Cuckoo Filter implementation in Go, better than Bloom Filters
Go
Latest commit 983ed10 Jan 5, 2017 @irfansharif bug: rand bucket selection never selects last one
rand.Intn(n) is not inclusive of n, the 'n - 1' present is unnecessary.

README.md

cfilter: Cuckoo Filter implementation in Go

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Cuckoo filter is a Bloom filter replacement for approximated set-membership queries. Cuckoo filters support adding and removing items dynamically while achieving even higher performance than Bloom filters. For applications that store many items and target moderately low false positive rates, cuckoo filters have lower space overhead than space-optimized Bloom filters. Some possible use-cases that depend on approximated set-membership queries would be databases, caches, routers, and storage systems where it is used to decide if a given item is in a (usually large) set, with some small false positive probability. Alternatively, given it is designed to be a viable replacement to Bloom filters, it can also be used to reduce the space required in probabilistic routing tables, speed longest-prefix matching for IP addresses, improve network state management and monitoring, and encode multicast forwarding information in packets, among many other applications.

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 refer to the original research paper, "Cuckoo Filter: Better Than Bloom" by Bin Fan, Dave Andersen and Michael Kaminsky.

Interface

A cuckoo filter supports following operations:

  • Insert(item): insert an item to the filter
  • Lookup(item): return if item is already in the filter (may return false positive results like Bloom filters)
  • Delete(item): delete the given item from the filter. Note that to use this method, it must be ensured that this item is in the filter (e.g., based on records on external storage); otherwise, a false item may be deleted.
  • Count(): return the total number of items currently in the filter

Example Usage

import "github.com/irfansharif/cfilter"

cf := cfilter.New()

// inserts 'buongiorno' to the filter
cf.Insert([]byte("buongiorno"))

// looks up 'hola' in the filter, may return false positive
cf.Lookup([]byte("hola"))

// returns 1 (given only 'buongiorno' was added)
cf.Count()

// tries deleting 'bonjour' from filter, may delete another element
// this could occur when another byte slice with the same fingerprint
// as another is 'deleted'
cf.Delete([]byte("bonjour"))

This repository was featured on Hacker News, front page (discussion here). Another implementation in Go can be found at seiflotfy/cuckoofilter and is where I borrowed the ideas for my tests, notably TestMultipleInsertions. The original implementation in C++ by the authors of the research paper can be found at efficient/cuckoofilter.

Author

Irfan Sharif: irfanmahmoudsharif@gmail.com, @irfansharifm

License

cfilter source code is available under the MIT License.