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Refactor scheduler task concurrency evaluation into a dedicated helper. #67589

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Refactor scheduler task concurrency evaluation into a dedicated helper. #67589

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149 changes: 85 additions & 64 deletions airflow-core/src/airflow/jobs/scheduler_job_runner.py
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Original file line number Diff line number Diff line change
Expand Up @@ -543,6 +543,80 @@ def _debug_dump(self, signum: int, frame: FrameType | None) -> None:
self.log.info("\n\t".join(map(repr, callstack)))
self.log.info("-" * 80)

def _task_concurrency_allows_execution(
self,
*,
task_instance: TI,
concurrency_map: ConcurrencyMap,
session: Session,
starved_tasks: set[tuple[str, str]],
starved_tasks_task_dagrun_concurrency: set[tuple[str, str, str]],
) -> bool:
"""Evaluate task-level concurrency constraints for a task instance."""
dag_id = task_instance.dag_id
task_id = task_instance.task_id
run_id = task_instance.run_id

serialized_dag = self.scheduler_dag_bag.get_dag_for_run(
dag_run=task_instance.dag_run,
session=session,
)

# If the DAG is missing, fail all scheduled TIs for this DAG.
if not serialized_dag:
self.log.error(
"DAG '%s' for task instance %s not found in serialized_dag table",
dag_id,
task_instance,
)

session.execute(
update(TI)
.where(TI.dag_id == dag_id, TI.state == TaskInstanceState.SCHEDULED)
.values(state=TaskInstanceState.FAILED)
.execution_options(synchronize_session="fetch")
)

return False

if not serialized_dag.has_task(task_id):
return True

task = serialized_dag.get_task(task_id)

task_concurrency_limit = task.max_active_tis_per_dag

if task_concurrency_limit is not None:
current_task_concurrency = concurrency_map.task_concurrency_map[(dag_id, task_id)]

if current_task_concurrency >= task_concurrency_limit:
self.log.info(
"Not executing %s since the task concurrency for this task has been reached.",
task_instance,
)

starved_tasks.add((dag_id, task_id))
return False

task_dagrun_concurrency_limit = task.max_active_tis_per_dagrun

if task_dagrun_concurrency_limit is not None:
current_task_dagrun_concurrency = concurrency_map.task_dagrun_concurrency_map[
(dag_id, run_id, task_id)
]

if current_task_dagrun_concurrency >= task_dagrun_concurrency_limit:
self.log.info(
"Not executing %s since the task concurrency per DAG run for this task has been reached.",
task_instance,
)

starved_tasks_task_dagrun_concurrency.add((dag_id, run_id, task_id))

return False

return True

def _executable_task_instances_to_queued(self, max_tis: int, session: Session) -> list[TI]:
"""
Find TIs that are ready for execution based on conditions.
Expand Down Expand Up @@ -868,71 +942,18 @@ def _executable_task_instances_to_queued(self, max_tis: int, session: Session) -
starved_dags.add(dag_id)
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
# Many DAGs do not define task concurrency limits, so avoid
# loading the serialized DAG unless required.
if task_instance.dag_model.has_task_concurrency_limits and not (
self._task_concurrency_allows_execution(
task_instance=task_instance,
concurrency_map=concurrency_map,
session=session,
starved_tasks=starved_tasks,
starved_tasks_task_dagrun_concurrency=(starved_tasks_task_dagrun_concurrency),
)
# If the dag is missing, fail the task and continue to the next task.
if not serialized_dag:
self.log.error(
"DAG '%s' for task instance %s not found in serialized_dag table",
dag_id,
task_instance,
)
session.execute(
update(TI)
.where(TI.dag_id == dag_id, TI.state == TaskInstanceState.SCHEDULED)
.values(state=TaskInstanceState.FAILED)
.execution_options(synchronize_session="fetch")
)
continue

task_concurrency_limit: int | None = None
if serialized_dag.has_task(task_instance.task_id):
task_concurrency_limit = serialized_dag.get_task(
task_instance.task_id
).max_active_tis_per_dag

if task_concurrency_limit is not None:
current_task_concurrency = concurrency_map.task_concurrency_map[
(task_instance.dag_id, task_instance.task_id)
]

if current_task_concurrency >= task_concurrency_limit:
self.log.info(
"Not executing %s since the task concurrency for this task has been reached.",
task_instance,
)
starved_tasks.add((task_instance.dag_id, task_instance.task_id))
continue

task_dagrun_concurrency_limit: int | None = None
if serialized_dag.has_task(task_instance.task_id):
task_dagrun_concurrency_limit = serialized_dag.get_task(
task_instance.task_id
).max_active_tis_per_dagrun

if task_dagrun_concurrency_limit is not None:
current_task_dagrun_concurrency = concurrency_map.task_dagrun_concurrency_map[
(task_instance.dag_id, task_instance.run_id, task_instance.task_id)
]

if current_task_dagrun_concurrency >= task_dagrun_concurrency_limit:
self.log.info(
"Not executing %s since the task concurrency per DAG run for"
" this task has been reached.",
task_instance,
)
starved_tasks_task_dagrun_concurrency.add(
(
task_instance.dag_id,
task_instance.run_id,
task_instance.task_id,
)
)
continue
):
continue

if executor_obj := self._try_to_load_executor(
task_instance, session, team_name=dag_id_to_team_name.get(task_instance.dag_id, NOTSET)
Expand Down