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.
参考:http://www.cnblogs.com/TenosDoIt/p/3417157.html
题目大意:设计一个用于LRU cache算法的数据结构。 题目链接。关于LRU的基本知识可参考here
分析:为了保持cache的性能,使查找,插入,删除都有较高的性能,我们使用双向链表(std::list)和哈希表(std::unordered_map)作为cache的数据结构,因为:
具体实现细节:
C++实现代码:
#include<unordered_map> #include<list> #include<iostream> using namespace std; 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) { auto iter=cacheMap.find(key); if(iter!=cacheMap.end()) { cacheList.splice(cacheList.begin(),cacheList,iter->second); cacheMap[key]=cacheList.begin(); return cacheMap[key]->value; } return -1; } void set(int key, int value) { auto iter=cacheMap.find(key); if(iter!=cacheMap.end()) { cacheMap[key]->value=value; cacheList.splice(cacheList.begin(),cacheList,cacheMap[key]); cacheMap[key]=cacheList.begin(); } else { if(size==(int)cacheList.size()) { //记得要先删除map中的元素,然后再删除list中的地址,不然map中的地址无效,有可能指向后来插入的元素 cacheMap.erase(cacheList.back().key); cacheList.pop_back(); } cacheList.push_front(CacheNode(key,value)); cacheMap[key]=cacheList.begin(); } } private: int size; unordered_map<int,list<CacheNode>::iterator> cacheMap; list<CacheNode> cacheList; }; int main(){ LRUCache lru_cache(1); lru_cache.set(2,1); cout<<lru_cache.get(2)<<endl; lru_cache.set(3,2); cout<<lru_cache.get(2)<<endl; cout<<lru_cache.get(3)<<endl; }