In its own pod on a kubernetes cluster based on the task's queue It provides the capability of running tasks with either LocalExecutor, which runs tasks within the scheduler service, or with KubernetesExecutor, which runs each task This will help reduce time when running DB Migrations (when updating Airflow version) □ The new `airflow db clean` CLI command for purging old records. Includes a "-show-sql-only" to output all the SQL so that you can run it yourself! You can downgrade to a particular Airflow version or a to a specific Alembic revision id. □ First class support for DB downgrade - `airflow db downgrade` command. Paves way for DAG Versioning - to easily show versions, which was impossible to handle in Tree View ! yay! Show runs and tasks but leave dependency lines to the graph view and handles Task Groups better! □ Dynamic Task Mapping: No longer hacking around dynamic tasks !!Īllows a way for a workflow to create a number of tasks at runtime based upon current data, rather than the DAG author having to know in advance how many tasks would be needed. □ Docker Image: "docker pull apache/airflow:2.3.0" □ And a new "SmoothOperator" - This is a surprise ! And a very powerful feature, try it out and let me know what you think about it □ □ Create Connection in native JSON format - no need to figure out the URI format □ The new `airflow db clean` CLI command for purging old records The following are the biggest & noteworthy changes□□□: ➡️ 700+ commits since 2.2 including 50 new features, 99 improvements, 85 bug fixes ➡️ This is the biggest Apache Airflow release since 2.0.0
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