[SPARK-3022] [SPARK-3041] [mllib] Call findBins once per level + unordered feature bug fix


DecisionTree improvements:
(1) TreePoint representation to avoid binning multiple times
(2) Bug fix: isSampleValid indexed bins incorrectly for unordered categorical features
(3) Timing for DecisionTree internals

Details:

(1) TreePoint representation to avoid binning multiple times

[https://issues.apache.org/jira/browse/SPARK-3022]

Added private[tree] TreePoint class for representing binned feature values.

The input RDD of LabeledPoint is converted to the TreePoint representation initially and then cached.  This avoids the previous problem of re-computing bins multiple times.

(2) Bug fix: isSampleValid indexed bins incorrectly for unordered categorical features

[https://issues.apache.org/jira/browse/SPARK-3041]

isSampleValid used to treat unordered categorical features incorrectly: It treated the bins as if indexed by featured values, rather than by subsets of values/categories.
* exhibited for unordered features (multi-class classification with categorical features of low arity)
* Fix: Index bins correctly for unordered categorical features.

(3) Timing for DecisionTree internals

Added tree/impl/TimeTracker.scala class which is private[tree] for now, for timing key parts of DT code.
Prints timing info via logDebug.

CC: @mengxr @manishamde @chouqin  Very similar update, with one bug fix.  Many apologies for the conflicting update, but I hope that a few more optimizations I have on the way (which depend on this update) will prove valuable to you: SPARK-3042 and SPARK-3043
@mengxr  I tried Array.copy but ran into issues with the Java code being unhappy with types.  I'd prefer to skip this change for now, since this part of the code is eliminated when I get rid of this part of the aggregation in a subsequent optimization.