uranusjr commented on a change in pull request #17552:
URL: https://github.com/apache/airflow/pull/17552#discussion_r707090443
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File path: docs/apache-airflow/dag-run.rst
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@@ -54,17 +54,33 @@ Cron Presets
Your DAG will be instantiated for each schedule along with a corresponding
DAG Run entry in the database backend.
-.. note::
+Data Interval
+-------------
- If you run a DAG on a schedule_interval of one day, the run stamped
2020-01-01
- will be triggered soon after 2020-01-01T23:59. In other words, the job
instance is
- started once the period it covers has ended. The ``execution_date``
available in the context
- will also be 2020-01-01.
+Each DAG run in Airflow has an assigned "data interval" that represents the
time
+range it operates in. For a DAG scheduled with ``@daily``, for example, each of
+its data interval would start at midnight of each day and end at midnight of
the
+next day.
- The first DAG Run is created based on the minimum ``start_date`` for the
tasks in your DAG.
- Subsequent DAG Runs are created by the scheduler process, based on your
DAG’s ``schedule_interval``,
- sequentially. If your start_date is 2020-01-01 and schedule_interval is
@daily, the first run
- will be created on 2020-01-02 i.e., after your start date has passed.
+A DAG run is scheduled *after* its associated data interval has ended, to
ensure
+the run is able to collect all the data within the time period. Therefore, a
run
+covering the data period of 2020-01-01 will not start to run until 2020-01-01
+has ended, i.e. after 2020-01-02 00:00:00.
Review comment:
I made the wording less certain on this to acount for the custom
timetable edge cases. I don’t think running a DAG before its data interval ends
makes enough general sense to complicate the explaination, so this is done with
some “usually” and “generally”s.
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