uranusjr commented on a change in pull request #17552:
URL: https://github.com/apache/airflow/pull/17552#discussion_r689286094
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File path: docs/apache-airflow/concepts/dags.rst
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@@ -148,14 +148,24 @@ The ``schedule_interval`` argument takes any value that
is a valid `Crontab <htt
with DAG("my_daily_dag", schedule_interval="0 * * * *"):
...
-Every time you run a DAG, you are creating a new instance of that DAG which
Airflow calls a :doc:`DAG Run </dag-run>`. DAG Runs can run in parallel for the
same DAG, and each has a defined ``execution_date``, which identifies the
*logical* date and time it is running for - not the *actual* time when it was
started.
+.. tip::
+
+ For more information on ``schedule_interval`` values, see :doc:`DAG Run
</dag-run>`.
+
+ If ``schedule_interval`` is not enough to express the DAG's schedule, see
:doc:`Timetables </howto/timetable>`.
+
+Every time you run a DAG, you are creating a new instance of that DAG which
Airflow calls a :doc:`DAG Run </dag-run>`. DAG Runs can run in parallel for the
same DAG, and each has a defined data interval, which identifies the *logical*
date and time range it is running for - not the *actual* time when it was
started.
As an example of why this is useful, consider writing a DAG that processes a
daily set of experimental data. It's been rewritten, and you want to run it on
the previous 3 months of data - no problem, since Airflow can *backfill* the
DAG and run copies of it for every day in those previous 3 months, all at once.
-Those DAG Runs will all have been started on the same actual day, but their
``execution_date`` values will cover those last 3 months, and that's what all
the tasks, operators and sensors inside the DAG look at when they run.
+Those DAG Runs will all have been started on the same actual day, but their
data intervals will cover those last 3 months, and that's what all the tasks,
operators and sensors inside the DAG look at when they run.
Review comment:
Definitely clearer than the previous wording!
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