Cache目的

为了加快查找速度，leveldb采用Cache的方式

基本原理

leveldb中默认实现的Cache是LRU Cache(最近最少使用)。

LRU Cache

1. 新数据插入到链表头部；
2. 每当缓存命中（即缓存数据被访问），则将数据移到链表头部；
3. 当链表满的时候，将链表尾部的数据丢弃。

具体实现

先上代码

// A single shard of sharded cache.
class LRUCache {
 public:
  LRUCache();
  ~LRUCache();

  // Separate from constructor so caller can easily make an array of LRUCache
  void SetCapacity(size_t capacity) { capacity_ = capacity; }

  // Like Cache methods, but with an extra "hash" parameter.
  Cache::Handle* Insert(const Slice& key, uint32_t hash,
                        void* value, size_t charge,
                        void (*deleter)(const Slice& key, void* value));
  Cache::Handle* Lookup(const Slice& key, uint32_t hash);
  void Release(Cache::Handle* handle);
  void Erase(const Slice& key, uint32_t hash);
  void Prune();
  size_t TotalCharge() const {
    MutexLock l(&mutex_);
    return usage_;
  }

 private:
  void LRU_Remove(LRUHandle* e);
  void LRU_Append(LRUHandle*list, LRUHandle* e);
  void Ref(LRUHandle* e);
  void Unref(LRUHandle* e);
  bool FinishErase(LRUHandle* e);

  // Initialized before use.
  size_t capacity_;

  // mutex_ protects the following state.
  mutable port::Mutex mutex_;
  size_t usage_;

  // Dummy head of LRU list.
  // lru.prev is newest entry, lru.next is oldest entry.
  // Entries have refs==1 and in_cache==true.
  LRUHandle lru_;

  // Dummy head of in-use list.
  // Entries are in use by clients, and have refs >= 2 and in_cache==true.
  LRUHandle in_use_;

  HandleTable table_;
};

这里需要注意的几点是，leveldb对基本方法进行了一些改进，采用了两个链表，
lru_：包含哪些不是正在被使用的数据（已按照最近使用时间排序）
in_use_：包含正在被使用的数据（未排序）

数据的结构

// An entry is a variable length heap-allocated structure.  Entries
// are kept in a circular doubly linked list ordered by access time.
struct LRUHandle {
  void* value;
  void (*deleter)(const Slice&, void* value);
  LRUHandle* next_hash;
  LRUHandle* next;
  LRUHandle* prev;
  size_t charge;      // TODO(opt): Only allow uint32_t?
  size_t key_length;
  bool in_cache;      // Whether entry is in the cache.
  uint32_t refs;      // References, including cache reference, if present.
  uint32_t hash;      // Hash of key(); used for fast sharding and comparisons
  char key_data[1];   // Beginning of key

  Slice key() const {
    // For cheaper lookups, we allow a temporary Handle object
    // to store a pointer to a key in "value".
    if (next == this) {
      return *(reinterpret_cast<Slice*>(value));
    } else {
      return Slice(key_data, key_length);
    }
  }
};

数据自身带有一个refs标志，当其值为0，表示不在cache中，值为1，表示在lru_链表中，当值大于1时，表示在in_use_的链表中，且其值减一表示正在使用这个数据的cliens的个数。

1. 当新数据进入Cache时，首先初始化数据

Cache::Handle* LRUCache::Insert(
    const Slice& key, uint32_t hash, void* value, size_t charge,
    void (*deleter)(const Slice& key, void* value)) {
  MutexLock l(&mutex_);

  LRUHandle* e = reinterpret_cast<LRUHandle*>(
      malloc(sizeof(LRUHandle)-1 + key.size()));
  e->value = value;
  e->deleter = deleter;
  e->charge = charge;
  e->key_length = key.size();
  e->hash = hash;
  e->in_cache = false;
  e->refs = 1;  // for the returned handle.
  memcpy(e->key_data, key.data(), key.size());

将数据加入in_use_的链表中

  if (capacity_ > 0) {
    e->refs++;  // for the cache's reference.
    e->in_cache = true;
    LRU_Append(&in_use_, e);
    usage_ += charge;
    FinishErase(table_.Insert(e));
  } // else don't cache.  (Tests use capacity_==0 to turn off caching.)

如果Cache满了则将lru_中的老数据移除

  while (usage_ > capacity_ && lru_.next != &lru_) {
    LRUHandle* old = lru_.next;
    assert(old->refs == 1);
    bool erased = FinishErase(table_.Remove(old->key(), old->hash));
    if (!erased) {  // to avoid unused variable when compiled NDEBUG
      assert(erased);
    }
  }

  return reinterpret_cast<Cache::Handle*>(e);
}

其余函数基本就是一些简单的链表操作，没什么好说的，其实注释很详细的😄

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