Solution: LRU Cache
Explore how to implement an LRU cache with Go by combining a doubly linked list and a hash map. Understand how this approach achieves efficient O(1) time complexity for cache operations and why it is preferred over naive solutions. This lesson helps you grasp the design and optimization techniques required to implement custom data structures for real-world coding interview challenges.
Statement
Implement an LRU cache struct with the following functions:
- NewLRUCache(capacity): Initializes an LRU cache with the capacity size.
- Set(key, value): Adds a new key-value pair or updates an existing key with a new value.
- Get(key): Returns the value of the key, or if the key does not exist.
If the number of keys has reached the cache capacity, evict the least recently used key and then add the new key.
As caches use relatively expensive, faster memory, they are not designed to store very large data sets. Whenever the cache becomes full, we need to evict some data from it. There are several caching algorithms to implement a cache eviction policy. LRU is a very simple and commonly used algorithm. The core concept of the LRU algorithm is to evict the oldest data from the cache to accommodate more data.
Constraints:
- capacity