Description
Bloom filter is a space efficient, probabilistic data structure, designed to test the membership of elements to a set.
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README
blooming-belle - A simple implementation of Bloom Filters
What?
Bloom filter is a space efficient, probabilistic data structure, designed to test the membership of elements to a set.
Trade-offs?
Being a space efficient data structure is it may return false positives, but always returns definite negatives.
Applications?
Testing for non-membership saves resources such as calls to a web server, checking a proxy cache. Google Chrome uses bloom filters as a check for malicious URLs.
blooming-bella
A bloom filter for integers. Uses mummur3,Super Fast Hash and marvin32 hashing algorithms
Example
bella, err := blooming_bella.NewBella(1000, 0.01)
if err != nil {
log.Fatal(err)
}
bella.Add(10)
bella.Add(121)
bella.Add(13)
bella.Add(111)
fmt.Println(bella.Test(10)) // => true
fmt.Println(bella.Test(104)) // => false
fmt.Println(bella.Test(110)) // => false
fmt.Println(bella.Test(13)) // => true
New
Added Super Fast Hashing algorithm
TODO
- [ ] Calculate "ideal" number of hash functions to use.
- [ ] Dynamically "generate" the hash functions. What does it mean to be alive?