【leetcode刷题笔记】LRU Cache

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

get(key) - Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1.
set(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.

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题解：用双向链表实现一个LRU cache，这里自定义越靠近链表头的node，在越近的时间使用过。支持两个操作——get和set：

1. get(key)：如果链表中有key对应的node，返回该node的值，并把node移到链表头部（最近使用过）；如果没有，返回-1；
2. set(key,value)：如果链表中已经有key对应的node，修改对应node的值为value（但不需要把这个node放在头结点处）；如果链表中没有key对应的node，那么要新建node插入链表中，但此时要看链表是否还有空间。如果没有，就将尾部node（最少使用的node）删除，然后在头部插入新的node。

为了提高查找效率，这里使用一个hashMap存放<key,node>键值对，这样就可以在O(1)的时间判断cache中是否存在对应的key。

代码如下：

 1 public class LRUCache {

 2     private class Node{

 3         int value;

 4         int key;

 5         Node before;

 6         Node after;

 7         public Node(int key,int value){

 8             this.value = value;

 9             this.key = key;

10             before = null;

11             after = null;

12         }

13     }

14     

15     private int capacity;

16     private HashMap<Integer, Node> map = new HashMap<Integer,Node>();

17     private Node headNode = new Node(-1, -1);

18     private Node tailNode = new Node(-1, -1);

19     

20     public LRUCache(int capacity) {

21         this.capacity = capacity;

22         headNode.after = tailNode;

23         tailNode.before = headNode;

24     }

25     

26     public void move_to_head(Node current){

27         current.after = headNode.after;

28         headNode.after = current;

29         current.before = headNode;

30         current.after.before = current;

31     }

32     public int get(int key) {

33         //if we don't have this node

34         if(!map.containsKey(key))

35             return -1;

36         

37         //if we have this node, get it and move it to head

38         Node current = map.get(key);

39         current.before.after = current.after;

40         current.after.before = current.before;

41         move_to_head(current);

42         

43         return map.get(key).value;        

44     }

45     

46     public void set(int key, int value) {

47         //if we already have this node,just change its value

48         if(get(key) != -1){

49             map.get(key).value = value;

50             return;

51         }

52         

53         //if we indeed don't have this node, we first check capacity

54         if(map.size() == capacity){

55             map.remove(tailNode.before.key);

56             tailNode.before.before.after = tailNode;

57             tailNode.before = tailNode.before.before;

58         }

59         

60         //now we are sure we have space for this new node,put it ahead of the list

61         Node newNode = new Node(key, value);

62         map.put(key, newNode);

63         move_to_head(newNode);

64     }

65 }

在实现的时候，还设置了两个node：head和tail，真正的cache数据节点存放在二者之间。