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Speed up airflow dags list on deployments with many Dags - #73033
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Listing Dags issued two extra queries for every Dag printed: one to load the DagModel row, and another when the response model reached the lazily loaded tags relationship. The command therefore got slower in proportion to the number of Dags, which is exactly the case it matters most for. The batched lookup is chunked rather than issued as a single IN clause so that installations with tens of thousands of Dags stay below the backend's bind parameter cap, where one oversized statement would fail outright.
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Hello @Eason09053360 - thank you for your contributions to Apache Airflow! The Airflow community has introduced a limit of 5 open pull requests at a time for contributors without write access to the repository. You currently have 33 open pull requests, so - as a one-time step of introducing the limit - we closed the ones where maintainers have not engaged yet:
These pull requests stay open because maintainers are already engaged in them - they count towards your limit:
This is not a judgement of you or of your changes. We never told contributors before that opening many pull requests at once was a problem, so there is nothing to feel bad about - and nothing is lost: your branches, commits and the review history stay where they are. What we ask you to do is to make your first prioritization decision: choose which of the pull requests above matter most to you, and reopen them (up to 5 open at a time, including the ones still open) with the "Reopen pull request" button or While your pull requests are waiting for review, the most valuable thing you can do is help in other ways - reviewing other contributors' pull requests, helping with issues, and taking part in the discussions on the devlist and Slack. Why we introduced the limit, what it means for you and how to reopen or restore a pull request is explained in https://github.com/apache/airflow/blob/main/contributing-docs/32_open_pull_request_limit.rst. Drafted-by: Claude Code (Opus 5); reviewed by @potiuk before posting |
Why
airflow dags listissued two extra queries for every Dag it printed: aDagModellookup in the row mapper, and a lazy load oftagswhenDAGResponseserialised the row. With N Dags that is 2N round trips, so the command gets slower the more Dags a deployment has.What
dag_list_dagsnow prefetches theDagModelrows with their tags before printing, chunked at 500 ids so large deployments stay under the backend's bind-parameter limit. Output and the dagbag fallback for Dags missing from thedagtable are unchanged.test_cli_list_dags_does_not_query_per_dagasserts the query count is the same for 2 and 6 Dags.Was generative AI tooling used to co-author this PR?
Generated-by: Claude Code (Fable 5.1) following the guidelines