[jira] [Created] (AIRFLOW-5538) Add a flag to make scheduling trigger on start_date instead of execution_date (make execution_date equal to start_date)

["kasim (Jira)" <ji...@apache.org>]

kasim created AIRFLOW-5538:
------------------------------

             Summary: Add a flag to make scheduling trigger on start_date instead of execution_date (make execution_date equal to start_date)
                 Key: AIRFLOW-5538
                 URL: https://issues.apache.org/jira/browse/AIRFLOW-5538
             Project: Apache Airflow
          Issue Type: Improvement
          Components: DagRun
    Affects Versions: 1.10.5
            Reporter: kasim


From https://airflow.apache.org/scheduler.html :

> Note that if you run a DAG on a schedule_interval of one day, the run
> stamped 2016-01-01 will be trigger soon after 2016-01-01T23:59. In
> other words, the job instance is started once the period it covers has
> ended.

This feature is very hurt .

For example I have etl job which run every day, schedule_interval is `0 1 * * *`, so it will trigger 2019-09-22 01:00:00 job on 2019-09-23 01:00:00 . But my etl is processing all data before start_date , means data range is between (history, 2019-09-23 00:00:00) , and we can't use `datetime.now()` because this is unable to reproduce. This force me add 1 day to execution_date:
```python
etl_end_time = "\{{ (execution_date + macros.timedelta(days=1)).strftime('%Y-%m-%d 00:00:00') }}"
```

However, when I need run a job with schedule_interval `45 2,3,4,5,6 * * *` , the `2019-09-22 06:45:00` job would run on `2019-09-23 02:45:00`, which is the day after execution_date . Instead of adding a day, I had to changed schedule_interval `45 2,3,4,5,6,7 * * *` and put a dummy operator on last run.
And in this situation , you don't need add one day to execution_date , this means you have to define two `etl_end_time` to represent a same date in jobs with different schedule_interval .

All these are very uncomfortable for me , is there any config or built-in method to make execution_date equal to start_date ? Or I have to modify airflow source code ...

 



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