[GitHub] [airflow] potiuk commented on a change in pull request #6999: [AIRFLOW-XXXX] Clarify wait_for_downstream and execution_date

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potiuk commented on a change in pull request #6999: [AIRFLOW-XXXX] Clarify wait_for_downstream and execution_date
URL: https://github.com/apache/airflow/pull/6999#discussion_r363110368
 
 

 ##########
 File path: docs/concepts.rst
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 @@ -113,13 +116,138 @@ DAGs can be used as context managers to automatically assign new operators to th
 
     op.dag is dag # True
 
-.. _concepts-operators:
+.. _concepts:dagruns:
+
+DAG Runs
+========
+
+A DAG run is a physical instance of a DAG, containing task instances that run for a specific ``execution_date``.
+
+A DAG run is usually created by the Airflow scheduler, but can also be created by an external trigger. 
+Multiple DAG runs may be running at once for a particular DAG, each of them having a different ``execution_date``.
+For example, we might currently have two DAG runs that are in progress for 2016-01-01 and 2016-01-02 respectively.
+
+.. _concepts:execution_date:
+
+execution_date
+--------------
+
+The ``execution_date`` is the *logical* date and time which the DAG Run, and its task instances, are running for.
+
+This allows task instances to process data for the desired *logical* date & time.
+While a task_instance or DAG run might have a *physical* start date of now,
+their *logical* date might be 3 months ago because we are busy reloading something.
+
+In the prior example the ``execution_date`` was 2016-01-01 for the first DAG Run and 2016-01-02 for the second.
+
+A DAG run and all task instances created within it are instanced with the same ``execution_date``, so
+that logically you can think of a DAG run as simulating the DAG running all of its tasks at some
+previous date & time specified by the ``execution_date``.
+
+.. _concepts:tasks:
+
+Tasks
 
 Review comment:
   ❤️ 

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