LateX

Thursday, May 9, 2013

Fast Bloom Filters

I have looked for Bloom Filter in the internet, but all implementations I have found were too slow. So I implemented my own.

It is not fully general, but I am sure if somebody is desperate for performance like I am they will make it more general by themselves :)

I used Murmur hash implementation that you can download here: http://d3s.mff.cuni.cz/~holub/sw/javamurmurhash/


The code:
package uk.ac.cam.cl.ss958.SpringBoardSimulation;

package uk.ac.cam.cl.ss958;

import ie.ucd.murmur.MurmurHash;

import java.util.BitSet;
import java.util.Random;

public class FastBloomFilter {

 private final BitSet bs;
 
 final int [] hashSeeds;

 final int capacity;
 
 public FastBloomFilter(int slots, int hashFunctions) {
  bs = new BitSet(slots);
  Random r = new Random(System.currentTimeMillis());
  hashSeeds = new int[hashFunctions];
  for (int i=0; i < hashFunctions; ++i) {
   hashSeeds[i] = r.nextInt();
  }
  capacity = slots;
 }
 
 public void add(int value) {
  byte [] b = new byte[] {
             (byte)(value >>> 24),
             (byte)(value >>> 16),
             (byte)(value >>> 8),
             (byte)value};
  for (int i=0; i < hashSeeds.length; ++i) {
   int h = MurmurHash.hash32(b, 4, hashSeeds[i]);
   bs.set(Math.abs(h)%capacity, true);
  }
 }
 
 public void clear() {
  bs.clear();
 }
 
 public boolean mightContain(int value) {
  byte [] b = new byte[] {
             (byte)(value >>> 24),
             (byte)(value >>> 16),
             (byte)(value >>> 8),
             (byte)value};
  for (int i=0; i < hashSeeds.length; ++i) {
   int h = MurmurHash.hash32(b, 4, hashSeeds[i]);
   if(!bs.get(Math.abs(h)%capacity)) {
    return false;
   }
  
  }
  
  return true;
 }
 
 
 public static void main(String [] args) {
  FastBloomFilter bf = new FastBloomFilter(1000, 10);
  System.out.println("Query for 2000: " + bf.mightContain(2000));
  System.out.println("Adding 2000");
  bf.add(2000);
  System.out.println("Query for 2000: " + bf.mightContain(2000));

  
 }
}


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