Leetcode 146. LRU Cache

最新推荐文章于 2020-03-23 10:24:44 发布

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本文介绍了一种使用双向链表和哈希映射实现的LRU(Least Recently Used)缓存机制。该机制能够在O(1)的时间复杂度内完成获取和设置操作。文章详细解释了LRU缓存类的定义、节点结构、初始化过程以及get和put方法的具体实现。

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public class LRUCache {
    // double linked list
    private class Node {
        Node prev;
        Node next;
        int key;
        int value;
        
        public Node (int key, int value) {
            this.key = key;
            this.value = value;
            this.prev = null;
            this.next = null;
        }
    }
    
    private int capacity;
    private HashMap<Integer, Node> map = new HashMap<Integer, Node>();
    private Node head = new Node(-1, -1);
    private Node tail = new Node(-1, -1);
    
    public LRUCache(int capacity) {
        this.capacity = capacity;
        tail.prev = head;
        head.next = tail;
    }
    
    public int get(int key) {
        if (!map.containsKey(key)) {
            return -1;
        }
        
        // delete current node from the list and move it to tail
        Node curr = map.get(key);
        curr.prev.next = curr.next;
        curr.next.prev = curr.prev;
        
        moveToTail(curr);
        
        return map.get(key).value;
    }
    
    public void put(int key, int value) {
        if (get(key) != -1) {
            map.get(key).value = value;
            return;
        }
        
        // remove least recently used node
        if (map.size() == capacity) {
            map.remove(head.next.key);      
            head.next = head.next.next;
            head.next.prev = head;
        }
        
        // insert new node to the tail
        Node newNode = new Node(key, value);
        map.put(key, newNode);
        moveToTail(newNode);
    }
    
    public void moveToTail(Node curr) {
        curr.prev = tail.prev;
        tail.prev = curr;
        curr.prev.next = curr;
        curr.next = tail;
    }
}