Question

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

Solution

  • Method 1: HashMap + Bidirectional list 
    class LRUCache {
    private int capacity;
    private Map<Integer, DequeNode> map;
    private DequeNode dummy;
    private DequeNode tail;
    private int size;
    private static class DequeNode{
        public int key;
        public int val;
        public DequeNode pre, next;
        public DequeNode(int key, int val){
            this.key = key;
            this.val = val;
        }
    }
    public LRUCache(int capacity) {
        this.capacity = capacity;
        this.map = new HashMap<>();
        this.size = 0;
        this.dummy = new DequeNode(-1, -1);        
    }

    private void insertHead(DequeNode cur){
        if(cur.pre != null){
            cur.pre.next = cur.next;    //remove current node from the list.
            if(cur.next != null)
                cur.next.pre = cur.pre;
        }
        DequeNode originalHead = dummy.next;    //insert current node to the head of the list.
        cur.pre = dummy;
        dummy.next = cur;
        cur.next = originalHead;
        if(originalHead != null){
            originalHead.pre = cur;
        }
    }

    public int get(int key) {
        if(!map.containsKey(key)) return -1;
        DequeNode cur = map.get(key);
        if(cur == tail && size != 1){
            this.tail = this.tail.pre;
            this.tail.next = null;
        }
        insertHead(cur);
        return cur.val;
    }

    public void put(int key, int value) {
        if(map.containsKey(key)){
            DequeNode cur = map.get(key);
            if(cur == tail && size != 1){
                tail = cur.pre;
            }
            cur.val = value;
            insertHead(cur);
        }else{
            DequeNode node = new DequeNode(key, value);
            this.map.put(key, node);
            if(size + 1 <= this.capacity){
                if(size + 1 == 1){
                    this.tail = node;
                }
                insertHead(node);
                size++;
            }else{
                // Need to remove the last node and insert current one.
                insertHead(node);
                DequeNode originalTail = this.tail;
                map.remove(originalTail.key);
                this.tail = this.tail.pre;
                this.tail.next = null;
            }
        }
    }
}

/**
 * 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);
 */