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https://issues.apache.org/jira/browse/AIRFLOW-249?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17098719#comment-17098719
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ASF GitHub Bot commented on AIRFLOW-249:
----------------------------------------

seanxwzhang commented on pull request #8545:
URL: https://github.com/apache/airflow/pull/8545#issuecomment-623290340


   Addressed most, if not all comments in the previous round of review. Played 
a bit with two cases regarding how we fetch DagRuns for SLA consideration:
   
   1. Use a fixed number (e.g., 100) for fetching DRs
   2. Add an *sla_checked* column to DR and use it to filter out DRs that have 
already been checked.
   
   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.
   


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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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