LeetCode 146. LRU缓存机制 （LRU缓存详解看这一篇就够了）

输入
["LRUCache", "put", "put", "get", "put", "get", "put", "get", "get", "get"]
[[2], [1, 1], [2, 2], [1], [3, 3], [2], [4, 4], [1], [3], [4]]
输出
[null, null, null, 1, null, -1, null, -1, 3, 4]

解释
LRUCache lRUCache = new LRUCache(2);
lRUCache.put(1, 1); // 缓存是 {1=1}
lRUCache.put(2, 2); // 缓存是 {1=1, 2=2}
lRUCache.get(1);    // 返回 1
lRUCache.put(3, 3); // 该操作会使得关键字 2 作废，缓存是 {1=1, 3=3}
lRUCache.get(2);    // 返回 -1 (未找到)
lRUCache.put(4, 4); // 该操作会使得关键字 1 作废，缓存是 {4=4, 3=3}
lRUCache.get(1);    // 返回 -1 (未找到)
lRUCache.get(3);    // 返回 3
lRUCache.get(4);    // 返回 4

class LRUCache {

    private int capacity;
    private HashMap<Integer, Node> map;
    private DoubleList cache;

    public LRUCache(int capacity) {
        this.capacity = capacity;
        map = new HashMap<>();
        cache = new DoubleList();
    }

    public int get(int key) {
        if (map.containsKey(key)) {
            Node node = map.get(key);
            cache.remove(node);
            cache.addLast(node);
            return node.val;
        } else {
            return -1;
        }
    }

    public void put(int key, int value) {
        if (map.containsKey(key)) {
            Node node = map.get(key);
            cache.remove(node);
            Node newNode = new Node(key, value);
            cache.addLast(newNode);
            map.put(key, newNode);
        } else {
            if (map.size() == capacity) {
                Node removeNode = cache.removeFirst();
                map.remove(removeNode.key);
            }
            Node newNode = new Node(key, value);
            cache.addLast(newNode);
            map.put(key, newNode);
        }
    }
}

// 定义双向链表的节点
class Node {
    public int key;
    public int val;
    public Node pre;
    public Node next;
    public Node(int key, int val) {
        this.key = key;
        this.val = val;
    }
}

// 定义双向链表
class DoubleList {
    private Node head;
    private Node tail;

    public DoubleList() {
        this.head = new Node(0, 0);
        this.tail = new Node(0, 0);
        head.next = tail;
        tail.pre = head;
    }

    public void addLast(Node node) {
        tail.pre.next = node;
        node.pre = tail.pre;
        node.next = tail;
        tail.pre = node;
    }

    public void remove(Node node) {
        node.pre.next = node.next;
        node.next.pre = node.pre;
    }

    public Node removeFirst() {
        Node removeNode = head.next;
        removeNode.pre.next = removeNode.next;
        removeNode.next.pre = removeNode.pre;
        return removeNode;
    }
}

/**
 * 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);
 */

class LRUCache {

    private int capacity;
    private LinkedHashMap<Integer, Integer> cache = new LinkedHashMap<>();
    public LRUCache(int capacity) {
        this.capacity = capacity;
    }
    
    public int get(int key) {
        Integer val = cache.remove(key);
        if (val != null) {
            cache.put(key, val);
            return val;
        } else {
           return -1;
        }
    }
    
    public void put(int key, int value) {
        Integer val = cache.remove(key);
        //当key在cache中的时候
        if (val != null) {
            cache.put(key, value);
            return;
        }
        // key 不在 cache 中，那么就把 key 插入 cache，插入前判断 cache 是否满了
        if (cache.size() >= capacity) {
            Integer oldestKey = cache.keySet().iterator().next();
            cache.remove(oldestKey);
        }
        cache.put(key, value);
    }
}

/**
 * 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);
 */