Well-tuned, production-ready cuckoo filter that performs best in class for low false positive rates (at around 0.01%). For details, see full evaluation.

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%).

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

The paper cited above leaves several parameters to choose. In this implementation

1. Every element has 2 possible bucket indices
2. Buckets have a static size of 4 fingerprints
3. Fingerprints have a static size of 16 bits

1 and 2 are suggested to be the optimum by the authors. The choice of 3 comes down to the desired false positive rate. Given a target false positive rate of r and a bucket size b, they suggest choosing the fingerprint size f using

f >= log2(2b/r) bits

With the 16 bit fingerprint size in this repository, you can expect r ~= 0.0001. Other implementations use 8 bit, which correspond to a false positive rate of r ~= 0.03.

import (
	"fmt"

	cuckoo "github.com/livekit/cuckoofilter"
)

func Example() {
	cf := cuckoo.NewFilter(1000)

	cf.Insert([]byte("pizza"))
	cf.Insert([]byte("tacos"))
	cf.Insert([]byte("tacos")) // Re-insertion is possible.

	fmt.Println(cf.Lookup([]byte("pizza")))
	fmt.Println(cf.Lookup([]byte("missing")))

	cf.Reset()
	fmt.Println(cf.Lookup([]byte("pizza")))
	// Output:
	// true
	// false
	// false
}

For more examples, see the example tests. Operations on a filter are not thread safe by default. See this example for using the filter concurrently.