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.
This is a difficult question, I can’t write the solution easily even after a month.
Solution
The solution is to use a Doubly-linked-list and a HashMap. Doing this allows O(1) search, remove and insert. A very nice and sophisticated data structure example, and very high frequency in interviews.
2 important things to note while coding:
We need 2 helper methods: removeNode() and setNodeAsHead().
Because we reuse both methods for get() and set() methods.
Initialization of LRU
We need 5 variables: capacity, current size(optional but good to have), hashmap, head, tail.
Initialization of DoubleLinkedListNode
This is easy, but do not forget about both key and value variable. We must use DoubleLinkedListNode.key when we want to delete tail.
public LRUCache(int capacity) { this.size = 0; this.capacity = capacity; head = null; tail = null; map = new HashMap<Integer, DoubleLinkedList>(); }
public void remove(DoubleLinkedList node) { if (node == head && node == tail) { head = null; tail = null; } else if (node == head) { head.next.prev = null; head = head.next; } else if (node == tail) { tail.prev.next = null; tail = tail.prev; } else { node.prev.next = node.next; node.next.prev = node.prev; } node.prev = null; node.next = null; }
public void setHead(DoubleLinkedList node) { node.next = head; node.prev = null; if (head != null) { head.prev = node; }
head = node; if (tail == null) { tail = node; } }
public int get(int key) { if (!map.containsKey(key)) { // if key is not found return -1; } else { // if key is found DoubleLinkedList target = map.get(key); remove(target); setHead(target); return head.val; } }
public void set(int key, int value) { if (this.get(key) != -1) { // key exist before, just replace the old value DoubleLinkedList old = map.get(key); old.val = value; } else { // this is a new key-value pair, insert it DoubleLinkedList newHead = new DoubleLinkedList(key, value); map.put(key, newHead); setHead(newHead); if (size == capacity) { // delete tail map.remove(tail.key); remove(tail); } else { size++; } } }
class DoubleLinkedList { int key; int val; DoubleLinkedList prev; DoubleLinkedList next; public DoubleLinkedList(int k, int v) { this.key = k; this.val = v; } } }
int capacity; DoublyLinkedNode head; DoublyLinkedNode tail; HashMap<Integer, DoublyLinkedNode> map;
public LRUCache(int capacity) { this.capacity = capacity; head = null; tail = null; map = new HashMap<Integer, DoublyLinkedNode>(); }
public int get(int key) { if (!map.containsKey(key)) { return -1; } else { DoublyLinkedNode target = map.get(key); removeNode(target); setHead(target); return head.val; } }
public void put(int key, int value) { if (this.get(key) != -1) { DoublyLinkedNode curNode = map.get(key); curNode.val = value; } else { // this is a new key-value pair, insert it DoublyLinkedNode newHead = new DoublyLinkedNode(key, value); map.put(key, newHead); setHead(newHead); if (map.size() > capacity) { map.remove(tail.key); removeNode(tail); } } }