146. LRU Cache

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

这里要删除的，是最久远没有操作过的数，统计访问次数的方法最坏结果是O(n)，所以要用双向链表才能设计出O(1)的解法。设计一个node，包含key，value，pre，和next。每次操作时，把这个node放在最前面；超过容量的时候，删除尾巴的节点。为了准确根据key定位node，还需要建立一个key和node的map。代码如下：

public class LRUCache {    class LRUNode {        int key, value;        LRUNode pre, next;        public LRUNode(int _key, int _value) {            key = _key; value = _value;        }    }        HashMap<Integer, LRUNode> map;    LRUNode head, tail;    int capacity;    public LRUCache(int capacity) {        map = new HashMap<Integer, LRUNode>();        head = new LRUNode(0, 0);        tail = new LRUNode(0, 0);        head.next = tail;        tail.pre = head;        this.capacity = capacity;    }        private void addToHead(LRUNode node) {        node.pre = head;        node.next = head.next;        head.next.pre = node;        head.next = node;    }        private void deleteNode(LRUNode node) {        node.pre.next = node.next;        node.next.pre = node.pre;    }        public int get(int key) {        if (map.containsKey(key)) {            LRUNode node = map.get(key);            int result = node.value;            deleteNode(node);            addToHead(node);            return result;        }        return -1;    }        public void put(int key, int value) {        if (map.containsKey(key)) {            LRUNode node = map.get(key);            node.value = value;            deleteNode(node);            addToHead(node);        } else {            LRUNode node = new LRUNode(key, value);            map.put(key, node);            addToHead(node);            if (map.size() > capacity) {                int nodeKey = tail.pre.key;                deleteNode(tail.pre);                map.remove(nodeKey);            }        }    }}/** * 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); */

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