What are the best practices for implementing an LRU cache?

What are the best practices for implementing an LRU cache?

When implementing an LRU (Least Recently Used) cache, consider the following best practices: 1. Choose the right data structure, like a combination of a hash map and a doubly linked list. 2. Set an appropriate cache size based on your application's needs. 3. Implement thread safety if your application is multi-threaded. 4. Regularly monitor cache performance and adjust parameters as needed.

Can you explain why a hash map and a doubly linked list are used together?

Certainly! A hash map allows for O(1) average time complexity for lookups, while a doubly linked list maintains the order of usage. This combination enables quick access to cache items and efficient removal of the least recently used item.

What should I consider when choosing the cache size?

When choosing the cache size, consider factors like the memory available, the size of the data being cached, the access patterns of your application, and the trade-off between hit rate and memory usage.

Are there any common pitfalls to avoid?

Yes, common pitfalls include not properly managing cache size, failing to handle cache eviction correctly, and not monitoring cache performance, which can lead to inefficient memory usage.