zhengruifeng opened a new pull request, #58327:
URL: https://github.com/apache/spark/pull/58327

   ### What changes were proposed in this pull request?
   
   This follow-up to #57755 validates the effective `minDF` and `maxDF` values 
after fractional
   thresholds are converted using the input document count. If the effective 
maximum is below the
   minimum, the DataFrame expression raises an error. Regression coverage 
includes both combinations
   of fractional and absolute thresholds.
   
   ### Why are the changes needed?
   
   The DataFrame rewrite retained validation when both thresholds use the same 
units, but dropped the
   post-conversion validation needed when one threshold is fractional and the 
other is absolute. An
   invalid effective range consequently produced an empty vocabulary instead of 
reporting the invalid
   parameters.
   
   ### Does this PR introduce _any_ user-facing change?
   
   Yes. On the unreleased `master` branch, invalid mixed-unit DF ranges now 
raise an error instead of
   silently producing an empty vocabulary. This restores the validation 
behavior from before #57755.
   
   ### How was this patch tested?
   
   Added regression coverage to `CountVectorizerSuite` for both mixed-unit 
invalid-range directions.
   The test suite was not run locally. `git diff --check` passes.
   
   ### Was this patch authored or co-authored using generative AI tooling?
   
   Generated-by: Codex (GPT-5)
   


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