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 producerFactory() {
Map configs = producerConfigs();
DefaultKafkaProducerFactory 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 kafkaTransactionManager(ProducerFactory 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> doSend(final ProducerRecord 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 producer = getTheProducer();
this.logger.trace(() -> "Sending: " + producerRecord);
//定义发送结果回调对象
final SettableListenableFuture> 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 executeInTransaction(KafkaOperations.OperationsCallback 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 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)