uranusjr commented on code in PR #40868:
URL: https://github.com/apache/airflow/pull/40868#discussion_r1687398867
##########
airflow/datasets/__init__.py:
##########
@@ -271,6 +306,20 @@ def iter_datasets(self) -> Iterator[tuple[str, Dataset]]:
yield k, v
seen.add(k)
+ def iter_dag_deps(self, *, source: str, target: str) ->
Iterator[DagDependency]:
+ """
+ Iterate dataset, dataset aliases and their resolved datasets as dag
dependency.
+
+ :meta private:
+ """
+ dag_deps: set[DagDependency] = set()
Review Comment:
Is the order of DAG dependencies significant? If not, I think we can
deduplicate at where this function is called instead. If we have aliases nested
in conditions (or just nested conditions), each nesting would have a set doing
deduplication, which isn’t efficient IMO.
Or, do we need to deduplicate dependencies at all…?
--
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]
