Retry on Airflow Schedule DAG Run DB Deadlock

[anthonyp97]

• This resolves the following issue: Deadlock in Scheduler Loop when Updating Dag Run #25765
• We have tested this on our most recent deployment and confirmed that we are retrying these deadlocks gracefully now with this change and the main scheduler loop no longer breaks with these deadlocks.

---

^ Add meaningful description above

Read the Pull Request Guidelines for more information.
In case of fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
In case of a new dependency, check compliance with the ASF 3rd Party License Policy.
In case of backwards incompatible changes please leave a note in a newsfragment file, named {pr_number}.significant.rst or {issue_number}.significant.rst, in newsfragments.

[boring-cyborg]

Congratulations on your first Pull Request and welcome to the Apache Airflow community! If you have any issues or are unsure about any anything please check our Contribution Guide (https://github.com/apache/airflow/blob/main/CONTRIBUTING.rst)
Here are some useful points:

• Pay attention to the quality of your code (flake8, mypy and type annotations). Our pre-commits will help you with that.
• In case of a new feature add useful documentation (in docstrings or in docs/ directory). Adding a new operator? Check this short guide Consider adding an example DAG that shows how users should use it.
• Consider using Breeze environment for testing locally, it's a heavy docker but it ships with a working Airflow and a lot of integrations.
• Be patient and persistent. It might take some time to get a review or get the final approval from Committers.
• Please follow ASF Code of Conduct for all communication including (but not limited to) comments on Pull Requests, Mailing list and Slack.
• Be sure to read the Airflow Coding style.
  Apache Airflow is a community-driven project and together we are making it better 🚀.
  In case of doubts contact the developers at:
  Mailing List: dev@airflow.apache.org
  Slack: https://s.apache.org/airflow-slack

[potiuk]

LGTM. But I would love others (@ashb?) to take a look.

[potiuk]

You also need to rebase @anthonyp97 to fix unrelated failures I think.

[blag]

Is there a reason you're including callback_to_run in the return statement here?? It seems cleaner to just return callback_tuples, especially because the last callback_to_run is going to be included in the last tuple of callback_tuples anyway.

The next line of code overwrites callback_to_run as well, so it just seems unnecessary to pass it back:

            callback_tuples, callback_to_run = self._schedule_all_dag_runs(guard, dag_runs, session)

        # ...
        for dag_run, callback_to_run in callback_tuples:  # <-- callback_to_run overwritten immediately

Also, would a dictionary be a better option to map dag runs to callbacks?

[anthonyp97]

@blag yea definitely right that I should just be returning callback_tuples, will update this. For the second point I imagine it shouldn't really matter between list of tuples and a dict since we are just iterating through the data structure either way element by element but if you strongly prefer a dict I can update to use that.

[blag]

I don't strongly prefer a dict, that's just what makes more sense to me. But yeah, if a list works then go with that.

[anthonyp97]

@potiuk @ashb just following up here, do you think this is good to merge now? Just hoping this can get in to the 2.4.1 release whenever that is planned to be, thank you!

[potiuk]

I think we are just about to release 2.4.1 I think it looks good to me, but we have just merged 2.4.1 branch to release it. I think it will go to 2.4.2.

[potiuk]

I also think @ashb should take a look.

[boring-cyborg]

Awesome work, congrats on your first merged pull request!