kaxil commented on a change in pull request #18310:
URL: https://github.com/apache/airflow/pull/18310#discussion_r710960302
##########
File path: tests/jobs/test_local_task_job.py
##########
@@ -707,6 +707,48 @@ def test_fast_follow(
if scheduler_job.processor_agent:
scheduler_job.processor_agent.end()
+ @conf_vars({('scheduler', 'schedule_after_task_execution'): 'True'})
+ def test_mini_scheduler_works_with_wait_for_upstream(self, caplog,
dag_maker):
+ session = settings.Session()
+ dep = {'A': 'B', 'B': 'C'}
+ with dag_maker(default_args={'wait_for_downstream': True},
catchup=False) as dag:
+ task_a = PythonOperator(task_id='A', python_callable=lambda: True)
+ task_b = PythonOperator(task_id='B', python_callable=lambda: True)
+ task_c = PythonOperator(task_id='C', python_callable=lambda: True)
+ for upstream, downstream in dep.items():
+ dag.set_dependency(upstream, downstream)
+
+ scheduler_job = SchedulerJob(subdir=os.devnull)
+ scheduler_job.dagbag.bag_dag(dag, root_dag=dag)
+
+ dr = dag.create_dagrun(run_id='test_1', state=State.RUNNING,
execution_date=DEFAULT_DATE)
+ dr2 = dag.create_dagrun(
+ run_id='test_2', state=State.RUNNING, execution_date=DEFAULT_DATE
+ datetime.timedelta(hours=1)
+ )
+ ti_a = TaskInstance(task_a, run_id=dr.run_id, state=State.SUCCESS)
+ ti_b = TaskInstance(task_b, run_id=dr.run_id, state=State.SUCCESS)
+ ti_c = TaskInstance(task_c, run_id=dr.run_id, state=State.RUNNING)
+ ti2_a = TaskInstance(task_a, run_id=dr2.run_id, state=State.NONE)
+ ti2_b = TaskInstance(task_b, run_id=dr2.run_id, state=State.NONE)
+ ti2_c = TaskInstance(task_c, run_id=dr2.run_id, state=State.NONE)
+ session.merge(ti_a)
+ session.merge(ti_b)
+ session.merge(ti_c)
+ session.merge(ti2_a)
+ session.merge(ti2_b)
+ session.merge(ti2_c)
+ session.flush()
+
+ job1 = LocalTaskJob(task_instance=ti2_a, ignore_ti_state=True,
executor=SequentialExecutor())
+ job1.task_runner = StandardTaskRunner(job1)
+ settings.engine.dispose()
+ job1.run()
+ ti2_a.refresh_from_db()
+ assert (
Review comment:
```suggestion
assert ti2_a.state=State.NONE
assert (
```
##########
File path: tests/jobs/test_local_task_job.py
##########
@@ -707,6 +707,48 @@ def test_fast_follow(
if scheduler_job.processor_agent:
scheduler_job.processor_agent.end()
+ @conf_vars({('scheduler', 'schedule_after_task_execution'): 'True'})
+ def test_mini_scheduler_works_with_wait_for_upstream(self, caplog,
dag_maker):
+ session = settings.Session()
+ dep = {'A': 'B', 'B': 'C'}
+ with dag_maker(default_args={'wait_for_downstream': True},
catchup=False) as dag:
+ task_a = PythonOperator(task_id='A', python_callable=lambda: True)
+ task_b = PythonOperator(task_id='B', python_callable=lambda: True)
+ task_c = PythonOperator(task_id='C', python_callable=lambda: True)
+ for upstream, downstream in dep.items():
+ dag.set_dependency(upstream, downstream)
+
+ scheduler_job = SchedulerJob(subdir=os.devnull)
+ scheduler_job.dagbag.bag_dag(dag, root_dag=dag)
+
+ dr = dag.create_dagrun(run_id='test_1', state=State.RUNNING,
execution_date=DEFAULT_DATE)
+ dr2 = dag.create_dagrun(
+ run_id='test_2', state=State.RUNNING, execution_date=DEFAULT_DATE
+ datetime.timedelta(hours=1)
+ )
+ ti_a = TaskInstance(task_a, run_id=dr.run_id, state=State.SUCCESS)
+ ti_b = TaskInstance(task_b, run_id=dr.run_id, state=State.SUCCESS)
+ ti_c = TaskInstance(task_c, run_id=dr.run_id, state=State.RUNNING)
+ ti2_a = TaskInstance(task_a, run_id=dr2.run_id, state=State.NONE)
+ ti2_b = TaskInstance(task_b, run_id=dr2.run_id, state=State.NONE)
+ ti2_c = TaskInstance(task_c, run_id=dr2.run_id, state=State.NONE)
+ session.merge(ti_a)
+ session.merge(ti_b)
+ session.merge(ti_c)
+ session.merge(ti2_a)
+ session.merge(ti2_b)
+ session.merge(ti2_c)
+ session.flush()
+
+ job1 = LocalTaskJob(task_instance=ti2_a, ignore_ti_state=True,
executor=SequentialExecutor())
+ job1.task_runner = StandardTaskRunner(job1)
+ settings.engine.dispose()
Review comment:
why do we need this?
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