How to implement Java distributed transactions using Apache Kafka

Apache Kafka supports Java distributed transactions: enable transactions: configure producer and consumer transaction properties. Processing transactions: Use the transactional interface to send messages and commit or rollback transactions. Practical case: Use Kafka transactions to atomically transmit order information to ensure data consistency between different systems. NOTE: Transactions are isolated by partition, performance may be reduced, keys are used to identify transactions and avoid conflicts.

How to use Apache Kafka to implement Java distributed transactions

Introduction

Apache Kafka is a stream processing platform that provides a high-throughput, low-latency distributed message delivery solution. It has built-in transaction support, allowing you to ensure data consistency in a distributed environment. This article will guide you on how to implement distributed transactions using Apache Kafka and the Java API.

Dependencies

<dependency>
    <groupId>org.apache.kafka</groupId>
    <artifactId>kafka-clients</artifactId>
    <version>3.3.1</version>
</dependency>

Setting up Kafka transactions

To use Kafka transactions, you need to enable producer transactions and consumers Transaction:

Properties properties = new Properties();
properties.put(ProducerConfig.TRANSACTIONAL_ID_CONFIG, "my-transaction-id");

// 创建生产者
Producer<String, String> producer = new KafkaProducer<>(properties);

// 开始事务
producer.initTransactions();

Properties properties = new Properties();
properties.put(ConsumerConfig.ISOLATION_LEVEL_CONFIG, "read_committed");

// 创建消费者
Consumer<String, String> consumer = new KafkaConsumer<>(properties);

// 订阅主题
consumer.subscribe(Arrays.asList("my-topic"));

Processing transaction records

In a transaction, you need to use the transactional interface to send messages and commit or rollback the transaction:

// 发消息
try {
    producer.beginTransaction();
    producer.send(new ProducerRecord<>("my-topic", "key1", "value1"));
    producer.send(new ProducerRecord<>("my-topic", "key2", "value2"));

    // 提交事务
    producer.commitTransaction();

} catch (Exception e) {
    producer.abortTransaction();
}

// 拉取消息
try {
    consumer.subscribe(Arrays.asList("my-topic"));
    ConsumerRecords<String, String> records = consumer.poll(100);

    for (ConsumerRecord<String, String> record : records) {
        // 处理消息
    }

    // 提交偏移量，避免重复消费
    consumer.commitSync();

} catch (Exception e) {
    consumer.seekToBeginning(consumer.assignment());
}

Practical Case

Suppose you have an application that needs to transfer order information from one system to another. To ensure that order information is submitted atomically, you can use Apache Kafka and distributed transactions to achieve:

1. In the order system, use Kafka producer transactions to send order information.
2. In the receiving system, use Kafka consumer transactions to pull order information and process it.
3. If the order is processed successfully, submit the consumer transaction to ensure that the order information is persisted to the receiving system database.
4. If the order processing fails, roll back the consumer transaction and cancel the order information pull.

This way you can ensure that order information is consistent between the two systems, even if a system failure or network problem occurs.

Notes

• Transactions in Apache Kafka are isolated by partition, which means that commits to a single partition will not affect other partitions.
• When using transactions, performance may be reduced because Kafka needs to maintain transaction metadata.
• Ensure that the Kafka record key is set to the part used to uniquely identify the transaction to ensure multiple transactions do not conflict.

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