How does LRU caching work in a multithreaded environment?

How does LRU caching work in a multithreaded environment?

LRU, or Least Recently Used, caching in multithreading involves managing shared resources efficiently. Each thread can access the cache, but you need to ensure that updates to the cache are thread-safe to avoid data corruption.

What are some common techniques to make LRU caching thread-safe?

Common techniques include using locks, concurrent data structures, or atomic operations to manage access to the cache. For example, you can use a mutex to lock the cache during updates.

Can you explain how a concurrent hashmap can be used for LRU caching?

A concurrent hashmap allows multiple threads to read and write without locking the entire structure. You can implement LRU by maintaining a linked list of keys to track usage, while the hashmap stores the key-value pairs.

What are the performance implications of using locks in LRU caching?

Using locks can lead to contention, which may degrade performance, especially under high load. It's essential to balance thread safety with performance, possibly by using finer-grained locks or lock-free algorithms.