Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/3702#issuecomment-67106963
@jkbradley Sure, well my thinking was that there is a nice straightforward
approach based on sampling every Nth point, so the natural thing is to add a
parameter for this N. Of course you can also compute this from a `numBins`
parameter and that does sound more useful. But N has to be an integer, so you
won't quite get what you expect if you ask for 1000 bins for 1100 points and
end up with 1100 or 550.
For the more common case, where you might ask for 1000 bins for millions of
points, this rounding error doesn't matter. What do you think -- close enough?
I think it would take more code to get the 1000-of-1100 example to take 1000
points that are as evenly spaced as possible, but it wouldn't be crazy. Worth
the extra bit of complexity?
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