag_for_run(
dag_run=task_instance.dag_run, session=session
)
- # If the dag is missing, fail the task and continue to the
next task.
+ # If the dag is transiently missing, skip scheduling it
this iteration
+ # and try again next time instead of bulk-failing all
scheduled tasks.
+ # Known limitation: permanently deleted DAGs will stay
SCHEDULED and
+ # trigger this warning every iteration. A follow-up can
track consecutive
+ # misses and escalate to failure after N iterations.
+ # See: https://github.com/apache/airflow/issues/62050
if not serialized_dag:
- self.log.error(
- "DAG '%s' for task instance %s not found in
serialized_dag table",
+ self.log.warning(
Review Comment:
Replicating the comment here such that it is not over-looked:
By reading the code I had exactly the same comment like kaxil earlier.
I think we can not leave it like this, because it would maybe improve some
cases but leave endless loop of scheduled tasks. Therefore I'd suggest to add a
check such that tasks are not endless looped over.
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