LeetCode OJ：LRU Cache（最近使用缓存）

Design and implement a data structure for Least Recently Used (LRU) cache. It should support the following operations: get and set.

get(key) - Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1.
set(key, value) - Set or insert the value if the key is not already present. When the cache reached its capacity, it should invalidate the least recently used item before inserting a new item.

最近使用缓存的问题，看到key和value感觉可能就要使用map了。用一个list维护一个cache，然后map指向相应cache的每个节点。

注意这里的最近使用，不管是get还是set都属于最近使用的范畴，代码如下所示：

 1 class LRUCache{
 2 struct cacheNode{
 3     int key;
 4     int val;
 5     cacheNode(int k, int v):
 6     key(k), val(v){}
 7 };
 8 public:
 9     LRUCache(int capacity) {
10         size = capacity;
11     }
12
13     int get(int key) {
14         if(cacheMap.find(key) != cacheMap.end()){
15             auto it = cacheMap[key];
16             cacheList.splice(cacheList.begin(), cacheList, it);
17             cacheMap[key] = cacheList.begin();
18             return cacheList.begin()->val;
19         }else
20             return -1;
21     }
22
23     void set(int key, int value) {
24         if(cacheMap.find(key) != cacheMap.end()){//list中存在该元素
25             auto it = cacheMap[key];
26             cacheList.splice(cacheList.begin(), cacheList, it);
27             cacheMap[key] == cacheList.begin();
28             cacheList.begin()->val = value;
29         }else{                                  //list中不存在该元素
30             if(cacheList.size() == this->size){
31                 cacheMap.erase(cacheList.back().key);
32                 cacheList.pop_back();
33             }
34             cacheList.push_front(cacheNode(key, value));
35             cacheMap[key] = cacheList.begin();
36         }
37     }
38 private:
39     int size;
40     list<cacheNode> cacheList;
41     unordered_map<int , list<cacheNode>::iterator> cacheMap;
42 };