LeetCode: LRU Cache [146]

时间:2023-03-09 02:09:50
LeetCode: LRU Cache [146]

【题目】

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.

【题意】

实现LRU策略

1. 依据key取value

2. 插入key-value时,须要删除LRU的item

【思路】

维护一个Map记录相应的<key, value>对

        为了模拟key的訪问先后关系,须要维护一个訪问次序列表,越靠后的节点,訪问时间距当前时间越短

而在insert或者訪问key的时候,须要从列表中找到相应的key,并把它调整到列表为。

这里遇到两个问题,一个是查找,还有一个是移动到末尾



假设使用顺序表,查找O(n),移动O(n),在cache规模非常大时时间代价过高

因此这里使用双向链表来处理

【代码】

struct Node{
int key;
int val;
Node*prev;
Node*next;
Node(int k, int v): key(k), val(v){
prev=NULL; next=NULL;
}
}; class LRUCache{
private:
Node* head;
Node* tail;
int capacity;
map<int, Node*>cache;
public:
LRUCache(int capacity) {
this->head = NULL;
this->tail = NULL;
this->capacity = capacity;
} void move2tail(Node* node){
if(node==tail)return;
if(node==head){
head = node->next;
head->prev=NULL;
tail->next=node;
node->prev=tail;
tail=node;
tail->next=NULL;
}
else{
node->prev->next = node->next;
node->next->prev = node->prev;
tail->next=node;
node->prev=tail;
tail=node;
tail->next=NULL;
}
} int get(int key) {
if(this->cache.find(key)==this->cache.end())return -1;
move2tail(this->cache[key]);
return this->cache[key]->val;
} void set(int key, int value) {
if(this->cache.find(key)==this->cache.end()){//cache中还没有
if(this->capacity==0){//cache已经满了
//删除头结点
this->cache.erase(head->key);
head=head->next;
if(head)head->prev=NULL;
else tail=NULL;
}
else{//cache还没满
this->capacity--;
}
//加入新节点
Node* newNode=new Node(key, value);
this->cache[key]=newNode;
if(tail){
tail->next=newNode;
newNode->prev=tail;
tail=newNode;
tail->next=NULL;
}
else{
head=tail=newNode;
}
}
else{//cache中已经有了
this->cache[key]->val = value;
move2tail(this->cache[key]);
}
}
};