This is a simple Bloom filter implementation written in Go. For the theory behind Bloom filters, read http://en.wikipedia.org/wiki/Bloom_filter This design uses a user-supplied hash function and salts provided at filter construction time. To determine how many salts are required, call 'SaltsRequired' with the desired filter capacity and false positive percentage. bloom_test.go shows how to do this.

# A simple Bloom Filter implementation in Go

##### Overview

###### A Go implementation of an in-memory bloom filter, with support for boltdb and badgerdb as optional data persistent storage.

Sprout A bloom filter is a probabilistic data structure that is used to determine if an element is present in a set. Bloom filters are fast and space

###### Cuckoo Filter: Practically Better Than Bloom

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###### go/golang: fast bit set Bloom filter

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###### A bloom filter is a probabilistic data structure that is used to determine if an element is present in a set

A Go implementation of a bloom filter, with support for boltdb and badgerdb as optional in-memory persistent storage.

###### Go package implementing Bloom filters

Bloom filters A Bloom filter is a representation of a set of n items, where the main requirement is to make membership queries; i.e., whether an item

###### Go package implementing Bloom filters

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###### Sync distributed sets using bloom filters

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