tansuo 2014-03-24
LRU是Least Recently Used的缩写,意思是最近最少使用,它是一种Cache替换算法。
实现思路: hashtable + 双向链表
时间复杂度: 插入,查找,删除:O(1)
空间使用情况: O(N) :一个链表存储K个数据(stl的hash_map实际占的空间比较大).
运行环境:
Linux:RedHat , Fedora ,CentOS等(理论上Ubuntu , debian,mac os等也可以运行)
代码:
#ifndef __LRUCACHE_H__
#define __LRUCACHE_H__
#include <vector>
#include <ext/hash_map>
#include <pthread.h>
#include <assert.h>
using namespace __gnu_cxx;
template <class K, class D>
struct Node{
K key;
D data;
Node *prev, *next;
};
template <class K, class D>
class LRUCache{
public:
LRUCache(size_t size , bool is_pthread_safe = false){
if(size <= 0)
size = 1024;
pthread_safe = is_pthread_safe;
if(pthread_safe)
pthread_mutex_init(&cached_mutex , NULL);
entries = new Node<K,D>[size];
for(size_t i = 0; i < size; ++i)
cached_entries.push_back(entries + i);
head = new Node<K,D>;
tail = new Node<K,D>;
head->prev = NULL;
head->next = tail;
tail->prev = head;
tail->next = NULL;
}
~LRUCache(){
if(pthread_safe)
pthread_mutex_destroy(&cached_mutex);
delete head;
delete tail;
delete[] entries;
}
void Put(K key, D data);
D Get(K key);
private:
void cached_lock(void){
if(pthread_safe)
pthread_mutex_lock(&cached_mutex);
}
void cached_unlock(void){
if(pthread_safe)
pthread_mutex_unlock(&cached_mutex);
}
void detach(Node<K,D>* node){
node->prev->next = node->next;
node->next->prev = node->prev;
}
void attach(Node<K,D>* node){
node->prev = head;
node->next = head->next;
head->next = node;
node->next->prev = node;
}
private:
hash_map<K, Node<K,D>* > cached_map;
vector<Node<K,D>* > cached_entries;
Node<K,D> * head, *tail;
Node<K,D> * entries;
bool pthread_safe;
pthread_mutex_t cached_mutex;
};
template<class K , class D>
void LRUCache<K,D>::Put(K key , D data){
cached_lock();
Node<K,D> *node = cached_map[key];
if(node){
detach(node);
node->data = data;
attach(node);
}
else{
if(cached_entries.empty()){
node = tail->prev;
detach(node);
cached_map.erase(node->key);
}
else{
node = cached_entries.back();
cached_entries.pop_back();
}
node->key = key;
node->data = data;
cached_map[key] = node;
attach(node);
}
cached_unlock();
}
template<class K , class D>
D LRUCache<K,D>::Get(K key){
cached_lock();
Node<K,D> *node = cached_map[key];
if(node){
detach(node);
attach(node);
cached_unlock();
return node->data;
}
else{
cached_unlock();
return D();
}
}
#endif
测试用例:
/*
Compile:
g++ -o app app.cpp LRUCache.cpp -lpthread
Run:
./app
*/
#include <iostream>
#include <string>
#include "LRUCache.h"
using namespace std;
int
main(void){
//int k = 10 ,
// max = 100;
int k = 100000 ,
max = 1000000;
LRUCache<int , int> * lru_cache = new LRUCache<int , int>(k , true);
int tmp = 0;
for(int i = 0 ; i < 2*k ; ++i){
tmp = rand() % max;
lru_cache->Put(tmp, tmp + 1000000);
cout<<tmp<<endl;
}
for(int i = 0 ; i < k ; ++i){
tmp = rand() % max;
if(lru_cache->Get(tmp) == 0)
cout<<"miss : "<<tmp<<endl;
else
cout<<"hit : "<<tmp<<" value : "<<lru_cache->Get(tmp)<<endl;
}
delete lru_cache;
return 0;
}
其实,上面的代码,有一些毛病的。改天我会继续改进。
例如:
1:冗余操作。cached_entries完全可以用一个counter代替。
2:过度抽象。
3:Get、Put的interface不合理。如果真的去实现一个磁盘block的LRU cache,就会发现之前的接口需要重写了。
不过对于大家理解LRU算法。应该有一定的帮助的。