springboot2.x +kafka使用和源码分析四(kafka事务)

kafka对于事务的支持(0.11.0.0客户端库开始添加了对事务的支持,kafka针对于事务机制新增名为 __transaction_state topic用以保存数据):

• KafkaTransactionManager：与spring提供的事务机制一起使用（@Transactional，TransactionTemplate等等）。

• 使用 KafkaMessageListenerContainer 事务性监听容器(消费者保证消费Exactly Once仅消费处理一次)

• 使用KafkaTemplate

如果需要开启事务机制，使用默认配置需要在yml添加spring.kafka.producer.transaction-id-prefix配置。

或者自己初始化bean在上述KafkaProducerConfigure中添加

    /**
     * 构建生产者工厂类
     */
    @Bean
    public ProducerFactory<Integer, String> producerFactory() {

        Map<String, Object> configs = producerConfigs();

        DefaultKafkaProducerFactory<Integer,String>  producerFactory =  new DefaultKafkaProducerFactory(configs,new IntegerSerializer(),new StringSerializer());

        //设置事务Id前缀 开启事务
        producerFactory.setTransactionIdPrefix("tx-");
        return producerFactory;
    }

    @Bean
    public KafkaTransactionManager<Integer, String> kafkaTransactionManager(ProducerFactory<Integer, String> producerFactory) {
		return new KafkaTransactionManager<>(producerFactory);
	}

将KafkaTransactionManager注入到spring中。如果开启的事务，则后续发送消息必须使用@Transactional注解或者使用kafkaTemplate.executeInTransaction() ,否则抛出java.lang.IllegalStateException: No transaction is in process; possible solutions: run the template operation within the scope of a template.executeInTransaction() operation, start a transaction with @Transactional before invoking the template method, run in a transaction started by a listener container when consuming a record

源码分析：

   /**
     *信息的发送最终会执行此方法
     */
    protected ListenableFuture<SendResult<K, V>> doSend(final ProducerRecord<K, V> producerRecord) {
        //判断是否开启线程
        if (this.transactional) {
            //判断当前消息是通过事务的方式发送
            Assert.state(inTransaction(),
                    "No transaction is in process; "
                            + "possible solutions: run the template operation within the scope of a "
                            + "template.executeInTransaction() operation, start a transaction with @Transactional "
                            + "before invoking the template method, "
                            + "run in a transaction started by a listener container when consuming a record");
        }
        //获取Producer 对象用于发送消息
        final Producer<K, V> producer = getTheProducer();
        this.logger.trace(() -> "Sending: " + producerRecord);
        //定义发送结果回调对象
        final SettableListenableFuture<SendResult<K, V>> future = new SettableListenableFuture<>();
        producer.send(producerRecord, buildCallback(producerRecord, producer, future));
        //是否开启自动刷新
        if (this.autoFlush) {
            flush();
        }
        this.logger.trace(() -> "Sent: " + producerRecord);
        return future;
    }

    /**
     *判断方法的执行是否在事务中
     */
    public boolean inTransaction() {
        return this.transactional && (
                //当前执行线程在ThreadLocal中是否保存过producer如果有说明已在事务中
                this.producers.get() != null
                || TransactionSynchronizationManager.getResource(this.producerFactory) != null
                || TransactionSynchronizationManager.isActualTransactionActive());
    }

 

1:本地事务支持(不支持事务嵌套)

 /**
     * 测试kafka事务机制
     */
    @RequestMapping("sendSyncPersonInfoStrByTransaction")
    public void sendSyncPersonInfoStrByTransaction(){
        JSONObject j = new JSONObject();

        j.put("name","张三测试事务");
        j.put("sex","男");
        j.put("age",18);

        Integer key = new Random().nextInt(100);

        /**
         * 如果KafkaTransactionManager正在进行一个事务，则不使用它。而是使用新的“嵌套”事务。
         */
        boolean flag =kafkaTemplate.executeInTransaction(t->{
    
                //如果在这里这些任何异常抛出 代表此次事务需要进行数据回滚

                t.send("springboot_test_topic",key,j.toJSONString())
                        .get(5, TimeUnit.SECONDS);

                j.put("sex","女");
                t.send("springboot_test_topic",key+10,j.toJSONString())
                        .get(5, TimeUnit.SECONDS);
                int i = 0/0;

                return true;    
           
        });

        System.out.println(flag);

    }

运行上述测试代码，当代码运行报错（ int i = 0/0; 除零异常）时，不会发送任何信息到kafka中

查看executeInTransaction方法源码可以知道

public <T> T executeInTransaction(KafkaOperations.OperationsCallback<K, V, T> callback) {

        Assert.notNull(callback, "'callback' cannot be null");
        Assert.state(this.transactional, "Producer factory does not support transactions");
        //在ThreadLocal保证线程安全
        Producer<K, V> producer = this.producers.get();
        Assert.state(producer == null, "Nested calls to 'executeInTransaction' are not allowed");

        String transactionIdSuffix;
        if (this.producerFactory.isProducerPerConsumerPartition()) {
            transactionIdSuffix = TransactionSupport.getTransactionIdSuffix();
            TransactionSupport.clearTransactionIdSuffix();
        }
        else {
            transactionIdSuffix = null;
        }
        //创建producer 事务的操作由此对象处理
        producer = this.producerFactory.createProducer(this.transactionIdPrefix);

        try {
            //开启事务
            producer.beginTransaction();
        }
        catch (Exception e) {
            //如果发送异常关闭producer 不占用资源
            closeProducer(producer, false);
            throw e;
        }
        //将
        this.producers.set(producer);
        try {
            //执行业务代码
            T result = callback.doInOperations(this);
            try {
                //提交事务
                producer.commitTransaction();
            }
            catch (Exception e) {
                throw new KafkaTemplate.SkipAbortException(e);
            }
            return result;
        }
        catch (KafkaTemplate.SkipAbortException e) { // NOSONAR - exception flow control
            throw ((RuntimeException) e.getCause()); // NOSONAR - lost stack trace
        }
        catch (Exception e) {
            //发生异常 终止事务
            producer.abortTransaction();
            throw e;
        }
        finally {
            //设置事务id
            if (transactionIdSuffix != null) {
                TransactionSupport.setTransactionIdSuffix(transactionIdSuffix);
            }
            //在ThreadLocal移除Producer
            this.producers.remove();
            //关闭资源
            closeProducer(producer, false);
        }
    }

2:使用@Transactional(transactionManager = "kafkaTransactionManager",rollbackFor = Exception.class) 使用

@RequestMapping("sendSyncPersonInfoStrByTransactionZJ")
    @Transactional(transactionManager = "kafkaTransactionManager",rollbackFor = Exception.class)
    public void sendSyncPersonInfoStrByTransactionZJ(){
        JSONObject j = new JSONObject();

        j.put("name","张三测试事务");
        j.put("sex","男");
        j.put("age",18);

        Integer key = new Random().nextInt(100);

        kafkaTemplate.send("transaction_test_topic",20,j.toJSONString());

        j.put("sex","女");
        kafkaTemplate.send("transaction_test_topic",10,j.toJSONString());

//        int i = 0/0;

    }

 

3:嵌套事务

在业务系统可能会存在以下的需求，当发送一条消息时，需要记录一条日志到业务数据库(mysql)中，那么这里面存在两种数据源（kafka,mysql）。这也就是我们说的嵌套事务，那么如何保证去数据一致性。spring提供了自己的解决方案(需要结合Consumer的Listen,后续表明)

Demo项目github地址:https://github.com/fangyuan94/kafkaDemo