levelDB跳表实现

跳表的原理就是利用随机性建立索引，加速搜索，并且简化代码实现难度。具体的跳表原理不再赘述，主要是看了levelDB有一些实现细节的东西，凸显自己写的实现不足之处。

• 去除冗余的key

    template<typename Key, class Comparator>
    struct SkipList<Key,Comparator>::Node {
      explicit Node(const Key& k) : key(k) { }
  
      Key const key;
  
      // Accessors/mutators for links.  Wrapped in methods so we can
      // add the appropriate barriers as necessary.
      Node* Next(int n) {
        assert(n >= 0);
        // Use an 'acquire load' so that we observe a fully initialized
        // version of the returned Node.
        return reinterpret_cast<Node*>(next_[n].Acquire_Load());
      }
      void SetNext(int n, Node* x) {
        assert(n >= 0);
        // Use a 'release store' so that anybody who reads through this
        // pointer observes a fully initialized version of the inserted node.
        next_[n].Release_Store(x);
      }
  
      // No-barrier variants that can be safely used in a few locations.
      Node* NoBarrier_Next(int n) {
        assert(n >= 0);
        return reinterpret_cast<Node*>(next_[n].NoBarrier_Load());
      }
      void NoBarrier_SetNext(int n, Node* x) {
        assert(n >= 0);
        next_[n].NoBarrier_Store(x);
      }
  
     private:
      // Array of length equal to the node height.  next_[0] is lowest level link.
      port::AtomicPointer next_[1];
    };
  

  这里使用一个Node节点表示所有相同key，不同高度的节点集合，仅保留了key和不同高度的向右指针，并且使用NewNode来动态分配随即高度的向右指针集合，而next_就指向这指针集合。这也是c/c++ tricky的地方。

    #include <stdio.h>
    struct Node {
    	char str[1];
    };
    int main() {
    	char* mem = new char[4];
    	for (int i = 0; i < 4; i++) {
    		mem[i] = i + '0';
    	}
    	Node* node = (Node*)mem;
    	char* const pstr = node->str;
    	for (int i = 0; i < 4; i++) {
    		printf("%c", pstr[i]);
    	}
    	return 0;
    }
  

  就像上面这个简单的sample，成员str可以作为指针指向从数组下标0开始的元素，并且不受申明时的限制，不局限于大小1，索引至分配的最大的内存地址。

• 简易随机数生成

    uint32_t Next() {
        static const uint32_t M = 2147483647L;   // 2^31-1
        static const uint64_t A = 16807;  // bits 14, 8, 7, 5, 2, 1, 0
        // We are computing
        //       seed_ = (seed_ * A) % M,    where M = 2^31-1
        //
        // seed_ must not be zero or M, or else all subsequent computed values
        // will be zero or M respectively.  For all other values, seed_ will end
        // up cycling through every number in [1,M-1]
        uint64_t product = seed_ * A;
  
        // Compute (product % M) using the fact that ((x << 31) % M) == x.
        seed_ = static_cast<uint32_t>((product >> 31) + (product & M));
        // The first reduction may overflow by 1 bit, so we may need to
        // repeat.  mod == M is not possible; using > allows the faster
        // sign-bit-based test.
        if (seed_ > M) {
          seed_ -= M;
        }
        return seed_;
    }
  

  可以看到，他使用A和M对种子进行运算，达到一定数据范围内不会重复的数集，而里面对于(product % M)，使用(product >> 31) + (product & M)进行运算优化，考虑右移和与操作的代价远小于取余操作。

• 简洁清晰的私有帮助方法，帮助寻找小于指定key的节点

    template<typename Key, class Comparator>
    typename SkipList<Key,Comparator>::Node*
    SkipList<Key,Comparator>::FindLessThan(const Key& key) const {
      Node* x = head_;
      int level = GetMaxHeight() - 1;
      while (true) {
        assert(x == head_ || compare_(x->key, key) < 0);
        Node* next = x->Next(level);
        if (next == NULL || compare_(next->key, key) >= 0) {
          if (level == 0) {
            return x;
          } else {
            // Switch to next list
            level--;
    	  }
        } else {
          x = next;
        }
      }
    }