Averages.percentiles(PTable<K, V extends Number>, p...) to calculate percentiles by key.

Percentiles are calculated on a per-key basis by counting, joining and sorting. This is highly scalable, but takes
2 more map-reduce cycles than if you can guarantee that the value set will fit into memory. The percentile
definition that we use here is the "nearest rank" defined here: http://en.wikipedia.org/wiki/Percentile#Definition

You should definitely use a different strategy for situations where we know the set will fit into memory. Perhaps
this should be implemented as well.
Add in-memory version of percentiles, which will perform a lot better for smaller (<~10M/key) data sets
Renamed Averages to Statistics, as its scope is now broader
Split Statistics into Averages and Percentiles. Promote anonymous to inner
Merge pull request #3 from spotify/percentiles

Percentiles.(inMemory|scalable)