• [leetcode]LRU Cache


    做个LRU,算法挺简单的。。。

    而且好像用处也挺广的(?),用的比较广的一个cache算法

    比如我cache只有4这么大,现在有很多元素1,2,2,4,2,5,3

    cache                  income:1

    1

    cache                  income:2

    2 1

    cache                  income:1

    1 2

    cache                  income:4

    4 1 2

    cache                  income:2

    2 4 1

    cache                  income:5

    5 2 4 1

    cache                  income:3

    3 5 2 4

    大概就这么个样子。。。

    看出来了吧,新按元素使用率(?)排序,最后使用的放最前面

    如果cache不满,新来的放第一个,如果满了,在cache里面就把里面那个放到第一个,如果不在就删除最后一个,然后把新元素放第一个。

    ok,算法就说完了。。

    talk is cheap , show me the code...

    经常看到各种经典算法,感觉都很简单啊。。。

    当然这个确实也简单

    就是用一个双向链表+map

    不用map查找的话就要遍历了。。。时间复杂度就上升了

    双向链表的好处就是。。。用map定位到那个节点,然后很方便的移动或者删除啊什么的,单向就做不到啦,因为你要删除还要找prev

    双向链表就不写了,用stl的list代替

    struct CacheNode{
        int key;
        int value;
        CacheNode(int k , int v) : key(k) , value(v){}
    };
    class LRUCache{
    public:
        LRUCache(int capacity) {
            size = capacity;
        }
        
        int get(int key) {
            if(cacheMap.find(key) != cacheMap.end()){
               auto it = cacheMap[key];
               cacheList.splice(cacheList.begin() , cacheList , it);
               cacheMap[key] = cacheList.begin();
               return cacheList.begin()->value;
            }else{
                return -1;
            }
        }
        
        void set(int key, int value) {
            if (cacheMap.find(key) == cacheMap.end()){
                if(cacheList.size() == size){
                    cacheMap.erase(cacheList.back().key);
                    cacheList.pop_back();
                }
                cacheList.push_front(CacheNode(key , value));
                cacheMap[key] = cacheList.begin();
            }else{
               auto it = cacheMap[key];
               cacheList.splice(cacheList.begin() , cacheList , it);
               cacheMap[key] = cacheList.begin();
               cacheList.begin()->value = value;
            }
        }
    private:
        int size;
        list<CacheNode> cacheList;
        unordered_map<int , list<CacheNode>::iterator > cacheMap;
    };

     ===update 13/07/2014

    从新自己用双向链表实现了一次,虽然原理很简单,但是一些细节总是弄错T_T

    所以debug了1个小时,真是伤心。。。

    #include <iostream>
    #include <unordered_map>
    using namespace std;
    struct CacheNode {
        int key;
        int value;
        CacheNode* next;
        CacheNode* prev;
        CacheNode(int _key, int _value) {
            key = _key;
            value = _value;
            next = nullptr;
            prev = nullptr;
        }
    };
    class LRUCache{
    public:
        LRUCache(int capacity) {
            _capacity = capacity;
            head = new CacheNode(INT_MIN,-1);
            tail = head->next;
            len = 0;
        }
        
        int get(int key) {
         // cout << "start get" <<endl;
            auto found = cache.find(key);
            if (found != cache.end()) {
                if (found -> second == tail) {
                  tail = tail->prev;
                }
                insertToHead(found->second);
                if (tail == head) tail = head -> next;
                return found -> second -> value;
            }
            return -1;
        }
        
        void set(int key, int value) {
            //in cache
         //  cout << "Start  set key = " <<key<<", value="<<value <<endl;
            auto found = cache.find(key);
            if (found != cache.end()) {
      //        cout << "In cache" <<endl;
                found->second->value = value;
                if (found -> second == tail) {
                  tail = tail->prev;
                }
                insertToHead(found->second);
                if (tail == head) tail = head->next;
                return ;
            }
          //  cout << "Not in cache"<<endl;
            //not in cache
            //trace
       //     outCache(head);
            if (len == _capacity) {
                // cout << "full" <<endl;
                // cout << "Tail = " << tail <<" Tail->pre = "<< tail->prev << endl;
                CacheNode* tmp = tail -> prev;
                cache.erase(tail->key);
                deleteNodeLink(tail);
              //  cout << "delete done"<<endl;
          //      cout << tail->key << endl;
                delete tail;
                tail = tmp;
                insertToHead(new CacheNode(key, value));
                return ;
            }
            //not full
            insertToHead(new CacheNode(key, value));
            if (tail == nullptr) tail = head->next;
       //     cout << "Tail = " << tail <<endl;
            len++;
         //   cout << len << endl;
        }
    private:
       CacheNode* head;
       CacheNode* tail;
       int _capacity;
       int len;
       unordered_map<int, CacheNode*> cache;
       
       void deleteNodeLink(CacheNode* node) {
           CacheNode* prev = nullptr;
           CacheNode* next = nullptr;
           if (node -> prev) prev = node->prev;
           if (prev) {
               prev -> next = node -> next;
           }
           if(node->next) next = node -> next;
           if(next) {
               next -> prev = prev;
           }
       }
       
       void insertToHead(CacheNode* node) {
           deleteNodeLink(node);
           node->prev = head;
           node->next = head->next;
           if (head -> next) head->next->prev = node;
           head->next = node;
           cache[node->key] = node;
       }
       void outCache(CacheNode* root) {
        while(root) {
          cout << root->key << " ";
          root = root -> next;
        }
        cout << endl;
       }
    };
    int main() {
      LRUCache lru(1);
      lru.set(2,1);
      cout<<lru.get(2)<<endl;
      lru.set(3,2);
      cout<<lru.get(2)<<endl;
      cout<<lru.get(3)<<endl;
    }
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  • 原文地址:https://www.cnblogs.com/x1957/p/3485053.html
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