How to implement distributed transactions in Java back-end function development?

How to implement distributed transactions in Java back-end function development?

In distributed systems, transaction processing is a common and important requirement. In Java back-end development, we often face scenarios where data operations are performed through multiple services. At this time, we need to consider how to implement distributed transactions to ensure data consistency and reliability. This article will introduce a common method of implementing distributed transactions and illustrate it with code examples.

1. What is a distributed transaction?

Distributed transactions refer to transaction operations involving multiple independent applications or services. Each application or service has its own database, and these databases are located in on different physical nodes. In a distributed transaction, it is necessary to ensure that each participating application or service can correctly submit or roll back the transaction to maintain data consistency.

2. Methods to implement distributed transactions

1. Two-phase commit (2PC) based on message queue

2PC is a common implementation distribution The basic idea of ​​the traditional transaction method is to introduce a coordinator (Coordinator) to coordinate the transaction operations of each participant (Participant). The specific steps are as follows:

(1) Coordination preparation phase (Prepare Phase): The coordinator sends preparation requests to all participants, requiring participants to be ready to execute transactions. After the participant completes the preparation operation, it sends a ready message (Ready) to the coordinator.

(2) Global commit phase (Commit Phase): After receiving the readiness messages from all participants, the coordinator sends a global commit request, requiring participants to perform transaction commit operations. After the participant completes the submission operation, it sends a submission completion message (Commit) to the coordinator.

(3) Global rollback phase (Rollback Phase): If any participant fails in the preparation phase or global commit phase, the coordinator will send a global rollback request and require the participants to perform a rollback operation of the transaction .

2. Eventual Consistency (TCC) based on reliable message confirmation

TCC is an eventual consistency scheme based on reliable message confirmation. Its basic idea is to reserve There are three stages of resource, confirmation and revocation to achieve transaction control. The specific steps are as follows:

(1) Try phase: Participants reserve resources and perform transaction operations locally.

(2) Confirm phase: Participants send confirmation messages and perform real transaction submission operations.

(3) Cancel phase: If any participant fails in the Confirm phase, the undo operation will be performed and the reserved resources will be released.

3. Code Example

The following is a Java example based on Spring Boot and Spring Cloud, demonstrating how to use 2PC based on message queues to implement distributed transactions.

First, we need to add relevant dependencies in the pom.xml file:

<!-- Spring Boot -->
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter</artifactId>
</dependency>

<!-- Spring Cloud -->
<dependency>
    <groupId>org.springframework.cloud</groupId>
    <artifactId>spring-cloud-stream-binder-rabbit</artifactId>
</dependency>

Then, we create a 2PC service based on message queue:

@Service
public class TransactionService {

    @Autowired
    private RabbitTemplate rabbitTemplate;

    @Transactional
    public void performTransaction() {
        // 执行本地事务操作

        // 发送准备请求消息
        rabbitTemplate.convertAndSend("transactionExchange", "prepare");

        // 等待所有参与者返回准备就绪消息
        // ...

        // 发送全局提交请求
        rabbitTemplate.convertAndSend("transactionExchange", "commit");

        // 等待所有参与者返回提交完成消息
        // ...
    }

    @RabbitListener(queues = "prepareQueue")
    public void handlePrepareMessage(String message) {
        // 处理准备请求消息
        // ...

        // 发送准备就绪消息
        rabbitTemplate.convertAndSend("transactionExchange", "ready");
    }

    @RabbitListener(queues = "commitQueue")
    public void handleCommitMessage(String message) {
        // 处理全局提交请求消息
        // ...

        // 发送提交完成消息
        rabbitTemplate.convertAndSend("transactionExchange", "commitComplete");
    }
}

In the above example , using RabbitMQ as the message queue, a 2PC solution based on the message queue is implemented. Specific message processing logic can be adjusted according to business needs.

Conclusion:

This article introduces common methods of implementing distributed transactions in Java back-end development, and illustrates them with code examples. In actual development, it is very important to choose a distributed transaction solution that suits your business needs, and factors such as performance and availability also need to be taken into consideration. I hope this article can provide some reference and help to readers when implementing distributed transactions.

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