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 <[email protected]>
Date: 2017-03-01T12:37:33Z
add support for null values in Bucketizer
commit b3f98b66e63c9c61c69a1429819feb236fad56c7
Author: Menglong TAN <[email protected]>
Date: 2017-03-01T15:10:05Z
fix a typo
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