kaxil opened a new pull request, #57592:
URL: https://github.com/apache/airflow/pull/57592
When updating dynamic DAGs (those without task instances), Airflow was
loading the entire `SerializedDagModel` object from the database, which could
contain megabytes of JSON data, just to update a few fields which was
completely unnecesary.
This change replaces the object-loading approach with a direct SQL UPDATE
statement, significantly improving performance for deployments with large or
frequently-changing dynamic DAGs.
The optimization uses SQLAlchemy's update() construct to modify only the
necessary columns (_data, _data_compressed, dag_hash) without fetching the
existing row, reducing both database load and network transfer.
Additionally, removed an unnecessary session.merge() call on dag_version, as
the object is already tracked by the session after being loaded.
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