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

Solution: Using hash map and list

Use Hashtable for fast mapping and double linked list for fast manipulation.

class LRUCache {
public:
    LRUCache(int capacity) {
        size = capacity;
    }

    int get(int key) {
        const auto it = m.find(key);

        // If key does not exist
        if (it == m.end()) return -1;

        // Move this key to the front of the list
        // remove it->second from cache, insert it at the beginning
        cache.splice(cache.begin(), cache, it->second);
        return it->second->second;
    }

    void put(int key, int value) {
        const auto it = m.find(key);

        if (it != m.end()) {
            // Update value is key exists
            it->second->second = value;
            // Move this key to the front
            cache.splice(cache.begin(), cache, it->second);
            return;
        }

        // If key doesn't exist
        // If Cache is full, remove the last key
        if (size == cache.size()) {
            auto& node = cache.back();
            m.erase(node.first);
            cache.pop_back();
        }

        cache.emplace_front(key, value);
        m[key] = cache.begin();
    }

private:
    int size;
    unordered_map<int, list<pair<int, int>>::iterator> m;
    list<pair<int, int>> cache;
};