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?
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
Solution :
class LRUCache extends LinkedHashMap<Integer,Integer>{
private int capacity;
public LRUCache(int capacity) {
super(capacity,0.75F,true);
this.capacity = capacity;
}
public int get(int key) {
return super.getOrDefault(key,-1);
}
public void put(int key, int value) {
super.put(key,value);
}
@Override
protected boolean removeEldestEntry(Map.Entry<Integer,Integer> eldest){
return size() > capacity;
}
}
/**
* 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);
*/
