Github user marmbrus commented on the pull request: https://github.com/apache/spark/pull/8922#issuecomment-145632836 "daily sql query" is not sufficiently descriptive. Please post actual benchmark results with code when making pull requests that claim to improve performance. It would also be good to evaluate the cost in degenerate cases. For example, I think you are adding an object allocation per input tuple when boxing for any queries that filter by UDF in parquet. Are you slowing down cases where the filter is not selective? If we want to improve the set of things that we push down, I don't think specializing for just UDFs in comparison operations is worth it given how much you are widening the API. Could we just have a single Function filter: ```scala case class FilterFunction(attribute: String, function: Any => Boolean) ``` or maybe some specialized variants: ```scala case class IntegerFilter(attribute: String, Int => Boolean) ... ```
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