GitHub user viirya opened a pull request:
https://github.com/apache/spark/pull/17819
[SPARK-20542][ML][SQL][WIP] Add a Bucketizer that can bin multiple columns
## What changes were proposed in this pull request?
Current ML's Bucketizer can only bin a column of continuous features. If a
dataset has thousands of of continuous columns needed to bin, we will result in
thousands of ML stages. It is inefficient regarding query planning and
execution.
We should have a type of bucketizer that can bin a lot of columns all at
once. It would need to accept an list of arrays of split points to correspond
to the columns to bin, but it might make things more efficient by replacing
thousands of stages with just one.
This current approach in this patch is to add a new `MultipleBucketizer`
for this purpose.
## How was this patch tested?
Jenkins tests.
Please review http://spark.apache.org/contributing.html before opening a
pull request.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/viirya/spark-1 SPARK-20542
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/17819.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 #17819
----
commit e8f5d89ab2c344d52ae245b1b22cb4425ae6ffa0
Author: Liang-Chi Hsieh <[email protected]>
Date: 2017-05-01T14:07:10Z
Add a Bucketizer that can bin multiple columns.
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