I'm posting my Java code for LeetCode's LRU Cache. If you have time and would like to review, please do so. Thank you!
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
Accepted Java
public class LRUCache { private final Node head = new Node(0, 0); private final Node tail = new Node(0, 0); private final Map<Integer, Node> cache; private final int capacity; public LRUCache(int capacity) { this.capacity = capacity; cache = new HashMap(capacity); head.next = tail; tail.prev = head; } public int get(int key) { int value = -1; if (cache.containsKey(key)) { Node node = cache.get(key); remove(node); append(node); value = node.value; } return value; } public void put(int key, int value) { if (cache.containsKey(key)) { Node node = cache.get(key); remove(node); node.value = value; append(node); } else { if (cache.size() == capacity) { cache.remove(tail.prev.key); remove(tail.prev); } Node node = new Node(key, value); append(node); cache.put(key, node); } } private void remove(Node node) { node.prev.next = node.next; node.next.prev = node.prev; } private void append(Node node) { Node headNext = head.next; head.next = node; headNext.prev = node; node.prev = head; node.next = headNext; } private class Node { Node prev, next; int key, value; Node(int key, int value) { this.key = key; this.value = value; } } } LeetCode's Solution (Not for review)
public class LRUCache { class DLinkedNode { int key; int value; DLinkedNode prev; DLinkedNode next; } private void addNode(DLinkedNode node) { /** * Always add the new node right after head. */ node.prev = head; node.next = head.next; head.next.prev = node; head.next = node; } private void removeNode(DLinkedNode node){ /** * Remove an existing node from the linked list. */ DLinkedNode prev = node.prev; DLinkedNode next = node.next; prev.next = next; next.prev = prev; } private void moveToHead(DLinkedNode node){ /** * Move certain node in between to the head. */ removeNode(node); addNode(node); } private DLinkedNode popTail() { /** * Pop the current tail. */ DLinkedNode res = tail.prev; removeNode(res); return res; } private Map<Integer, DLinkedNode> cache = new HashMap<>(); private int size; private int capacity; private DLinkedNode head, tail; public LRUCache(int capacity) { this.size = 0; this.capacity = capacity; head = new DLinkedNode(); // head.prev = null; tail = new DLinkedNode(); // tail.next = null; head.next = tail; tail.prev = head; } public int get(int key) { DLinkedNode node = cache.get(key); if (node == null) return -1; // move the accessed node to the head; moveToHead(node); return node.value; } public void put(int key, int value) { DLinkedNode node = cache.get(key); if(node == null) { DLinkedNode newNode = new DLinkedNode(); newNode.key = key; newNode.value = value; cache.put(key, newNode); addNode(newNode); ++size; if(size > capacity) { // pop the tail DLinkedNode tail = popTail(); cache.remove(tail.key); --size; } } else { // update the value. node.value = value; moveToHead(node); } } } Reference
On LeetCode, there is a class usually named Solution with one or more public functions which we are not allowed to rename.
