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

Example usage

extern crate cuckoofilter;

...

let value: &str = "hello world";

//Create cuckoo filter wit max capacity of 1000000 items
let cf = cuckoofilter::new(1000000);

// Add data to the filter
let success = cf.add(&value.as_bytes());
// success ==> true

// Lookup if data is in the filter
let success = cf.lookup(&value.as_bytes());
// success ==> true

// Test and add to the filter (if data does not exists then add)
let success = cf.test_and_add(&value.as_bytes());
// success ==> false

// Test and add to the filter (if data does not exists then add)
let success = cf.delete(&value.as_bytes());
// success ==> true

// Lookup if data is in the filter
let success = cf.lookup(&value.as_bytes());
// success ==> false

##Note 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.