LRU Cache
Design and implement a data structure for Least Recently Used (LRU) cache. It should support the following operations: get and set.
- get(key) - Get the value (will always be positive) of the key if the key exists in the cache, otherwise return -1.
- set(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.
import java.util.*;
public class LRUCache {
int capacity;
HashMap<Integer, Node> map = new HashMap<Integer, Node>();
Node head = null;
Node tail = null;
public LRUCache(int capacity) {
this.capacity = capacity;
}
public int get(int key) {
if (map.containsKey(key)) {
Node n = map.get(key);
remove(n);
setHead(n);
return n.value;
} else {
return -1;
}
}
public void set(int key, int value) {
if (map.containsKey(key)) {
Node n = map.get(key);
n.value = value;
remove(n);
setHead(n);
} else {
Node newNode = new Node(key, value);
if (map.size() >= capacity) {
map.remove(tail.key);
remove(tail);
setHead(newNode);
} else {
setHead(newNode);
}
map.put(key, newNode);
}
}
private void setHead(Node n) {
n.next = head;
n.prev = null;
if (head != null) {
head.prev = n;
}
head = n;
if (tail == null) {
tail = n;
}
}
private void remove(Node n) {
if (n.prev != null) {
n.prev.next = n.next;
} else {
head = n.next;
}
if (n.next != null) {
n.next.prev = n.prev;
} else {
tail = n.prev;
}
}
}
class Node{
int key;
int value;
Node prev;
Node next;
public Node(int key, int value){
this.key = key;
this.value = value;
}
}