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MurmurHash算法

2018-06-19
suli

哈希算法在很多系统中有应用,除了在hashmap等数据结构中用外在负载均衡上也有应用,hash算法的性能直接影响很多底层应用,最近在看leveldb源码看到里面用到的hash算法,具体记录一下。

MurmurHash算法介绍

MurmurHash 是一种非加密型哈希函数,适用于一般的哈希检索操作。由Austin Appleby github地址 在2008年发明,并出现了多个变种,都已经发布到了公有领域。与其它流行的哈希函数相比,对于规律性较强的key,MurmurHash的随机分布特征表现更良好,现在在libstdc++,hadoop和nginx等很多著名开源项目中使用。 MurmurHash3的实现,代码

void MurmurHash3_x64_128 ( const void * key, const int len,
                           const uint32_t seed, void * out )
{
  const uint8_t * data = (const uint8_t*)key;
  const int nblocks = len / 16;

  uint64_t h1 = seed;
  uint64_t h2 = seed;

  const uint64_t c1 = BIG_CONSTANT(0x87c37b91114253d5);
  const uint64_t c2 = BIG_CONSTANT(0x4cf5ad432745937f);

  //----------
  // body

  const uint64_t * blocks = (const uint64_t *)(data);

  for(int i = 0; i < nblocks; i++)
  {
    uint64_t k1 = getblock64(blocks,i*2+0);
    uint64_t k2 = getblock64(blocks,i*2+1);

    k1 *= c1; k1  = ROTL64(k1,31); k1 *= c2; h1 ^= k1;

    h1 = ROTL64(h1,27); h1 += h2; h1 = h1*5+0x52dce729;

    k2 *= c2; k2  = ROTL64(k2,33); k2 *= c1; h2 ^= k2;

    h2 = ROTL64(h2,31); h2 += h1; h2 = h2*5+0x38495ab5;
  }

  //----------
  // tail

  const uint8_t * tail = (const uint8_t*)(data + nblocks*16);

  uint64_t k1 = 0;
  uint64_t k2 = 0;

  switch(len & 15)
  {
  case 15: k2 ^= ((uint64_t)tail[14]) << 48;
  case 14: k2 ^= ((uint64_t)tail[13]) << 40;
  case 13: k2 ^= ((uint64_t)tail[12]) << 32;
  case 12: k2 ^= ((uint64_t)tail[11]) << 24;
  case 11: k2 ^= ((uint64_t)tail[10]) << 16;
  case 10: k2 ^= ((uint64_t)tail[ 9]) << 8;
  case  9: k2 ^= ((uint64_t)tail[ 8]) << 0;
           k2 *= c2; k2  = ROTL64(k2,33); k2 *= c1; h2 ^= k2;

  case  8: k1 ^= ((uint64_t)tail[ 7]) << 56;
  case  7: k1 ^= ((uint64_t)tail[ 6]) << 48;
  case  6: k1 ^= ((uint64_t)tail[ 5]) << 40;
  case  5: k1 ^= ((uint64_t)tail[ 4]) << 32;
  case  4: k1 ^= ((uint64_t)tail[ 3]) << 24;
  case  3: k1 ^= ((uint64_t)tail[ 2]) << 16;
  case  2: k1 ^= ((uint64_t)tail[ 1]) << 8;
  case  1: k1 ^= ((uint64_t)tail[ 0]) << 0;
           k1 *= c1; k1  = ROTL64(k1,31); k1 *= c2; h1 ^= k1;
  };

  //----------
  // finalization

  h1 ^= len; h2 ^= len;

  h1 += h2;
  h2 += h1;

  h1 = fmix64(h1);
  h2 = fmix64(h2);

  h1 += h2;
  h2 += h1;

  ((uint64_t*)out)[0] = h1;
  ((uint64_t*)out)[1] = h2;
}

leveldb实现

uint32_t Hash(const char* data, size_t n, uint32_t seed) {
  // Similar to murmur hash
  const uint32_t m = 0xc6a4a793;
  const uint32_t r = 24;
  const char* limit = data + n;
  uint32_t h = seed ^ (n * m);

  // Pick up four bytes at a time
  while (data + 4 <= limit) {
    uint32_t w = DecodeFixed32(data);
    data += 4;
    h += w;
    h *= m;
    h ^= (h >> 16);
  }

  // Pick up remaining bytes
  switch (limit - data) {
    case 3:
      h += static_cast<unsigned char>(data[2]) << 16;
      FALLTHROUGH_INTENDED;
    case 2:
      h += static_cast<unsigned char>(data[1]) << 8;
      FALLTHROUGH_INTENDED;
    case 1:
      h += static_cast<unsigned char>(data[0]);
      h *= m;
      h ^= (h >> r);
      break;
  }
  return h;
}

总结

MurmurHash算法的速度大概是FNV算法的三倍左右,并且相对简单,随机型更好,可以用作以后的工作和使用。


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