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
extern crate cuckoofilter; ... let value: &str = "hello world"; // Create cuckoo filter with default max capacity of 1000000 items let mut cf = cuckoofilter::new(); // Add data to the filter let success = cf.add(value); // success ==> true // Lookup if data is in the filter let success = cf.contains(value); // success ==> true // Test and add to the filter (if data does not exists then add) let success = cf.test_and_add(value); // success ==> false // Remove data from the filter. let success = cf.delete(value); // success ==> true
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.