LeetCode:LRU Cache

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LRU Cache

Total Accepted: 76226 Total Submissions: 481333 Difficulty: Hard

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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Design

思路一：

题目要求实现“最近最少使用”缓存算法，这在Android中的图片缓存中有使用。

实现要求是，最近被访问（get,set）的放前后；最久被访问的放在最后，但容量不足时删除此结点。

实现方式：双链表 + HashMap

java code:

class Node {    int key,value;    Node pre,next;        public Node(int key, int value) {        this.key = key;        this.value = value;    }}public class LRUCache {        HashMap<Integer, Node> map;    int capicity;    int count;    Node head,tail;        // 设置一个头结点和一个尾结点，作为哨兵    public LRUCache(int capacity) {        this.capicity = capacity;        map = new HashMap<>();        head = new Node(0, 0);        tail = new Node(0, 0);                head.next = tail;        tail.pre = head;        head.pre = null;        tail.next = null;        count = 0;    }        // 删除结点    public void deleteNode(Node node) {        node.pre.next = node.next;        node.next.pre = node.pre;    }        // 添加，添加到head的下一个结点    public void addToHead(Node node) {        node.pre = head;        node.next = head.next;            head.next.pre = node;        head.next = node;    }        //     public int get(int key) {        if(map.get(key)!=null) {            Node node = map.get(key);            int result = node.value;            deleteNode(node);            addToHead(node);            return result;        }        return -1;    }        //     public void set(int key, int value) {        if(map.get(key)!=null) {            Node node = map.get(key);            node.value = value;            deleteNode(node);            addToHead(node);        }else{            Node node = new Node(key, value);            map.put(key, node);            if(count < capicity) {                count++;                addToHead(node);            }else{                map.remove(tail.pre.key);                deleteNode(tail.pre);                addToHead(node);            }        }    }}

思路二：

集合类中LinkedHashMap的实现方式就是：双链表 + HashMap，也是Android LRU Cache中实现使用数据结构，因此只需在LinkedHashMap的基础上添加容量限制即可。

java code:

public class LRUCache {    private Map<Integer, Integer> map;    public LRUCache(int capacity) {        map = new LinkedCappedHashMap<>(capacity);    }    public int get(int key) {        if(!map.containsKey(key)) { return -1; }        return map.get(key);    }    public void set(int key, int value) {        map.put(key,value);    }    private static class LinkedCappedHashMap<K,V> extends LinkedHashMap<K,V> {        int maximumCapacity;        LinkedCappedHashMap(int maximumCapacity) {            super(16, 0.75f, true);            this.maximumCapacity = maximumCapacity;        }        protected boolean removeEldestEntry(Map.Entry eldest) {            return size() > maximumCapacity;        }    }}

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