146 LRU Cache

Design a data structure that follows the constraints of a Least Recently Used (LRU) cache.

Implement the LRUCache class:

• LRUCache(int capacity) Initialize the LRU cache with positive size capacity.
• int get(int key) Return the value of the key if the key exists, otherwise return -1.
• void put(int key, int value) Update the value of the key if the key exists. Otherwise, add the key-value pair to the cache. If the number of keys exceeds the capacity from this operation, evict the least recently used key.

The functions get and put must each run in O(1) average time complexity.

Example 1:

Input
["LRUCache", "put", "put", "get", "put", "get", "put", "get", "get", "get"]
[[2], [1, 1], [2, 2], [1], [3, 3], [2], [4, 4], [1], [3], [4]]
Output
[null, null, null, 1, null, -1, null, -1, 3, 4]

Explanation
LRUCache lRUCache = new LRUCache(2);
lRUCache.put(1, 1); // cache is {1=1}
lRUCache.put(2, 2); // cache is {1=1, 2=2}
lRUCache.get(1);    // return 1
lRUCache.put(3, 3); // LRU key was 2, evicts key 2, cache is {1=1, 3=3}
lRUCache.get(2);    // returns -1 (not found)
lRUCache.put(4, 4); // LRU key was 1, evicts key 1, cache is {4=4, 3=3}
lRUCache.get(1);    // return -1 (not found)
lRUCache.get(3);    // return 3
lRUCache.get(4);    // return 4

Solution:

class LRUCache {
    static class Node{
        int key; 
        int value;
        Node next;
        Node prev;
        Node(int key, int value){
            this.key = key;
            this.value = value;
        }
    }

    private Map<Integer, Node> cache = new HashMap<Integer, Node>();
    private int size;
    private int capacity;
    private Node head;
    private Node tail;
    // 伪头部和伪尾部节点，用于方便地添加和删除节点

    public LRUCache(int capacity) {
        this.size = 0;
        this.capacity = capacity;

        // 初始化伪头部和伪尾部节点
        head = new Node(-1, -1);
        tail = new Node(-1, -1);
        head.next = tail;
        tail.prev = head;

    }

    public int get(int key) {
        Node node = cache.get(key);
        if (node == null){
            return -1;
        }

        // 将访问的节点移动到双向链表的头部
        moveToHead(node);
        return node.value;

    }

    public void put(int key, int value) {
        Node node = cache.get(key);
        if (node == null){
            // 如果键不存在，创建新的节点
            Node newNode = new Node(key, value);
            // 添加进哈希表
            cache.put(key, newNode);
             // 添加至双向链表的头部
            addToHead(newNode);
            size = size + 1;
            if (size > capacity){
                // 如果超过容量，删除双向链表的尾部节点
                Node tail = removeTail();
                cache.remove(tail.key);
                size = size - 1;
            }
        }else{
            node.value = value;
            moveToHead(node);
        }
    }

    private void addToHead(Node node){
        node.prev = head;
        node.next = head.next;
        head.next.prev = node;
        head.next = node;
    }

    private void removeNode(Node node){
        node.prev.next = node.next;
        node.next.prev = node.prev;
    }

    private void moveToHead(Node node){
        removeNode(node);
        addToHead(node);
    }

    private Node removeTail(){
        Node res = tail.prev;
        removeNode(res);
        return res;
    }
}

/**
 * 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);
 */

// TC: O(1)
// SC: O(1)