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https://issues.apache.org/jira/browse/AIRFLOW-372?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16596261#comment-16596261
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jack commented on AIRFLOW-372:
------------------------------
The recommendation I got when I started using airflow is to never mess with
start date. It's preferred to create a new dag with a new start date rather
than changing the old one. Maybe this is why I was recommended to act like this.
> DAGs can run before start_date time
> -----------------------------------
>
> Key: AIRFLOW-372
> URL: https://issues.apache.org/jira/browse/AIRFLOW-372
> Project: Apache Airflow
> Issue Type: Bug
> Affects Versions: Airflow 1.7.1.2
> Reporter: Isaac Steele
> Priority: Major
>
> If you turn off a DAG in the UI, there seemingly is no way to prevent
> "missed" runs to schedule after the DAG is turned back on. I thought the
> workaround for this, since it is not a parameterized option to prevent, would
> be to update the start_date in the DAG code before turning the DAG back on.
> This does not work, and therefore the scheduler is running dag_runs *before*
> the listed start_date.
> To reproduce:
> # Create a DAG with a schedule_interval
> # Let the DAG run at least once
> # Turn off the DAG in the UI
> # Allow the schedule_interval to pass at least twice
> # Update the start_date in the DAG to be be after the two interval time
> # (I then removed the compiled python file and restarted airflow/scheduler
> just to make sure)
> # Turn DAG back on in UI
> Result: All dag_runs that were "missed" while the DAG was turned off run,
> despite the start_date being later.
> Ideally the start_date would always be honored. And also there would be a
> parameter to just not run any "missed" dag_runs.
>
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