How to implement reliable Java distributed transactions in large-scale systems

In Java, methods to achieve reliable distributed transactions include: XA transaction two-phase commit (2PC) compensation-based distributed transaction distributed transaction framework (such as Spring Framework)

How to implement reliable Java distributed transactions in large-scale systems

Distributed transactions are critical to maintaining the integrity of data between multiple services. In Java, there are several ways to implement reliable distributed transactions, such as:

• XA Transactions: Distributed transactions are provided through the XA interface of the Java Transaction API (JTA) support.
• Two Phase Commit (2PC): A traditional distributed transaction processing protocol involving a coordinator and participants.
• Compensation-based distributed transactions: Data consistency is achieved by performing compensation operations when transactions fail.
• Distributed transaction framework: Such as Spring Framework or Atomikos, providing distributed transaction support out of the box.

Practical case: Order processing system

Consider an order processing system, in which ordering goods requires modifying two services: the goods inventory service and the payment service. To ensure data integrity, we want to implement reliable distributed transactions.

Using the distributed transaction framework Spring Framework, we can define service interfaces and transaction methods:

public interface OrderService {

    @Transactional
    void placeOrder(Order order);
}

In the service implementation, we will use Spring’s @Transactional annotation to Representing transaction boundaries:

public class OrderServiceImpl implements OrderService {

    @Override
    public void placeOrder(Order order) {
        // 更新库存服务
        inventoryService.reduceStock(order.getItemId(), order.getQuantity());

        // 调用支付服务
        paymentService.processPayment(order.getPaymentInfo());
    }
}

In this case, the Spring transaction framework is responsible for coordinating distributed transactions between two services. If any operation fails, the entire transaction is rolled back, ensuring data consistency in both services.

Advantages

• Simplify the implementation of distributed transactions through the distributed transaction framework.
• Guaranteed atomicity, consistency, isolation, and durability (ACID) properties across multiple services.
• Improve system stability and data integrity.

Disadvantages

• Coordination of distributed transactions may introduce performance overhead.
• In some cases, distributed transactions may not guarantee 100% reliability.

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