LRU Cache实现

 最近在看Leveldb源码，里面用到LRU（Least Recently Used）缓存，所以自己动手来实现一下。LRU Cache通常实现方式为Hash Map + Double Linked List，我使用std::map来代替哈希表。

实现代码如下：

#include <iostream>
#include <map>
#include <assert.h>

using namespace std;

// define double linked list node
template<class K, class V>
struct Node{
	K key;
	V value;
	Node *pre_node;
	Node *nxt_node;
	Node() : key(K()), value(V()), pre_node(0), nxt_node(0){}
};

// define LRU cache.
template<class K, class V>
class LRUCache{
public:
	typedef Node<K, V> CacheNode;
	typedef map<K, CacheNode*> HashTable;

	LRUCache(const int size) : capacity(size), count(0), head(0), tail(0){
		head = new CacheNode;
		tail = new CacheNode;
		head->nxt_node = tail;
		tail->pre_node = head;
	}
	~LRUCache(){
		HashTable::iterator itr = key_node_map.begin();
		for (itr; itr != key_node_map.end(); ++itr)
			delete itr->second;
		delete head;
		delete tail;
	}

	void put(const K &key, const V &value){
		// check if key already exist.
		HashTable::const_iterator itr = key_node_map.find(key);
		if (itr == key_node_map.end()){
			CacheNode *node = new CacheNode;
			node->key = key;
			node->value = value;		
			if (count == capacity)
			{
				CacheNode *tail_node = tail->pre_node;
				extricateTheNode(tail_node);
				key_node_map.erase(tail_node->key);
				delete tail_node;
				count--;
			}

			key_node_map[key] = node;
			count++;
			moveToHead(node);
		}
		else{
			itr->second->value = value;
			extricateTheNode(itr->second);
			moveToHead(itr->second);
		}
	}

	V get(const K &key){
		// check if key already exist.
		HashTable::const_iterator itr = key_node_map.find(key);
		if (itr == key_node_map.end()){
			return V();
		}
		else{
			extricateTheNode(itr->second);
			moveToHead(itr->second);
			return itr->second->value;
		}
	}

	void print(){
		if (count == 0)
			cout << "Empty cache." << endl;

		cout << "Cache information:" << endl;
		cout << "  " << "capacity: " << capacity << endl;
		cout << "  " << "count: " << count << endl;
		cout << "  " << "map size: " << key_node_map.size() << endl;
		cout << "  " << "keys: ";
		CacheNode *node = head;
		while (node->nxt_node != tail)
		{
			cout << node->nxt_node->key << ",";
			node = node->nxt_node;
		}
		cout << endl;
	}

private:
	void moveToHead(CacheNode *node){
		assert(head);
		node->pre_node = head;
		node->nxt_node = head->nxt_node;
		head->nxt_node->pre_node = node;
		head->nxt_node = node;
	}
	void extricateTheNode(CacheNode *node){ // evict the node from the list.
		assert(node != head && node != tail);
		node->pre_node->nxt_node = node->nxt_node;
		node->nxt_node->pre_node = node->pre_node;
	}

private:
	int capacity;
	int count;
	Node<K, V> *head;
	Node<K, V> *tail;
	HashTable key_node_map;
};

int main()
{
	LRUCache<int, int> my_cache(4);
	
	for (int i = 0; i < 20; ++i)
	{
		int key = rand() % 10 + 1;
		int value = key * 2;
		cout << "Put[" << key << "," << value << "]>>>" << endl;
		my_cache.put(key, value);
		my_cache.print();
	}
	
	for (int i = 0; i < 20; ++i)
	{
		int key = rand() % 10 + 1;
		int value = my_cache.get(key);
		cout << "Get value of " << key << ": " << value << ".>>>" << endl;
		my_cache.print();
	}

	return 0;
}

 

转载于:https://www.cnblogs.com/pbendan/p/5573645.html