[
https://issues.apache.org/jira/browse/AIRFLOW-140?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15292963#comment-15292963
]
dud commented on AIRFLOW-140:
-----------------------------
Hello.
I tried with the LocalExecutor as requested and I observed the same behaviour :
{code}
airflow=> SELECT * FROM task_instance WHERE dag_id = :dag_id ORDER BY
execution_date ; SELECT * FROM dag_run WHERE dag_id = :dag_id ; SELECT * FROM
job ORDER BY start_date DESC LIMIT 5;
task_id | dag_id | execution_date | start_date
| end_date | duration | state | try_number | hostname
| unixname | job_id | pool | queue | priority_weight | operator |
queued_dttm
----------+---------------+---------------------+----------------------------+----------------------------+-----------+---------+------------+-----------+----------+--------+------+---------+-----------------+----------------+-------------
alt_sleep | dagrun_not_updated | 2016-05-20 07:45:00 | 2016-05-20
07:46:54.372843 | | | running | 1
| localhost | airflow | 3203 | | default | 1 |
PythonOperator |
alt_sleep | dagrun_not_updated | 2016-05-20 07:46:00 | 2016-05-20
07:47:19.317705 | 2016-05-20 07:47:29.453316 | 10.135611 | success | 1
| localhost | airflow | 3204 | | default | 1 |
PythonOperator |
alt_sleep | dagrun_not_updated | 2016-05-20 07:47:00 | 2016-05-20
07:48:01.724885 | | | running | 1
| localhost | airflow | 3205 | | default | 1 |
PythonOperator |
alt_sleep | dagrun_not_updated | 2016-05-20 07:48:00 | 2016-05-20
07:49:12.031225 | 2016-05-20 07:49:22.083763 | 10.052538 | success | 1
| localhost | airflow | 3206 | | default | 1 |
PythonOperator |
(4 rows)
id | dag_id | execution_date | state | run_id
| external_trigger | conf | end_date | start_date
------+---------------+---------------------+---------+--------------------------------+------------------+------+----------+----------------------------
1485 | dagrun_not_updated | 2016-05-20 07:45:00 | running |
scheduled__2016-05-20T07:45:00 | f | | |
2016-05-20 07:46:38.30924
1486 | dagrun_not_updated | 2016-05-20 07:46:00 | running |
scheduled__2016-05-20T07:46:00 | f | | |
2016-05-20 07:47:01.563541
1487 | dagrun_not_updated | 2016-05-20 07:47:00 | running |
scheduled__2016-05-20T07:47:00 | f | | |
2016-05-20 07:48:00.016718
1488 | dagrun_not_updated | 2016-05-20 07:48:00 | running |
scheduled__2016-05-20T07:48:00 | f | | |
2016-05-20 07:49:00.203204
(4 rows)
id | dag_id | state | job_type | start_date |
end_date | latest_heartbeat | executor_class | hostname |
unixname
------+--------+---------+--------------+----------------------------+----------------------------+----------------------------+----------------+-----------+----------
3206 | | success | LocalTaskJob | 2016-05-20 07:49:08.691714 |
2016-05-20 07:49:23.706144 | 2016-05-20 07:49:08.691725 | LocalExecutor |
localhost | airflow
3205 | | running | LocalTaskJob | 2016-05-20 07:48:01.155988 |
| 2016-05-20 07:50:51.312164 | LocalExecutor | localhost |
airflow
3204 | | success | LocalTaskJob | 2016-05-20 07:47:16.153078 |
2016-05-20 07:47:31.168997 | 2016-05-20 07:47:16.153091 | LocalExecutor |
localhost | airflow
3203 | | running | LocalTaskJob | 2016-05-20 07:46:48.198379 |
| 2016-05-20 07:50:53.42636 | LocalExecutor | localhost |
airflow
3202 | | running | SchedulerJob | 2016-05-20 07:45:31.43799 |
| 2016-05-20 07:50:55.061958 | LocalExecutor | localhost |
airflow
{code}
Database logs :
{code}
2016-05-20 07:47:31 UTC [24003-36] airflow@airflow LOG: duration: 38.731 ms
statement: UPDATE job SET state='success',
end_date='2016-05-20T07:47:31.168997'::timestamp,
latest_heartbeat='2016-05-20T07:47:16.153091'::timestamp WHERE job.id = 3204
2016-05-20 07:49:23 UTC [24107-36] airflow@airflow LOG: duration: 0.179 ms
statement: UPDATE job SET state='success',
end_date='2016-05-20T07:49:23.706144'::timestamp,
latest_heartbeat='2016-05-20T07:49:08.691725'::timestamp WHERE job.id = 3206
2016-05-20 07:52:03 UTC [23971-336] airflow@airflow LOG: duration: 0.291 ms
statement: UPDATE job SET state='success',
end_date='2016-05-20T07:52:03.526927'::timestamp,
latest_heartbeat='2016-05-20T07:46:48.198389'::timestamp WHERE job.id = 3203
2016-05-20 07:53:06 UTC [24047-326] airflow@airflow LOG: duration: 0.179 ms
statement: UPDATE job SET state='success',
end_date='2016-05-20T07:53:06.444879'::timestamp,
latest_heartbeat='2016-05-20T07:48:01.155997'::timestamp WHERE job.id = 3205
2016-05-20 07:53:10 UTC [24276-18] airflow@airflow LOG: duration: 0.315 ms
statement: UPDATE dag_run SET state='success' WHERE dag_run.id = 1485
2016-05-20 07:53:10 UTC [24276-19] airflow@airflow LOG: duration: 0.108 ms
statement: UPDATE dag_run SET state='success' WHERE dag_run.id = 1486
2016-05-20 07:53:10 UTC [24276-20] airflow@airflow LOG: duration: 0.090 ms
statement: UPDATE dag_run SET state='success' WHERE dag_run.id = 1487
2016-05-20 07:53:10 UTC [24276-21] airflow@airflow LOG: duration: 0.098 ms
statement: UPDATE dag_run SET state='success' WHERE dag_run.id = 1488
2016-05-20 07:53:40 UTC [24307-36] airflow@airflow LOG: duration: 0.177 ms
statement: UPDATE job SET state='success',
end_date='2016-05-20T07:53:40.881165'::timestamp,
latest_heartbeat='2016-05-20T07:53:25.864395'::timestamp WHERE job.id = 3208
{code}
Extract of Airflow logs
{code}
May 20 07:47:29 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:47:29,947]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:47:40 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:47:39,950]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:47:44 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:47:44,955]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:47:49 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:47:49,963]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:47:55 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:47:54,967]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:48:00 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:48:00,102]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:48:09 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:48:09,996]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:48:19 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:48:19,995]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:48:24 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:48:24,996]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:48:30 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:48:30,001]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:48:35 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:48:35,008]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:48:40 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:48:40,006]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:48:45 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:48:45,015]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:48:50 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:48:50,079]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:49:00 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:49:00,273]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:49:05 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:49:05,682]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:49:16 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:49:16,606]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:49:25 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:49:25,045]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:49:25 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:49:25,046]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:48:00: scheduled__2016-05-20T07:48:00, externally triggered: False>
successful
May 20 07:49:30 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:49:30,080]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:49:30 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:49:30,081]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:48:00: scheduled__2016-05-20T07:48:00, externally triggered: False>
successful
May 20 07:49:40 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:49:40,511]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:49:40 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:49:40,511]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:48:00: scheduled__2016-05-20T07:48:00, externally triggered: False>
successful
May 20 07:49:50 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:49:50,072]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:49:50 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:49:50,073]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:48:00: scheduled__2016-05-20T07:48:00, externally triggered: False>
successful
May 20 07:49:55 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:49:55,074]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:46:00: scheduled__2016-05-20T07:46:00, externally triggered: False>
successful
May 20 07:49:55 airflow-ec2 airflow-scheduler[23873]: [2016-05-20 07:49:55,074]
{models.py:2725} INFO - Marking run <DagRun dagrun_not_updated @ 2016-05-20
07:48:00: scheduled__2016-05-20T07:48:00, externally triggered: False>
successful
{code}
For the record I'm getting the same issue with the SequentialExecutor and the
CeleryExecutor as well.
dud
> DagRun state not updated
> ------------------------
>
> Key: AIRFLOW-140
> URL: https://issues.apache.org/jira/browse/AIRFLOW-140
> Project: Apache Airflow
> Issue Type: Bug
> Components: scheduler
> Environment: Airflow latest Git version
> Reporter: dud
> Priority: Minor
>
> Hello
> I've noticed a strange behaviour : when launching a DAG whose task execution
> duration is alternatingly slower and longer, DagRun state is only updated if
> all previous DagRuns have ended.
> Here is DAG that can trigger this behaviour :
> {code}
> from airflow import DAG
> from airflow.operators import *
> from datetime import datetime, timedelta
> from time import sleep
> default_args = {
> 'owner': 'airflow',
> 'depends_on_past': False,
> 'start_date': datetime(2016, 5, 19, 10, 15),
> 'end_date': datetime(2016, 5, 19, 10, 20),
> }
> dag = DAG('dagrun_not_updated', default_args=default_args,
> schedule_interval=timedelta(minutes=1))
> def alternating_sleep(**kwargs):
> minute = kwargs['execution_date'].strftime("%M")
> is_odd = int(minute) % 2
> if is_odd:
> sleep(300)
> else:
> sleep(10)
> return True
> PythonOperator(
> task_id='alt_sleep',
> python_callable=alternating_sleep,
> provide_context=True,
> dag=dag)
> {code}
> When this operator is executed, being run at an even minute makes the TI runs
> faster than an odd one.
> I'm observing the following behaviour :
> - after some time, the second DagRun is still i running state despites it has
> ended for a while :
> {code}
> airflow=> SELECT * FROM task_instance WHERE dag_id = :dag_id ORDER BY
> execution_date ; SELECT * FROM dag_run WHERE dag_id = :dag_id ;
> task_id | dag_id | execution_date | start_date
> | end_date | duration | state | try_number |
> hostname | unixname | job_id | pool | queue | priority_weight |
> operator | queued_dttm
> ----------+---------------+---------------------+----------------------------+----------------------------+-----------+---------+------------+-----------+----------+--------+------+---------+-----------------+----------------+-------------
> alt_sleep | dagrun_not_updated | 2016-05-19 10:15:00 | 2016-05-19
> 10:17:19.039565 | | | running |
> 1 | localhost | airflow | 3196 | | default | 1 |
> PythonOperator |
> alt_sleep | dagrun_not_updated | 2016-05-19 10:16:00 | 2016-05-19
> 10:17:23.698928 | 2016-05-19 10:17:33.823066 | 10.124138 | success |
> 1 | localhost | airflow | 3197 | | default | 1 |
> PythonOperator |
> alt_sleep | dagrun_not_updated | 2016-05-19 10:17:00 | 2016-05-19
> 10:18:03.025546 | | | running |
> 1 | localhost | airflow | 3198 | | default | 1 |
> PythonOperator |
> (3 rows)
> id | dag_id | execution_date | state |
> run_id | external_trigger | conf | end_date | start_date
>
> ------+---------------+---------------------+---------+--------------------------------+------------------+------+----------+----------------------------
> 1479 | dagrun_not_updated | 2016-05-19 10:15:00 | running |
> scheduled__2016-05-19T10:15:00 | f | | |
> 2016-05-19 10:17:06.563842
> 1480 | dagrun_not_updated | 2016-05-19 10:16:00 | running |
> scheduled__2016-05-19T10:16:00 | f | | |
> 2016-05-19 10:17:12.188781
> 1481 | dagrun_not_updated | 2016-05-19 10:17:00 | running |
> scheduled__2016-05-19T10:17:00 | f | | |
> 2016-05-19 10:18:01.550625
> (3 rows)
> {code}
> - afer some time, all reportedly still running DagRuns are being marked as
> successful at the same time :
> {code}
> 2016-05-19 10:23:11 UTC [12073-18] airflow@airflow LOG: duration: 0.168 ms
> statement: UPDATE dag_run SET state='success' WHERE dag_run.id = 1479
> 2016-05-19 10:23:11 UTC [12073-19] airflow@airflow LOG: duration: 0.106 ms
> statement: UPDATE dag_run SET state='success' WHERE dag_run.id = 1480
> 2016-05-19 10:23:11 UTC [12073-20] airflow@airflow LOG: duration: 0.083 ms
> statement: UPDATE dag_run SET state='success' WHERE dag_run.id = 1481
> 2016-05-19 10:23:11 UTC [12073-21] airflow@airflow LOG: duration: 0.081 ms
> statement: UPDATE dag_run SET state='success' WHERE dag_run.id = 1482
> {code}
> So it waited till the 4th DagRun ended to update the dag_run table.
> I've looked at the code I'm not sure whether the issue lies in Airflow as the
> scheduler properly runs the code that updates the state to sucess :
> {code}
> May 19 10:17:36 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:17:36,542] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:17:41 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:17:41,666] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:17:51 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:17:51,571] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:17:56 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:17:56,578] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:18:01 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:18:01,591] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:18:06 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:18:06,735] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:18:16 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:18:16,599] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:18:21 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:18:21,623] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:18:31 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:18:31,651] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:18:41 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:18:41,611] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:18:46 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:18:46,625] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:18:56 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:18:56,619] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:19:01 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:19:01,640] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:19:07 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:19:07,355] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:19:16 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:19:16,633] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:19:21 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:19:21,710] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:19:21 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:19:21,711] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:18:00: scheduled__2016-05-19T10:18:00, externally triggered:
> False> successful
> May 19 10:19:31 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:19:31,646] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:19:31 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:19:31,647] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:18:00: scheduled__2016-05-19T10:18:00, externally triggered:
> False> successful
> May 19 10:19:36 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:19:36,650] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:19:36 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:19:36,651] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:18:00: scheduled__2016-05-19T10:18:00, externally triggered:
> False> successful
> May 19 10:19:41 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:19:41,656] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:19:41 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:19:41,657] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:18:00: scheduled__2016-05-19T10:18:00, externally triggered:
> False> successful
> May 19 10:19:51 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:19:51,659] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:19:51 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:19:51,659] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:18:00: scheduled__2016-05-19T10:18:00, externally triggered:
> False> successful
> May 19 10:19:56 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:19:56,664] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:19:56 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:19:56,664] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:18:00: scheduled__2016-05-19T10:18:00, externally triggered:
> False> successful
> May 19 10:20:01 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:20:01,670] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:20:01 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:20:01,671] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:18:00: scheduled__2016-05-19T10:18:00, externally triggered:
> False> successful
> May 19 10:20:06 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:20:06,669] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:20:06 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:20:06,674] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:18:00: scheduled__2016-05-19T10:18:00, externally triggered:
> False> successful
> May 19 10:20:11 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:20:11,739] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:20:11 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:20:11,739] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:18:00: scheduled__2016-05-19T10:18:00, externally triggered:
> False> successful
> May 19 10:20:21 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:20:21,726] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:20:21 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:20:21,727] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:18:00: scheduled__2016-05-19T10:18:00, externally triggered:
> False> successful
> May 19 10:20:31 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:20:31,699] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:20:31 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:20:31,699] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:18:00: scheduled__2016-05-19T10:18:00, externally triggered:
> False> successful
> May 19 10:20:36 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:20:36,700] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:16:00: scheduled__2016-05-19T10:16:00, externally triggered:
> False> successful
> May 19 10:20:36 airflow-ec2 airflow-scheduler[11543]: [2016-05-19
> 10:20:36,700] {models.py:2725} INFO - Marking run <DagRun dagrun_not_updated
> @ 2016-05-19 10:18:00: scheduled__2016-05-19T10:18:00, externally triggered:
> False> successful
> {code}
> I've also verified that the scheduler runs session.commit(). But for some
> reason this doesn't trigger any database sync.
> Please note that I have the following parameters in my configuration that may
> be related with the behaviour reported above :
> {code}
> parallelism = 4
> max_active_runs_per_dag = 4
> {code}
> dud
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