This is part 5 of my series on calculating percentiles on streaming data.

I have created a reusable C++ library which contains my implementation of the streaming percentile algorithms found within this blog post and published it to GitHub. Here’s what using it looks like:

#include <stmpct/gk.hpp> using namespace stmpct; double epsilon = 0.1; gk g(epsilon); for (int i = 0; i < 1000; ++i) g.insert(rand()); double p50 = g.quantile(0.5); // Approx. median double p95 = g.quantile(0.95); // Approx. 95th percentile

You can find it here:

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