HeartSaVioR edited a comment on pull request #30167:
URL: https://github.com/apache/spark/pull/30167#issuecomment-718331516


   Additionally, if the pattern is normal in Spark codebase I think we should 
revisit - if users configure something (A) and Spark decides to fail back (B), 
it must be only case where there's no functional difference between A and B 
(e.g. whole stage codegen failback might be OK as it should ideally only have 
difference on performance). Otherwise Spark is silently breaking the intention.


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