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Copy pathDay 24 : LRU Cache
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Day 24 : LRU Cache
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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
class LRUCache {
list<pair<int,int>> cache;
unordered_map<int,list<pair<int,int>>::iterator> mymap; //Key, address in dequeue PAIR
void refreshPosition(int key,int value)
{
cache.erase(mymap[key]);
cache.push_front(make_pair(key,value));
mymap[key] = cache.begin(); //Addr of new position stored in map
}
int capacity;
public:
LRUCache(int capacity) {
this->capacity = capacity;
}
int get(int key) {
if(mymap.find(key)!=mymap.end())
{
refreshPosition(key,(*mymap[key]).second);
return (*mymap[key]).second;
}
return -1;
}
void put(int key, int value) {
if(mymap.find(key)!=mymap.end())
refreshPosition(key,value);
else
{
//Add to cache
cache.push_front(make_pair(key,value));
mymap[key] = cache.begin();
if(mymap.size()>capacity)
{
mymap.erase(cache.back().first);
cache.pop_back();
}
}
}
};
/**
* 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);
*/