GitHub user crackcell opened a pull request: https://github.com/apache/spark/pull/17123
[SPARK-19781][ML] Handle NULLs as well as NaNs in Bucketizer when handleInvalid is on ## What changes were proposed in this pull request? The original Bucketizer can put NaNs into a special bucket when handleInvalid is on. but leave NULLs untouched. This PR unify behaviours of processing of NULLs and NaNs. BTW, this is my first commit to Spark code. I'm not sure whether my code or the way of doing things is appropriate. Plz point it out if I'm doing anything wrong. :-) ## How was this patch tested? manual tests You can merge this pull request into a Git repository by running: $ git pull https://github.com/crackcell/spark master Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/17123.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #17123 ---- commit 2b0751428cad5280df47f96412608967b71a7360 Author: Menglong TAN <tanmengl...@gmail.com> Date: 2017-03-01T12:37:33Z add support for null values in Bucketizer commit b3f98b66e63c9c61c69a1429819feb236fad56c7 Author: Menglong TAN <tanmengl...@gmail.com> Date: 2017-03-01T15:10:05Z fix a typo ---- --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org