zhengruifeng opened a new pull request, #57236: URL: https://github.com/apache/spark/pull/57236
### What changes were proposed in this pull request? Consolidate the specialized PySpark `VALUE_NOT_ANY_OR_ALL` error condition into the existing `VALUE_NOT_ALLOWED` condition. The classic and Spark Connect implementations of `DataFrame.dropna` now report the allowed values through the generic condition, and the shared test expectation is updated accordingly. ### Why are the changes needed? `VALUE_NOT_ANY_OR_ALL` is used only for `DataFrame.dropna(how=...)` and duplicates the existing generic condition for arguments restricted to a fixed set of values. Removing it reduces the number of narrowly scoped error conditions and aligns this validation with other PySpark APIs. ### Does this PR introduce _any_ user-facing change? Yes. Invalid values for `DataFrame.dropna(how=...)` now use the `VALUE_NOT_ALLOWED` error condition and its generic message. Valid calls and exception types are unchanged. ### How was this patch tested? The focused PySpark test was not run. The JSON error-condition file was parsed successfully, `git diff --check` passed, and the existing shared error assertion was updated for both classic and Spark Connect execution modes. ### Was this patch authored or co-authored using generative AI tooling? Generated-by: Codex (GPT-5) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
