gongxun0928 / bloom

Go package implementing Bloom filters

Bloom filters

A Bloom filter is a representation of a set of n items, where the main requirement is to make membership queries; i.e., whether an item is a member of a set.

A Bloom filter has two parameters: m, a maximum size (typically a reasonably large multiple of the cardinality of the set to represent) and k, the number of hashing functions on elements of the set. (The actual hashing functions are important, too, but this is not a parameter for this implementation). A Bloom filter is backed by a BitSet; a key is represented in the filter by setting the bits at each value of the hashing functions (modulo m). Set membership is done by testing whether the bits at each value of the hashing functions (again, modulo m) are set. If so, the item is in the set. If the item is actually in the set, a Bloom filter will never fail (the true positive rate is 1.0); but it is susceptible to false positives. The art is to choose k and m correctly.

In this implementation, the hashing functions used is murmurhash, a non-cryptographic hashing function.

This implementation accepts keys for setting and testing as []byte. Thus, to add a string item, "Love":

n := uint(1000)
filter := bloom.New(20*n, 5) // load of 20, 5 keys
filter.Add([]byte("Love"))

Similarly, to test if "Love" is in bloom:

if filter.Test([]byte("Love"))

For numeric data, I recommend that you look into the encoding/binary library. But, for example, to add a uint32 to the filter:

i := uint32(100)
n1 := make([]byte, 4)
binary.BigEndian.PutUint32(n1, i)
filter.Add(n1)

Finally, there is a method to estimate the false positive rate of a particular bloom filter for a set of size n:

if filter.EstimateFalsePositiveRate(1000) > 0.001

Given the particular hashing scheme, it's best to be empirical about this. Note that estimating the FP rate will clear the Bloom filter.

Discussion here: Bloom filter

Godoc documentation: https://godoc.org/github.com/willf/bloom

Installation

go get -u github.com/willf/bloom

Contributing

If you wish to contribute to this project, please branch and issue a pull request against master ("GitHub Flow")

This project include a Makefile that allows you to test and build the project with simple commands. To see all available options:

make help

Running all tests

Before committing the code, please check if it passes all tests using (note: this will install some dependencies):

make deps
make qa