jedcunningham commented on code in PR #26208:
URL: https://github.com/apache/airflow/pull/26208#discussion_r965178315
##########
docs/apache-airflow/concepts/datasets.rst:
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@@ -15,33 +15,185 @@
specific language governing permissions and limitations
under the License.
-Datasets
-========
+Data-aware scheduling
+=====================
.. versionadded:: 2.4
-With datasets, instead of running a DAG on a schedule, a DAG can be configured
to run when a dataset has been updated.
+Quickstart
+----------
-To use this feature, define a dataset:
+In addition to scheduling DAGs based upon time, they can also be scheduled
based upon a task updating a dataset.
-.. exampleinclude:: /../../airflow/example_dags/example_datasets.py
- :language: python
- :start-after: [START dataset_def]
- :end-before: [END dataset_def]
+.. code-block:: python
-Then reference the dataset as a task outlet:
+ from airflow import Dataset
-.. exampleinclude:: /../../airflow/example_dags/example_datasets.py
- :language: python
- :dedent: 4
- :start-after: [START task_outlet]
- :end-before: [END task_outlet]
+ with DAG(...):
+ MyOperator(
+ # this task updates example.csv
+ outlets=[Dataset("s3://dataset-bucket/example.csv")],
+ ...,
+ )
-Finally, define a DAG and reference this dataset in the DAG's ``schedule``
argument:
-.. exampleinclude:: /../../airflow/example_dags/example_datasets.py
- :language: python
- :start-after: [START dag_dep]
- :end-before: [END dag_dep]
+ with DAG(
+ # this DAG should be run when example.csv is updated (by dag1)
+ schedule=[Dataset("s3://dataset-bucket/example.csv")],
+ ...,
+ ):
+ ...
-You can reference multiple datasets in the DAG's ``schedule`` argument. Once
there has been an update to all of the upstream datasets, the DAG will be
triggered. This means that the DAG will run as frequently as its
least-frequently-updated dataset.
+What is a "dataset"?
+--------------------
+
+An Airflow dataset is a stand-in for a logical grouping of data. Datasets may
be updated by upstream "producer" tasks, and dataset updates contribute to
scheduling downstream "consumer" DAGs.
+
+A dataset is defined by a Uniform Resource Identifier (URI):
+
+.. code-block:: python
+
+ from airflow import Dataset
+
+ example_dataset = Dataset('s3://dataset-bucket/example.csv')
+
+Airflow makes no assumptions about the content or location of the data
represented by the identifier. It is treated as a string, so any use of regular
expressions (eg ``input_\d+.csv``) or file glob patterns (eg
``input_2022*.csv``) as an attempt to create multiple datasets from one
declaration will not work.
Review Comment:
```suggestion
Airflow makes no assumptions about the content or location of the data
represented by the URI. It is treated as a string, so any use of regular
expressions (eg ``input_\d+.csv``) or file glob patterns (eg
``input_2022*.csv``) as an attempt to create multiple datasets from one
declaration will not work.
```
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