stas-snow commented on issue #22193:
URL: https://github.com/apache/airflow/issues/22193#issuecomment-1067079346
Code:
```
import logging
import time
# Airflow packages
from random import uniform
from airflow.decorators import dag, task
logger = logging.getLogger(__name__)
default_dag_args = {
'owner': 'airflow',
'start_date': '2022-03-01',
'schedule_interval': '@daily',
'retries': 0,
'catchup': True,
'max_active_runs': 1,
'depends_on_past': False,
}
@dag(default_args=default_dag_args)
def test2_dag():
@task()
def start():
logging.info("Starting DAG. Going to sleep")
time.sleep(uniform(1, 5) * 60)
logging.info("First task, exiting")
return None
@task()
def do():
time.sleep(uniform(1, 5) * 60)
return None
@task()
def end():
logging.info(f"Finishing...")
time.sleep(3)
return None
# Define dependency between tasks
start() >> do() >> end()
# start the DAG
test_pipeline = test2_dag()
```
Screenshot of multiple DAG instances all in "Running" state.
<img width="546" alt="image"
src="https://user-images.githubusercontent.com/93541868/158224423-fae9b635-abd2-4be5-a292-fa2c6d3c5398.png";>
Documentation says that there should not be more than max_active_runs in
Running state:
```
max_active_runs – maximum number of active DAG runs, beyond this number of
DAG runs in a running state, the scheduler won’t create new active DAG runs
```
I would expect only 1 DAG in Running state if I have "max_active_runs = 1".
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