In modern Spring applications, it is common to combine asynchronous execution with transactional behavior. However, annotating a method with @Async and @Transactional(propagation = Propagation.REQUIRES_NEW) might result in unexpected behavior because Spring manages asynchronous tasks and transactions.

In this article, we’ll explore the issue in detail and demonstrate a solution to handle both asynchronous execution and transaction management correctly.

The Problem: @Async and @Transactional(propagation = Propagation.REQUIRES_NEW)

Consider the following code snippet:

@Async
@Transactional(propagation = Propagation.REQUIRES_NEW)
public void saveSomething() {
    // save-point one
    // save-point two
}

At first glance, it might seem that everything is working as expected. However, there are some key problems with this configuration that can lead to unintended behavior.

What Happens Behind the Scenes?

• @Async Annotation:

The @Async annotation tells Spring to run the method asynchronously in a separate thread. This means the method will not run in the original thread that called it but will be offloaded to a different thread in a thread pool.
Spring uses proxies to manage asynchronous methods. When you call a method annotated with @Async, Spring delegates the execution to an internal Executor that runs the method in a different thread.

• @Transactional(propagation = Propagation.REQUIRES_NEW) Annotation:

The @Transactional(propagation = Propagation.REQUIRES_NEW) annotation ensures that a new transaction is started for the method, regardless of any existing transaction. It suspends any active transaction in the calling thread and begins a new transaction for the method.

Transaction management in Spring is generally thread-bound, meaning that the transaction context is tied to the current thread.

The Conflict

The issue arises because @Async runs the method in a different thread, and Spring’s transaction management relies on the thread to bind the transaction. When the method is executed asynchronously, the transaction context from the calling thread does not propagate to the new thread, which leads to the following problems:

• The @Transactional annotation will not create a new transaction in the async thread, and any transactional behavior (like rollbacks, commits, etc.) will not be handled correctly.
• The REQUIRES_NEW propagation setting won’t apply because the asynchronous method is running outside the original transaction context.

The Solution: Decoupling Async Execution and Transactions

To solve this problem, you can decouple the asynchronous execution from the transactional logic by handling the transaction in a separate service method. Here’s how you can do it:

• Step 1: Create a New Synchronous Service for Transactional Logic
  Create a new service that handles the transactional logic. This method will be executed synchronously (without @Async) to ensure that the transaction management works as expected.

• Step 2: Call the Synchronous Method Asynchronously
  You can then call the synchronous transactional method asynchronously using @Async. This ensures that the transactional logic is handled correctly in the main thread, and the asynchronous behavior is still maintained.

Here’s how the refactored code looks:

@Service
public class MyService {

    private final TransactionalService transactionalService;

    public MyService(TransactionalService transactionalService) {
        this.transactionalService = transactionalService;
    }

    @Async
    public void saveSomethingAsync() {
        transactionalService.saveSomething();  // Call the synchronous transactional method asynchronously
    }
}

@Service
public class TransactionalService {

    @Transactional(propagation = Propagation.REQUIRES_NEW)
    public void saveSomething() {
        // save-point one
        // save-point two
    }
}

How does it work?

In the refactored solution, asynchronous execution is achieved by annotating the saveSomethingAsync() method with @Async. This means that when saveSomethingAsync() is called, it will run in a separate thread managed by Spring’s asynchronous task executor. Running this in a different thread allows the main thread to continue its execution without waiting for saveSomethingAsync() to complete. This approach is beneficial for scenarios where you want to offload long-running tasks, improve responsiveness, or handle independent operations concurrently.

For transactional behavior, the saveSomething() method in TransactionalService is annotated with @Transactional(propagation = Propagation.REQUIRES_NEW). This ensures that each call to saveSomething() creates a new transaction independent of any existing transaction in the calling method. The REQUIRES_NEW propagation starts a fresh transaction and suspends any existing one, allowing saveSomething() to operate in an isolated transaction context. This means that even if the original calling method has a transaction, saveSomething() will work within its own separate transaction, enabling controlled commits and rollbacks for just this operation.

By decoupling the asynchronous execution from the transactional logic, we ensure that transaction management works as expected. In this setup, the transaction context remains correctly handled within the saveSomething() method, while the saveSomethingAsync() method continues to execute in a separate thread. This separation of concerns allows both the benefits of asynchronous processing and reliable transaction management, enabling independent and safe data operations even when processing concurrently.

When to Use This Approach?

• When Transaction Isolation Is Critical: If you need to ensure that certain operations are carried out in a separate transaction (i.e., REQUIRES_NEW), this approach works well.

• Asynchronous Operations: If you have long-running, independent tasks that need to be executed asynchronously but also require their own transaction boundaries.

Alternative: Using a Message Queue for Complete Decoupling

If you need more advanced decoupling or wish to handle retries, error handling, and long-running processes, consider offloading the task to a message queue like Kafka or RabbitMQ. By using a message queue, you can ensure that each task runs in its own context, and the transaction can be managed independently.