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.
思路:LRU这里涉及是用向量记录内存地址,使用Map映射key和相应Key在向量中的映射,最前面的永远都是最新的,如果内存没有使用完,使用新的内存,如果使用完了,从第一个内存更新,然后将第一块内存放到最后一块中,需要注意的是这里需要map的信息。
class LRUCache{
public:
LRUCache(int capacity) {
m_capacity=capacity;
m_size =0;
for(int i=0;i<capacity;i++)
{
int* temp = (int*)malloc(sizeof(int));
*temp =0;
m_cache.push_back(temp);
}
}
int get(int key) {
map<int,int>::iterator itr=m_hash.find(key);
if(itr == m_hash.end())
return -1;
else
return *(m_cache[itr->second]);
}
void set(int key, int value) {
map<int,int>::iterator itr=m_hash.find(key);
map<int,int>::iterator index;
if(itr == m_hash.end()) //没有找到
{
if(m_size < m_capacity)
{
*m_cache[m_size] = value;
m_hash.insert(pair<int,int>(key,m_size));
m_size++;
}
else
{
for(index=m_hash.begin();index!=m_hash.end();index++)
if(index->second ==0)
itr = index;
else
index->second--;
m_hash.erase(itr);
int* temp = m_cache[0];
m_cache.erase(m_cache.begin());
*temp = value;
m_cache.push_back(temp);
m_hash.insert(pair<int,int>(key,m_cache.size()-1));
}
}
else
{
int* temp = m_cache[itr->second];
*m_cache[itr->second] = value;
m_cache.erase(m_cache.begin()+itr->second);
m_cache.push_back(temp);
for(index=m_hash.begin();index != m_hash.end();index++)
if(index->second > itr->second)
index->second--;
itr->second = m_cache.size()-1;
}
}
~LRUCache()
{
for(int i=0;i<m_capacity;i++)
free(m_cache[i]);
}
private:
int m_capacity;
int m_size;
vector<int*> m_cache;
map<int,int> m_hash;
};原文:http://blog.csdn.net/yusiguyuan/article/details/45039255