Bloom Filter - probability and benchmarks
December 26, 2020
Bloom filters are a data structure which allows you to test whether an element exists in a set, with lower memory usage and better access times than other hash table implementations. It is probabilistic, and while it can guarantee negative matches, there is a slight chance it returns a false positive match. Through clever mathematical assumptions, we can produce constraints to minimise the chance of a false positive.