Currently, sampling from a ZipfDistribution is very inefficient. Random values are generated by inverting the CDF. However, the current implementation uses O(N) power function evaluations to calculate the CDF for some point. (Here N is the number of points of the Zipf distribution.) I propose to use rejection sampling instead, which allows the generation of a single random value in constant time.