146. LRU Cache(Leetcode每日一题-2020.05.25）


Problem

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.

The cache is initialized with a positive capacity.

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

在这里插入图片描述

注意get时，也要更新哈希表和链表

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class LRUCache {
public:
    LRUCache(int capacity) {
        cap = capacity;

    }
   
    int get(int key) {
        auto it= hash_table.find(key);
       
        if(it == hash_table.end()) //key not in cache
            return -1;

        pair<int,int> kv = *(it->second);
        int ret = kv.second;

        //Move current kv to cache head
        cache.erase(it->second);
        cache.push_front(kv);

        //update hash_table
        hash_table[key] = cache.begin();

        return ret;

    }
   
    void put(int key, int value) {
        auto it= hash_table.find(key);
       
        if(it != hash_table.end()) //key in cache
        {
            cache.erase(it->second);
           
        }
        else
        {
            if(cache.size() == cap)//cache is full,remove the least recent used
            {
                pair<int,int> kv = cache.back();
                cache.pop_back();
                hash_table.erase(kv.first);

            }
        }

        cache.push_front(pair<int,int>(key,value));
        hash_table[key] = cache.begin();
           

    }
private:
    int cap;
    list<pair<int,int>> cache;
    unordered_map<int,list<pair<int,int>>::iterator> hash_table;
   
};

/**
 * 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);
 */