kaxil commented on code in PR #54103:
URL: https://github.com/apache/airflow/pull/54103#discussion_r2705351672
##########
airflow-core/tests/unit/jobs/test_scheduler_job.py:
##########
@@ -1266,6 +1312,71 @@ def
test_find_executable_task_instances_executor_with_teams(self, dag_maker, moc
]
assert len(b_tis_in_wrong_executor) == 0
+ @conf_vars(
+ {
+ ("scheduler", "max_tis_per_query"): "100",
+ ("scheduler", "max_dagruns_to_create_per_loop"): "10",
+ ("scheduler", "max_dagruns_per_loop_to_schedule"): "20",
+ ("core", "parallelism"): "100",
+ ("core", "max_active_tasks_per_dag"): "4",
+ ("core", "max_active_runs_per_dag"): "10",
+ ("core", "default_pool_task_slot_count"): "64",
+ }
+ )
+ def test_per_dr_limit_applied_in_task_query(self, dag_maker,
mock_executors):
+ scheduler_job = Job()
+ scheduler_job.executor.parallelism = 100
+ scheduler_job.executor.slots_available = 70
+ scheduler_job.max_tis_per_query = 100
+ self.job_runner = SchedulerJobRunner(job=scheduler_job)
+ session = settings.Session()
+
+ # Use the same run_id.
+ task_maker(dag_maker, session, "dag_1300_tasks", 1300, 4, "run1")
+ task_maker(dag_maker, session, "dag_1200_tasks", 1200, 4, "run1")
+ task_maker(dag_maker, session, "dag_1100_tasks", 1100, 4, "run1")
+ task_maker(dag_maker, session, "dag_100_tasks", 100, 4, "run1")
+ task_maker(dag_maker, session, "dag_90_tasks", 90, 4, "run1")
+ task_maker(dag_maker, session, "dag_80_tasks", 80, 4, "run1")
+
+ count = 0
+ iterations = 0
+
+ from airflow.configuration import conf
+
+ task_num = conf.getint("core", "max_active_tasks_per_dag") * 6
+
+ # 6 dags * 4 = 24.
+ assert task_num == 24
+
+ queued_tis = None
+ while count < task_num:
+ # Use `_executable_task_instances_to_queued` because it returns a
list of TIs
+ # while `_critical_section_enqueue_task_instances` just returns
the number of the TIs.
+ queued_tis = self.job_runner._executable_task_instances_to_queued(
+ max_tis=scheduler_job.executor.slots_available, session=session
+ )
+ count += len(queued_tis)
+ iterations += 1
+
+ assert iterations == 1
+ assert count == task_num
+
+ assert queued_tis is not None
+
+ dag_counts = Counter(ti.dag_id for ti in queued_tis)
+
+ # Tasks from all 6 dags should have been queued.
+ assert len(dag_counts) == 6
+ assert dag_counts == {
+ "dag_1300_tasks": 4,
+ "dag_1200_tasks": 4,
+ "dag_1100_tasks": 4,
+ "dag_100_tasks": 4,
+ "dag_90_tasks": 4,
+ "dag_80_tasks": 4,
+ }, "Count for each dag_id should be 4 but it isn't"
+
def test_find_executable_task_instances_order_priority_with_pools(self,
dag_maker):
Review Comment:
Couple test cases worth adding:
1. **Starvation filter ordering**: dag run with tasks in mixed pools (some
starved, some not). Verify non-starved pool tasks aren't excluded because
starved-pool tasks consumed row_number slots.
2. **Partial capacity**: dag run with `max_active_tasks=4` where 2 are
already RUNNING + 10 SCHEDULED. Verify query returns only 2 (not 4) for that
run.
##########
airflow-core/src/airflow/jobs/scheduler_job_runner.py:
##########
@@ -515,7 +590,13 @@ def _executable_task_instances_to_queued(self, max_tis:
int, session: Session) -
try:
locked_query = with_row_locks(query, of=TI, session=session,
skip_locked=True)
- task_instances_to_examine: list[TI] =
list(session.scalars(locked_query).all())
+ task_instances_to_examine = session.scalars(locked_query).all()
+
+ self.log.debug("Length of the tis to examine is %d",
len(task_instances_to_examine))
+ self.log.debug(
+ "TaskInstance selection is: %s",
+ dict(Counter(ti.dag_id for ti in
task_instances_to_examine)),
+ )
timer.stop(send=True)
Review Comment:
nit: The `Counter()` iteration runs even when debug logging is disabled. If
we're optimizing for perf:
```python
if self.log.isEnabledFor(logging.DEBUG):
self.log.debug(...)
```
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