L146 LRU Cache
HashMap + double LinkedList
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.
Solution
HashMap + double LinkedList TC: O1 for both put and get function SC: O(capacity)
HashMap is for keeping track of the keys, and keep its values in double linked list.
Class LRUCach{
Map<Integer, ListNode> map;
ListNode head;
ListNode tail;
int size;
int capacity;
public LRUCache(int capacity){
map = new HashMap<>;
head = new ListNode(0,0);
tail = new ListNOde(0,0);
head.next = tail;
tail.prev = head;
size = 0;
this.capacity = capacity;
}
publc int get(int key){
if(!map.contaisKey(key)) return -1;
ListNode node= map.get(key);
delete(node);
addToTail(node);
return node.value;
}
public put(int key, int value){
if(!map.containsKey(key)){
ListNode = newNode = new ListNode(key, value);
if(size == capacity){
ListNode deleteNode = head.next;
delete(deletNode);
map.remove(deleteNode,key);
size --;
}
addToTail(newNode);
map.put(key, newNode);
size ++;
return;
}
ListNode curNode = map.get(key);
curNode.val = value;
delete(curNode);
addToTail(curNode);
return;
}
private void delete(ListNode node){
node.prev.next = node.next;
node.next.prev = node.prev;
node.next = null;
node.prev = null;
}
private void addToTail(ListNode node){
node.next = tial;
node.prev = tail.prev;
tail.prev.next = node;
tail.prev = node;
}
class ListNode{
int key;
int value;
ListNode prev;
ListNode next;
public ListNode(int key, int value){
this.key = key;
this.value = value;
prev = null;
next = null;
}
}
}
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