LeetCode OJ:LRU Cache

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LRU Cache

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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.

算法思想：

LRU算法自不必多说，我这里是想自己写写实现下hashmap和双端循环队列，所以代码比较烦，如果用STL模板库就方便多了

思想就是：利用双端循环队列处理新元素的增加及快速删除，因为头结点的next指针指向的就是最早进入队列的元素，即要删除的元素，head结点的pre指针指向的是最新加入的元素；

利用hashmap能迅速找到队列中的节点，然后将该节点加入到队尾

#define MAX 10000#define MOD 9991struct node{int key;int val;node *pre;node *next;node(int k,int v):key(k),val(v),pre(this),next(this){}};class DQueue{node *head;int Size;node *Hash[MAX][20];int len[MAX];int _hash(int key){return key%MOD;}node * search(int key){int pos=_hash(key);for(int i=0;i<len[pos];i++){if(key==Hash[pos][i]->key){node *t=Hash[pos][i];t->pre->next=t->next;t->next->pre=t->pre;t->pre=head->pre;head->pre->next=t;t->next=head;head->pre=t;return t;}}return NULL;}public:DQueue(){head=new node(0,0);memset(len,0,sizeof(len));Size=0;}int insert(int key,int val){node *i=search(key);if(i!=NULL){i->val=val;return 1;}node *t=new node(key,val);t->next=head;t->pre=head->pre;head->pre->next=t;head->pre=t;int pos=_hash(key);Hash[pos][len[pos]++]=t;Size++;return 1;}int delHead(){node *p=head->next;head->next=p->next;p->next->pre=head;delete[] p;Size--;return 1;}int find(int key){node *f=search(key);if(f!=NULL)return f->val;return -1;}int size(){return Size;}};class LRUCache{DQueue *dq;int capa;public:LRUCache(int capacity){capa=capacity;dq=new DQueue();}int get(int key){return dq->find(key);}void set(int key,int value){dq->insert(key,value);if(dq->size()>capa){dq->delHead();}}};

answer2

//时间复杂度O(logn)，空间复杂度O(n)class LRUCache{    struct CacheNode{        int key;        int val;        CacheNode(int k,int v):key(k),val(v){}    };public:    LRUCache(int capacity) {        this->capacity=capacity;    }        int get(int key) {        if(cacheMap.find(key) == cacheMap.end())return -1;                //把当前访问结点移到表头，并更新map        cacheList.splice(cacheList.begin(),cacheList,cacheMap[key]);        cacheMap[key] = cacheList.begin();        return cacheMap[key]->val;    }        void set(int key, int value) {        if(cacheMap.find(key) == cacheMap.end()){            if(cacheList.size() == capacity){                cacheMap.erase(cacheList.back().key);                cacheList.pop_back();            }            cacheList.push_front(CacheNode(key,value));            cacheMap[key]=cacheList.begin();        }        else{            cacheMap[key]->val=value;            cacheList.splice(cacheList.begin(),cacheList,cacheMap[key]);            cacheMap[key] = cacheList.begin();        }    }private:    list<CacheNode> cacheList;    unordered_map<int,list<CacheNode>::iterator> cacheMap;    int capacity;};

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