Bloom filters are defined by 4 interdependent values:
- n - Number of items in the filter
- p - Probability of false positives, float between 0 and 1 or a number indicating 1-in-p
- m - Number of bits in the filter
- k - Number of hash functions
The values are interdependent as shown in the following calculations:
m = ceil((n * log(p)) / log(1.0 / (pow(2.0, log(2.0)))));
k = round(log(2.0) * m / n);
I use murmur3 hash to generate 128 bit hash integer, and then i split it into two integers of 64 bits each. Following is the pseudo-code written for the design of bloom filter.
let hash_128 = murmur3_hash(data);
let first_64 = (hash_128 & (2_u128.pow(64) - 1));
let second_64 = hash >> 64;
for i 0..num_of_hashfuncs{
first_64 += i* second_64;
index = fist_64 % number_of_bits
self.bitvec.set(index, true);
}
extern crate rust_bloomfilter;
use rust_bloomfilter::BloomFilter;
let mut b = BloomFilter(20000, 0.01, true);
b.add("Helloworld");
assert!(b.contains("Helloworld"));