SPARK-4547 [MLLIB] OOM when making bins in BinaryClassificationMetrics

Now that I've implemented the basics here, I'm less convinced there is a need for this change, somehow. Callers can downsample before or after. Really the OOM is not in the ROC curve code, but in code that might `collect()` it for local analysis. Still, might be useful to down-sample since the ROC curve probably never needs millions of points.

This is a first pass. Since the `(score,label)` are already grouped and sorted, I think it's sufficient to just take every Nth such pair, in order to downsample by a factor of N? this is just like retaining every Nth point on the curve, which I think is the goal. All of the data is still used to build the curve of course.

What do you think about the API, and usefulness?
Indent comment?  Also, looking at this, I like having the explanation, but it might be nice to format as:
Quick description.
Default value.
Caveat about approximation