[GitHub] [airflow] tanelk commented on pull request #21901: Add `max_active_runs_reached` column to DagModel

[GitBox <gi...@apache.org>]

tanelk commented on PR #21901:
URL: https://github.com/apache/airflow/pull/21901#issuecomment-1100813499

   I have some questions about this PR. Mainly how does it help with the "original" issue - deadlocking?
   
   These changes you propose might bring amazing performace improvements (hard to say without benchmarks) but it "feels" like a wrong way to solve a deadlock issue.  
   
   I'm now just spitballing without actually running the code.  The pair of methods `self._should_update_dag_next_dagruns` and `dag_model.calculate_dagrun_date_fields` are called in 3 places:
   
   Once when creating dag runs:
   https://github.com/apache/airflow/blob/3a2eb961ca628d962ed5fad68760ef3439b2f40b/airflow/jobs/scheduler_job.py#L1038-L1039
   
   Twice when scheduling those dag runs:
   https://github.com/apache/airflow/blob/3a2eb961ca628d962ed5fad68760ef3439b2f40b/airflow/jobs/scheduler_job.py#L1139-L1140
   https://github.com/apache/airflow/blob/3a2eb961ca628d962ed5fad68760ef3439b2f40b/airflow/jobs/scheduler_job.py#L1165-L1166
   
   In the first case we have a lock on the `DagModel` from the `DagModel.dags_needing_dagruns` method. In the second two cases we have a lock on the `DagRun` from the `DagRun.next_dagruns_to_examine` method.
   
   Perhaps we should be locking also on the `DagModel`, because we are modifing it? It is probably best to bounce it by @ashb.
   


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