146. LRU Cache (Hard)

https://leetcode.com/problems/lru-cache/

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

Hints

Solutions

class LRUCache {
   public static class DLinkList {
        int key, value;
        DLinkList left;
        DLinkList right;

        DLinkList(int key, int value) {
            this.key = key;
            this.value = value;
            left = null;
            right = null;
        }
    }

    private Map<Integer, DLinkList> cache;
    private DLinkList head, tail;
    private int capacity, currentSize;

    /**
     * Pop head node
     *
     * @return
     */
    private DLinkList popHead() {
        if (!head.right.equals(tail)) {
            DLinkList node = head.right;
            head.right = node.right;
            node.right.left = head;
            node.right = null;
            node.left = null;
            return node;
        }
        return null;
    }

    /**
     * Push to tail
     *
     * @param node
     */
    private void offer(DLinkList node) {
        tail.left.right = node;
        node.left = tail.left;
        node.right = tail;
        tail.left = node;
    }

    /**
     * Move node to tail
     *
     * @param node
     */
    private void moveToTail(DLinkList node) {
        node.left.right = node.right;
        node.right.left = node.left;
        offer(node);
    }

    public LRUCache(int capacity) {
        this.capacity = capacity;
        this.currentSize = 0;
        cache = new HashMap<>();
        head = new DLinkList(-1, -1);
        tail = new DLinkList(-1, -1);
        head.right = tail;
        tail.left = head;
    }

    public int get(int key) {
        if (cache.get(key) == null) return -1;
        DLinkList node = cache.get(key);
        moveToTail(node);
        return node.value;
    }

    public void put(int key, int value) {
        if (cache.containsKey(key)) {
            DLinkList node = cache.get(key);
            node.value = value;
            moveToTail(node);
        } else {
            if (capacity == currentSize) {
                DLinkList head = popHead();
                if (head != null) {
                    cache.remove(head.key);
                    DLinkList node = new DLinkList(key, value);
                    offer(node);
                    cache.put(key, node);
                }
            } else {
                DLinkList node = new DLinkList(key, value);
                offer(node);
                cache.put(key, node);
                ++currentSize;
            }
        }
    }
}

/**
 * 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);
 */
Copyright © iovi.com 2017 all right reserved,powered by GitbookLast Modification: 2019-04-09 12:30:54

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