A simple bloom filter written for learning Cassandra

simple_bloom_filter.go

/*
 This code is written for learning Cassandra's key-value storage,
 where Bloom Filter is used to check the existence of a key in a replica.
*/
package main

import "fmt"
import "math"

/*
Hash calculates the posion of a given key in bitmap.
the hash function: (key^2 + key^3) * i mod m, where
- i is the ith hash function
- m is bitmap size. e.g. m=64, the bitmap is 64 bits
*/
func Hash(key float64, i float64, m float64) int64 {
    val := int64((math.Pow(key, 2) + math.Pow(key, 3)) * i) % int64(m)
    return val 
}

/*
Hash_a calculates the posion of a given key in bitmap.
the hash function: (key^2 + key^3) * i mod m, where
- i is the ith hash function
- m is bitmap size. e.g. m=64, the bitmap is 64 bits
*/
func Hash_a(key float64, i float64, m float64) int64 {
    val := int64(key * i) % int64(m)
    return val 
}

func main() {
    // An example of using Bloom Filter
    m := 64.0
    keys := []float64{1975, 1985, 1995, 2005, 2015}
    for _, k := range keys {
        pos1 := Hash_a(k, 1, m)
        pos2 := Hash_a(k, 2, m)
        fmt.Printf("key %f's positions: %d, %d\n", k, pos1, pos2)
    }   
}