Leetcode 146 LRU Cache

最新推荐文章于 2022-06-19 18:56:24 发布

pessis1

最新推荐文章于 2022-06-19 18:56:24 发布

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本文介绍了一种使用双向链表实现的LRU缓存机制。该机制支持get和put操作，并确保在缓存满时移除最久未使用的项。文章提供了完整的Java代码示例。

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Design and implement a data structure for Least Recently Used (LRU) cache. It should support the following operations: get and put.

get(key) - Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1.
put(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.

Follow up:
Could you do both operations in O(1) time complexity?

cache的问题，和在15213里面写过的cache 和 malloc类似。

基本思想在于用双向链表来进行LRU的操作。

public class LRUCache {
    
    
    private class Node{
        int key;
        int value;
        Node prev;
        Node next;
        
        
        public Node(int key, int value){
            this.key = key;
            this.value = value;
        }
        
        
    }
    
    
    Node head;
    Node tail;
    int capacity;
    int size;
    Map<Integer, Node> map;
    public LRUCache(int capacity) {
        head = new Node(0,0);
        head.next = tail;
        
        tail = new Node(0,0);
        tail.prev = head;
        this.capacity = capacity;
        size = 0;
        map = new HashMap<>(capacity);
    }
    
    public int get(int key) {
        if(map.containsKey(key)){
            Node tmp = map.get(key);
           
            tmp.prev.next = tmp.next;
            tmp.next.prev = tmp.prev;
            tail.prev.next = tmp;
            tmp.prev = tail.prev;
            tmp.next = tail;
            tail.prev = tmp;
            return tmp.value;
        }else{
            return -1;
        }
    }
    
    public void put(int key, int value) {
        if(!map.containsKey(key)){
            if(size == capacity){
                int tmpkey = head.next.key;
                head.next = head.next.next;
                head.next.prev = head;
                map.remove(tmpkey);
                size--;
            }
            Node tmp = new Node(key,value);
            map.put(key,tmp);
            tail.prev.next = tmp;
            tmp.prev = tail.prev;
            tmp.next = tail;
            tail.prev = tmp;
            size++;
        }else{
            Node tmp = map.get(key);
            tmp.value = value;
            tmp.prev.next = tmp.next;
            tmp.next.prev = tmp.prev;
            tail.prev.next = tmp;
            tmp.prev = tail.prev;
            tmp.next = tail;
            tail.prev = tmp;
            
        }
    }
}

/**
 * Your LRUCache object will be instantiated and called as such:
 * LRUCache obj = new LRUCache(capacity);
 * int param_1 = obj.get(key);
 * obj.put(key,value);
 */