基于Redis BloomFilter算法，redisbloomfilter

基于Redis BloomFilter算法，redisbloomfilter

public class BloomFilter implements Serializable {
   private static final long serialVersionUID = 5829598197124113258L;
   private static final  int  DEFAULT_SIZE  =2 << 25 ; //2的24次方
   private static final  int [] seeds =new  int []{5,7,11,13,19,31,37,61,73,89};//构造不同因子，用于不同散列函数
   private BitSet bits= new  BitSet(DEFAULT_SIZE);
   private SimpleHash[]  func=new  SimpleHash[seeds.length];//对不同的数字构造不同Hash函数避免冲突
   private int size = 0;
   public BloomFilter() {
      for (int i = 0; i < seeds.length; i++) {//初始化构造函数
         func[i] = new SimpleHash(DEFAULT_SIZE, seeds[i]);
      }
   }
   public void add(String value) {
      if(!contains(value)){
         size++;
      }
      for (SimpleHash f : func) { //添加hash值映射到相应位
         bits.set(f.hash(value), true);
      }
   }
   public boolean contains(String value) { //判断存在有一定误判率,所有位置为1不一定存在
      if (value == null) {
         return false;
      }
      boolean ret = true;
      for (SimpleHash f : func) {

 	  if(!bits.get(f.hash(value)){return false};//按照添加时候hash函数计算是否true,判断存在有一定误判率,所有位置为1不一定存在

      }
      return true;
   }

   public int getSize(){
      return size;
   }

   public static class SimpleHash  implements Serializable {
      private static final long serialVersionUID = 1286028965900771610L;
      private int cap;
      private int seed;
      public SimpleHash(int cap, int seed) {
         this.cap = cap;
         this.seed = seed;
      }
      public int hash(String value) {//hash值通过数字个数和数字散列后得到值
         int result = 0;
         int len = value.length();
         for (int i = 0; i < len; i++) {
            result = seed * result + value.charAt(i);
         }
         return (cap - 1) & result;
      }
   }

   public static void main(String[] args) {
      String value = "aaa@yyy.com";
      String value2 = "aaa@yyy.com";
      String value3 = "bbb@yyy.com";
      BloomFilter filter = new BloomFilter();
      System.out.println(filter.contains(value));
      filter.add(value);
      filter.add(value2);
      if(filter.noContains(value3)){
         System.out.println(value3+" 一定不存在 ");
      }
   }

   /*获取100内质数*/
   public static int[] getAllSeeds(){
      return new int[]{2,3,5,7,11,13,17,19,23,29,31,37,41,43,47,53,59,61,67,71,73,79,83,89,97};
   }
}//基于Redis BitSet，由单机扩展到分布式

public void add(byte[] bytes) {
   int[] hashes = createHashes(bytes, k);
   for (int hash : hashes)
       bitset.set(Math.abs(hash % bitSetSize), true);
}

public boolean contains(byte[] bytes) {
    int[] hashes = createHashes(bytes, k);
    for (int hash : hashes) {
        if (!bitset.get(Math.abs(hash % bitSetSize))) {
            return false;
        }
    }
    return true;
}