The Road To Google From Scratch — LRU Cache Optimized Solution

In this video we implement the optimized solution for the LRU Cache problem using a HashMap combined with a doubly linked list. Instead of scanning the cache to find the least recently used entry, we maintain O(1) time complexity for both get and put operations by using the HashMap for instant lookup and the doubly linked list for instant reordering.

We break down the solution step by step:
1.Understand the problem requirements — design a data structure with O(1) get and put that evicts the least recently used key when capacity is exceeded
2.Design the data structure: HashMap from key to Node, plus a doubly linked list with dummy head and tail to track usage order
3.Implement the get operation — look up the node in the map, move it to the front of the list, return its value
4.Implement the put operation — if the key exists update and move to front, if at capacity evict the tail node, then insert the new node at the front
5.Implement the helper remove and insert operations — relink prev and next pointers in O(1)
6.Handle edge cases — missing key, capacity overflow, updating existing key

Timeline:
0:00 - Condition
0:42 - Visualization
5:22 - Solution

#leetcode #lrucache #design #hashmap #doublylinkedlist #codinginterview #java #python #algorithms #datastructures #medium #faang #interviewprep #cache

Видео The Road To Google From Scratch — LRU Cache Optimized Solution канала Alex_Pro