[
https://issues.apache.org/jira/browse/AIRFLOW-140?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Chris Riccomini updated AIRFLOW-140:
------------------------------------
Component/s: scheduler
> 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
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
