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
public class LRUCache { public class Node { int key; int value; Node next; Node prev; public Node(int key, int value){ this.key = key; this.value = value; this.next = null; this.prev = null; } } public HashMap<Integer, Node> map = new HashMap<Integer, Node>(); public int capacity; public Node head = new Node(-1, -1); public Node tail = new Node(-1, -1); public LRUCache(int capacity){ this.capacity = capacity; head.next = tail; tail.prev = head; } public int get(int key){ if(map.containsKey(key)) { Node node = map.get(key); node.prev.next = node.next; node.next.prev = node.prev; move_to_tail(node); return node.value; } return -1; } public void put(int key, int value){ if(get(key) != -1){ Node node = map.get(key); node.prev.next = node.next; node.next.prev = node.prev; move_to_tail(node); node.value = value; return; } if(map.size() >= capacity){ map.remove(head.next.key); head.next = head.next.next; head.next.prev = head; } Node node = new Node(key, value); map.put(key, node); move_to_tail(node); } public void move_to_tail(Node node){ node.prev = tail.prev; tail.prev.next = node; node.next = tail; tail.prev = node; }}新闻热点
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