Intro Bloom filter is a probabilistic data structure for searching element in a data set. It is similar to HashSet, similarly it tells us whether the set contains certain element or not. Difference is the output of contains(element)=TRUE is futuristic. In our example we set futuristic value to 0.01 , which means the answer "It contains" is 99% correct. Read more about Bloom filter from here: https://en.wikipedia.org/wiki/Bloom_filter Scenario We create two Arrays of random elements. Elements count in each array is 1,000,000. Then we insert the first array into BloomFilter, and we iterate the first array and check if the item contains in BloomFilter. Second array is used only for checking non-existing elements. We do the same for HashSet as described above. Benchmarking code We used customized version of Bloom filter which can accept byte array. (Previous version of this blog was using encoding of string for every put and contains, which was misguiding
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