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https://issues.apache.org/jira/browse/AIRFLOW-249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17101971#comment-17101971
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ASF GitHub Bot commented on AIRFLOW-249:
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houqp commented on pull request #8545:
URL: https://github.com/apache/airflow/pull/8545#issuecomment-625434121
> My conclusion is that option 1 is a better trade-off, because one has to
go through all TIs in a DagRun to determine if a DR can be free from further
checking (e.g., if a DR has 10 TIs, then each TI has to checked for all
possible SLA violations before the DR is sla_checked). This is not a cheap
operation since a single TI could have 3 SLAs, hence the additional computation
and IO could easily outweigh the benefit of filtering out sla_checked DRs.
Option 1 doesn't guarantee correctness right? i.e. if there are more dagruns
that need to be checked than the preset limit, some of them will be ignored?
With regards to performance comparison between option 1 and option 2, aren't
we already checking all the TIs for the 100 fetched dag runs in option 1?
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> Refactor the SLA mechanism
> --------------------------
>
> Key: AIRFLOW-249
> URL: https://issues.apache.org/jira/browse/AIRFLOW-249
> Project: Apache Airflow
> Issue Type: Improvement
> Reporter: dud
> Priority: Major
>
> Hello
> I've noticed the SLA feature is currently behaving as follow :
> - it doesn't work on DAG scheduled @once or None because they have no
> dag.followwing_schedule property
> - it keeps endlessly checking for SLA misses without ever worrying about any
> end_date. Worse I noticed that emails are still being sent for runs that are
> never happening because of end_date
> - it keeps checking for recent TIs even if SLA notification has been already
> been sent for them
> - the SLA logic is only being fired after following_schedule + sla has
> elapsed, in other words one has to wait for the next TI before having a
> chance of getting any email. Also the email reports dag.following_schedule
> time (I guess because it is close of TI.start_date), but unfortunately that
> doesn't match what the task instances shows nor the log filename
> - the SLA logic is based on max(TI.execution_date) for the starting point of
> its checks, that means that for a DAG whose SLA is longer than its schedule
> period if half of the TIs are running longer than expected it will go
> unnoticed. This could be demonstrated with a DAG like this one :
> {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, 6, 16, 12, 20),
> 'email': my_email
> 'sla': timedelta(minutes=2),
> }
> dag = DAG('unnoticed_sla', 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='sla_miss',
> python_callable=alternating_sleep,
> provide_context=True,
> dag=dag)
> {code}
> I've tried to rework the SLA triggering mechanism by addressing the above
> points., please [have a look on
> it|https://github.com/dud225/incubator-airflow/commit/972260354075683a8d55a1c960d839c37e629e7d]
> I made some tests with this patch :
> - the fluctuent DAG shown above no longer make Airflow skip any SLA event :
> {code}
> task_id | dag_id | execution_date | email_sent |
> timestamp | description | notification_sent
> ----------+---------------+---------------------+------------+----------------------------+-------------+-------------------
> sla_miss | dag_sla_miss1 | 2016-06-16 15:05:00 | t | 2016-06-16
> 15:08:26.058631 | | t
> sla_miss | dag_sla_miss1 | 2016-06-16 15:07:00 | t | 2016-06-16
> 15:10:06.093253 | | t
> sla_miss | dag_sla_miss1 | 2016-06-16 15:09:00 | t | 2016-06-16
> 15:12:06.241773 | | t
> {code}
> - on a normal DAG, the SLA is being triggred more quickly :
> {code}
> // start_date = 2016-06-16 15:55:00
> // end_date = 2016-06-16 16:00:00
> // schedule_interval = timedelta(minutes=1)
> // sla = timedelta(minutes=2)
> task_id | dag_id | execution_date | email_sent |
> timestamp | description | notification_sent
> ----------+---------------+---------------------+------------+----------------------------+-------------+-------------------
> sla_miss | dag_sla_miss1 | 2016-06-16 15:55:00 | t | 2016-06-16
> 15:58:11.832299 | | t
> sla_miss | dag_sla_miss1 | 2016-06-16 15:56:00 | t | 2016-06-16
> 15:59:09.663778 | | t
> sla_miss | dag_sla_miss1 | 2016-06-16 15:57:00 | t | 2016-06-16
> 16:00:13.651422 | | t
> sla_miss | dag_sla_miss1 | 2016-06-16 15:58:00 | t | 2016-06-16
> 16:01:08.576399 | | t
> sla_miss | dag_sla_miss1 | 2016-06-16 15:59:00 | t | 2016-06-16
> 16:02:08.523486 | | t
> sla_miss | dag_sla_miss1 | 2016-06-16 16:00:00 | t | 2016-06-16
> 16:03:08.538593 | | t
> (6 rows)
> {code}
> than before (current master branch) :
> {code}
> // start_date = 2016-06-16 15:40:00
> // end_date = 2016-06-16 15:45:00
> // schedule_interval = timedelta(minutes=1)
> // sla = timedelta(minutes=2)
> task_id | dag_id | execution_date | email_sent |
> timestamp | description | notification_sent
> ----------+---------------+---------------------+------------+----------------------------+-------------+-------------------
> sla_miss | dag_sla_miss1 | 2016-06-16 15:41:00 | t | 2016-06-16
> 15:44:30.305287 | | t
> sla_miss | dag_sla_miss1 | 2016-06-16 15:42:00 | t | 2016-06-16
> 15:45:35.372118 | | t
> sla_miss | dag_sla_miss1 | 2016-06-16 15:43:00 | t | 2016-06-16
> 15:46:30.415744 | | t
> sla_miss | dag_sla_miss1 | 2016-06-16 15:44:00 | t | 2016-06-16
> 15:47:30.507345 | | t
> sla_miss | dag_sla_miss1 | 2016-06-16 15:45:00 | t | 2016-06-16
> 15:48:30.487742 | | t
> sla_miss | dag_sla_miss1 | 2016-06-16 15:46:00 | t | 2016-06-16
> 15:50:40.647373 | | t
> sla_miss | dag_sla_miss1 | 2016-06-16 15:47:00 | t | 2016-06-16
> 15:50:40.647373 | | t
> {code}
> Please note that in this last case (current master) execution_date is equal
> to dag.following_schedule, so SLA is being fired after one extra
> schedule_interval. Also note that SLA are still being triggered after
> end_date. Also note the timestamp column being updated seveal time.
> Please tell me what do you think about my patch.
> dud
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