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.
