blag commented on code in PR #27745:
URL: https://github.com/apache/airflow/pull/27745#discussion_r1028830891
##########
airflow/models/dag.py:
##########
@@ -2822,6 +2822,11 @@ def bulk_write_to_db(
all_datasets = outlet_datasets
all_datasets.update(input_datasets)
+ # Save this set of URIs for later, since we del all_datasets before we
use this
+ datasets_to_remove = {_[0] for _ in
session.query(DatasetModel.uri).all()} - {
+ k.uri for k in all_datasets.keys()
Review Comment:
Well shoot, you're right. I was using `airflow dags reserialize` to
explicitly reload DAGs, which does load all of the DAGs at once and gives a
correct overview of all referenced (and more importantly, unreferenced)
datasets. But the DAG processor setup loads individual `.py` files at a time,
and does not have a global view of all datasets. So this approach isn't going
to work for that.
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