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146. LRU Cache - Hard

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?

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

 

HashMap + Double LinkedList

首先定義一個Node類,用來構建double linked list,包括key, val, next, prev。兩個引數count, capacity,count用來給cache裡的元素計數。LRUcache初始化的時候,還要定義兩個dummy Node,head和tail,方便取和放連結串列首(head.next)、尾(tail.prev)的元素。

get:如果map中存在該key,從map中取出node,儲存這個node對應的value,在連結串列中刪掉這個節點,再把這個節點插入到連結串列頭部。如果map中不存在該key,返回-1。

put:根據map中有無該key,分兩種情況

1. map中無key。根據新的(key, value)新建一個node,把node放進map裡。如果沒有超過容量,把當前node放到double linked list的頭部,並且count增加1;如果超過容量,刪除連結串列尾部的節點(注意除了連結串列裡,map裡也要刪除!),並把當前node插入到頭部。

2. map中有key。從map中取出node,並賦值為當前value,在連結串列中刪掉這個節點,再把這個節點插入到連結串列頭部。

刪除節點 和 把節點插入到連結串列頭部 可以用兩個輔助函式來表示。

時間:O(1),空間:O(N)

class LRUCache {
    class Node {
        int key, val;
        Node next, prev;
        public Node(int key, int val) {
            this.key = key;
            this.val = val;
        }
    }
    HashMap<Integer, Node> map;
    Node head, tail;
    int count, capacity;

    public LRUCache(int capacity) {
        this.capacity = capacity;
        count = 0;
        map = new HashMap<>();
        head = new Node(0, 0);
        tail = new Node(0, 0);
        head.next = tail;
        head.prev = null;
        tail.next = null;
        tail.prev = head;
    }
    
    private void deleteNode(Node node) {
        node.prev.next = node.next;
        node.next.prev = node.prev;
    }
    
    private void addToHead(Node node) {
        head.next.prev = node;
        node.next = head.next;
        head.next = node;
        node.prev = head;
    }
    
    public int get(int key) {
        if(map.containsKey(key)) {
            Node node = map.get(key);
            int val = node.val;
            deleteNode(node);
            addToHead(node);
            return val;
        }
        return -1;
    }
    
    public void put(int key, int value) {
        if(map.containsKey(key)) {
            Node node = map.get(key);
            node.val = value;
            deleteNode(node);
            addToHead(node);
        } else {
            Node node = new Node(key, value);
            map.put(key, node);
            if(count < capacity) {
                addToHead(node);
                count++;
            } else {
                map.remove(tail.prev.key);
                deleteNode(tail.prev);
                addToHead(node);
            }
        }
    }
}

/**
 * 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);
 */