Please use wait_on_downstream True. This should fix the issue.
Thanks , Sunil K On Fri, 2 Oct 2020 at 6:58 PM Sandeep Shetty <[email protected]> wrote: > Hi Sunil, > > Let me add more details: > Used Case: The DAG has multiple tasks and is scheduled to run every 5 mins. > Actual result: The DAG kicks off a 2nd run every time there is a failure > in the 1st run. The status of 1st DAG is Failed but 2nd run kicks off after > 5 mins. > Expected Result: The DAG should not kick off a 2nd run unless the first > run completes successfully. > > DAG Code: > > default_args = { > > 'owner': 'xxx', > > 'depends_on_past': True, > > 'start_date': datetime(2020, 6, 15, tzinfo=local_tz), > > 'email': NOTIFY_EMAIL, > > 'email_on_failure': True, > > # 'email_on_retry': True, > > # 'retries': 1, > > 'domain': 'Mediasupplychain' > > # 'retry_delay': timedelta(minutes=30) > > } > > > > > > dag = DAG(DAG_NAME, > > default_args=default_args, > > schedule_interval= '0 */3 * * *', > > catchup=False, > > max_active_runs=1) > > > Airflow screenshot: > [image: image.png] > > On Fri, Oct 2, 2020 at 9:11 AM Sunil Khaire <[email protected]> > wrote: > >> Hi , Sandeep , >> >> Its not quite clear what you want. But if I understood correctly may be >> you can try depend_on_past as True or max_active_runs at dag level. >> >> >> Thanks , >> Sunil Khaire >> >> On Fri, 2 Oct 2020 at 5:32 PM Sandeep S <[email protected]> wrote: >> >>> Hi All, >>> >>> I am having a production issue running only one instance of DAG at a >>> time. If the DAG is running one instance, a 2nd instance does not kick off. >>> But if any of the task fails in the active DAG instance, the DAG gets >>> marked failed but a 2nd instance kicks off after 5 mins(5 mins scheduled >>> time for DAG. >>> >>> Please help. >>> >>> Regards >>> Sandeep >>> >>> On Mon, Sep 28, 2020 at 1:18 PM Tavares Forby <[email protected]> >>> wrote: >>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> Hi All, >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> I am having a few issues with Airflow and task instances greater than >>>> 750. I am getting one consistent error and one error that happens random >>>> (understand, it's technically not random). >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> Consistent error: >>>> >>>> >>>> >>>> >>>> [2020-09-25 12:28:01,703] {scheduler_job.py:237} >>>> >>>> WARNING - Killing PID 119970 [2020-09-25 12:29:17,110] >>>> {scheduler_job.py:237} WARNING - Killing PID 121013 [2020-09-25 >>>> 12:29:17,110] {scheduler_job.py:237} WARNING - Killing PID 121013 >>>> [2020-09-25 12:30:12,171] {scheduler_job.py:237} WARNING - Killing PID >>>> >>>> 123243 >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> Random error: >>>> >>>> >>>> >>>> >>>> [2020-09-27 >>>> >>>> 19:37:25,127] {scheduler_job.py:771} INFO - Examining DAG run <DagRun >>>> tutorial_large_design_debug7 @ 2020-09-28 02:37:24+00:00: >>>> manual__2020-09-28T02:37:24+00:00, externally triggered: True> [2020-09-27 >>>> 19:37:26,749] {logging_mixin.py:112} INFO - [2020-09-27 >>>> >>>> 19:37:26,749] {dagrun.py:408} INFO - (MySQLdb. >>>> >>>> *exceptions.IntegrityError) (1062, "Duplicate entry >>>> 'echo__a*-tutorial_large_design_debug7-2020- >>>> 09-28 02:37:24.000000' for key 'PRIMARY'") >>>> >>>> [SQL: INSERT INTO task_instance (task_id, dag_id, execution_date, >>>> start_date, end_date, duration, state, try_number, max_tries, hostname, >>>> unixname, job_id, pool, pool_slots, queue, priority_weight, operator, qu >>>> eued_dttm, pid, executor_config) VALUES (%s, >>>> >>>> %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, >>>> %s)] >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>>> Please >>>> >>>> help! thanks! >>>> >>>> >>>> >>>> >>>> >>>> >>>> >>> >>> >> >> > >
