yuseok89 commented on code in PR #75635:
URL: https://github.com/apache/airflow/pull/75635#discussion_r4389889817


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airflow-core/src/airflow/api_fastapi/common/parameters/search.py:
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Review Comment:
   For reference, here is what I measured through the Dag runs endpoint on 
Postgres, with 5M runs across 200 Dags.
   
   | Case | Before | After |
   |---|---|---|
   | Matching runs spread evenly | 35 to 116 ms | 48 to 161 ms |
   | A Dag whose matching runs are all old | 39 ms | 10.6 s |
   | A Dag with no recent runs | 97 ms | 6.5 s |
   
   With evenly distributed runs I got results similar to yours, but skewed data 
can be much slower.
   
   Changing the indexes could be one way to keep prefix ranges correct under 
any collation, but that would be a bigger change, so a separate PR might suit 
it better.



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