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 very 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.