dstandish commented on code in PR #659: URL: https://github.com/apache/airflow-site/pull/659#discussion_r973339745
########## landing-pages/site/content/en/blog/airflow-2.4.0/index.md: ########## @@ -0,0 +1,140 @@ +--- +title: "Apache Airflow 2.4.0: Data +linkTitle: "Apache Airflow 2.4.0" +author: "Ash Berlin-Taylor" +github: "ashberlin" +linkedin: "ashberlin-taylor" +description: "We're proud to announce that Apache Airflow 2.4.0 has been released." +tags: [Release] +date: "2022-09-19" +--- + +Apache Airflow +Apache Airflow 2.4.0 contains over 650 "user-facing" commits in this release (excluding commits to providers or chart) and over 870 in total since 2.3.0 and includes 50 new features, 99 improvements, 85 bug fixes, and several doc changes. + +**Details**: + +📦 PyPI: https://pypi.org/project/apache-airflow/2.4.0/ \ +📚 Docs: https://airflow.apache.org/docs/apache-airflow/2.4.0/ \ +🛠️ Release Notes: https://airflow.apache.org/docs/apache-airflow/2.4.0/release_notes.html \ +🐳 Docker Image: docker pull apache/airflow:2.4.0 \ +🚏 Constraints: https://github.com/apache/airflow/tree/constraints-2.4.0 + + +## Data-aware scheduling (AIP-48) + +This one is big. Airflow now has the ability to schedule DAGs based on other tasks updating datasets. + +What does this mean, exactly? This is a great new feature and lets DAG authors create smaller, more self-contained DAGs, that can chain together into a larger data-based workflow. If you are currently using `ExternalTaskSensor` or `TriggerDagRunOperator` you should take a look at datasets -- in most cases you can replace them with something that will speed up the scheduling! Review Comment: Second _dag_ -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
