Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

https://github.com/OldPanda/bloomfilter

Yet another Bloomfilter implementation in Go, compatible with Java's Guava library
https://github.com/OldPanda/bloomfilter

bloomfilter bloomfilter-go golang golang-library

Last synced: about 2 months ago
JSON representation

Yet another Bloomfilter implementation in Go, compatible with Java's Guava library

Lists

README 

        
# bloomfilter



![Build](https://github.com/OldPanda/bloomfilter/workflows/Build/badge.svg?event=push)

[![codecov](https://codecov.io/gh/OldPanda/bloomfilter/branch/master/graph/badge.svg?token=FCV788SCL7)](https://codecov.io/gh/OldPanda/bloomfilter)

[![Go Reference](https://pkg.go.dev/badge/github.com/OldPanda/bloomfilter.svg)](https://pkg.go.dev/github.com/OldPanda/bloomfilter)

[![Go Report Card](https://goreportcard.com/badge/github.com/OldPanda/bloomfilter)](https://goreportcard.com/report/github.com/OldPanda/bloomfilter)

[![Mentioned in Awesome Go](https://awesome.re/mentioned-badge-flat.svg)](https://github.com/avelino/awesome-go)



## Overview



Yet another Bloomfilter implementation in Go, compatible with Java's Guava library. This library borrows how [Java's Guava libraray](https://guava.dev/) implements Bloomfilter hashing strategies to achieve the serialization compatibility.



## Installing



First pull the latest version of the library:



```

go get github.com/OldPanda/bloomfilter

```



Then import the this library in your code:



```

import "github.com/OldPanda/bloomfilter"

```



## Usage Examples



### Basic Usage



```Go

package main



import (

	"fmt"



	"github.com/OldPanda/bloomfilter"

)



func main() {

	// create bloomfilter with expected insertion=500, error rate=0.01

	bf, _ := bloomfilter.NewBloomFilter(500, 0.01)

	// add number 0~199 into bloomfilter

	for i := 0; i < 200; i++ {

		bf.Put(i)

	}



	// check if number 100 and 200 are in bloomfilter

	fmt.Println(bf.MightContain(100))

	fmt.Println(bf.MightContain(200))

}

```



### Serialization



```Go

package main



import "github.com/OldPanda/bloomfilter"



func main() {

	// expected insertion=500, error rate=0.01

	bf, _ := bloomfilter.NewBloomFilter(500, 0.01)

	// add 0~199 into bloomfilter

	for i := 0; i < 200; i++ {

		bf.Put(i)

	}



	// serialize bloomfilter to byte array

	bytes := bf.ToBytes()

	// handling the bytes ...

}

```



### Deserialization



```Go

package main



import (

	"fmt"



	"github.com/OldPanda/bloomfilter"

)



func main() {

	// create bloomfilter from byte array

	bf, _ := bloomfilter.FromBytes(bytes)

	// check whether number 100 is in bloomfilter

	fmt.Println(bf.MightContain(100))

}

```



## Benchmark



The benchmark testing runs on element insertion and query separately.



```Bash

» go test -bench . -benchmem ./...

# github.com/OldPanda/bloomfilter.test

goos: darwin

goarch: amd64

pkg: github.com/OldPanda/bloomfilter

cpu: Intel(R) Core(TM) i7-4870HQ CPU @ 2.50GHz

BenchmarkBloomfilterInsertion-8                  4923142               387.1 ns/op            17 B/op          1 allocs/op

BenchmarkBloomfilterQuery-8                      4678299               259.6 ns/op            15 B/op          1 allocs/op

BenchmarkBloomfilterDeserialization-8             162871              7110 ns/op           13200 B/op         52 allocs/op

PASS

ok      github.com/OldPanda/bloomfilter 4.880s

```