146. LRU Cache (Hard)

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

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?

Example:

LRUCache cache = new LRUCache( 2 /* capacity */ );

cache.put(1, 1);
cache.put(2, 2);
cache.get(1);       // returns 1
cache.put(3, 3);    // evicts key 2
cache.get(2);       // returns -1 (not found)
cache.put(4, 4);    // evicts key 1
cache.get(1);       // returns -1 (not found)
cache.get(3);       // returns 3
cache.get(4);       // returns 4

Solution 1: HashMap + Doubly LinkedList O(1); O(n) n is capacity of LRU

    /**
     * HashMap + Doubly LinkedList
     * Build a HashMap between Node’s key and Node, the size is capacity of LRU.
     * Create a dummy head and tail in Doubly LinkedList to mark the boundary, 
     * so that we don't need to check the NULL node during the update.
     * For operation get, get node from HashMap according to key and move node to head.
     * For operation put, if key exists in HashMap, update the value of node. Otherwise, 
     * create a new node and add it to HashMap and Doubly LinkedList. If the size of HashMap reaches its capacity, 
     * remove the last node.
     */
    class Node {
        int key;
        int val;
        Node pre;
        Node next;

        Node(int key, int val) {
            this.key = key;
            this.val = val;
        }
    }

    private void addNode(Node node) {
        node.pre = head;
        node.next = head.next;
        head.next.pre = node; //不能和下面的交换
        head.next = node;
    }

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

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

    int capacity;
    Map<Integer, Node> cache;
    Node head;
    Node tail;

    public LRUCache(int capacity) {
        this.capacity = capacity;
        cache = new HashMap<>();
        head = new Node(-1, -1);
        tail = new Node(-1, -1);
        head.next = tail;
        tail.pre = head;
    }

    public int get(int key) {
        if (!cache.containsKey(key)) {
            return -1;
        }

        Node node = cache.get(key);
        moveToHead(node);
        return node.val;
    }

    public void put(int key, int value) {
        if (cache.containsKey(key)) {
            Node node = cache.get(key);
            node.val = value;
            moveToHead(node);
        } else {
            Node newNode = new Node(key, value);
            addNode(newNode);
            cache.put(key, newNode);
            if (cache.size() > capacity) {
                Node last = tail.pre;
                removeNode(last);
                cache.remove(last.key);
            }
        }
    }