Cuckoo Filter: Practically Better Than Bloom
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seiflotfy Merge pull request #17 from AuspeXeu/master
Updated example to work with latest version of go
Latest commit 09e42b4 Aug 1, 2018

Cuckoo Filter


Cuckoo filter is a Bloom filter replacement for approximated set-membership queries. While Bloom filters are well-known space-efficient data structures to serve queries like "if item x is in a set?", they do not support deletion. Their variances to enable deletion (like counting Bloom filters) usually require much more space.

Cuckoo filters provide the flexibility to add and remove items dynamically. A cuckoo filter is based on cuckoo hashing (and therefore named as cuckoo filter). It is essentially a cuckoo hash table storing each key's fingerprint. Cuckoo hash tables can be highly compact, thus a cuckoo filter could use less space than conventional Bloom filters, for applications that require low false positive rates (< 3%).

For details about the algorithm and citations please use this article for now

"Cuckoo Filter: Better Than Bloom" by Bin Fan, Dave Andersen and Michael Kaminsky


This implementation uses a a static bucket size of 4 fingerprints and a fingerprint size of 1 byte based on my understanding of an optimal bucket/fingerprint/size ratio from the aforementioned paper.

Example usage:

package main

import "fmt"
import ""

func main() {
  cf := cuckoofilter.NewDefaultCuckooFilter()
  cf.InsertUnique([]byte("geeky ogre"))

  // Lookup a string (and it a miss) if it exists in the cuckoofilter

  count := cf.Count()
  fmt.Println(count) // count == 1

  // Delete a string (and it a miss)

  count = cf.Count()
  fmt.Println(count) // count == 1

  // Delete a string (a hit)
  cf.Delete([]byte("geeky ogre"))

  count = cf.Count()
  fmt.Println(count) // count == 0


"Cuckoo Filter on GoDoc"