Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/5980#issuecomment-100321346
Sorry that I didn't see the hidden GitHub comments. I think it depends on
the use cases of bucketizer. My guess is that in most cases users use
bucketizer on values that they already know the range. For example, time ->
hourOfDay, dayOfMonth, or age -> 10-year buckets. In those cases, accepting
`(-inf, firstSplit]` and `(lastSplit, inf)` by default may result empty
buckets. Another issue is what the expected behavior is for values out of
range. Should they go to a new bucket, or be merged into the closest bucket?
Letting users explicitly specify the buckets would be able to avoid those
problems.
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