wjddn279 commented on issue #61453:
URL: https://github.com/apache/airflow/issues/61453#issuecomment-3869484541

   @pjavier29 
   
   Yes, in my opinion, considering the usage scenario, I don't think additional 
filtering is necessary (refer to PR description), but in-memory filtering would 
be nice. However, I have a question. What was the main cause of the performance 
degradation you observed?
   
   1. Network IO from passing long string queries (the items going into the IN 
operation)
   2. Query performance of the IN operation
   
   In case of 1, the same (or very similar) network IO would have occurred when 
calling 
https://github.com/apache/airflow/blob/main/airflow-core/src/airflow/jobs/scheduler_job_runner.py#L2992.
   
   If 2 is the problem, doing in-memory filtering in Python would be slower 
than the database if anything, not faster, wouldn't it?


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