How can a thread-safe hash table with high performance be implemented in a multithreaded environment?

To implement a thread-safe hash table with high performance in a multithreaded environment, the following approaches can be used:

• Using ConcurrentHashMap — in Java and Android, this is the standard implementation of a thread-safe hash table that provides high performance through segmentation and minimizing locks.

• Minimizing locking — instead of full synchronization across the entire table, locks are applied only to specific segments or operations, increasing parallelism.

• Using atomic operations — for updating values, classes from java.util.concurrent.atomic can be used to avoid locks.

• Avoiding blocking operations in critical sections — to prevent reducing performance.

Example of using ConcurrentHashMap:

ConcurrentHashMap<String, Integer> map = new ConcurrentHashMap<>();

// Adding or updating a value
map.put("key", 42);

// Safe update using compute
map.compute("key", (k, v) -> (v == null) ? 1 : v + 1);

// Getting a value
Integer value = map.get("key");

This class is suitable for most scenarios of multithreaded access to a hash table with good performance.