【发布时间】:2018-11-28 18:31:44
【问题描述】:
我的目标是从主题 A 消费,做一些处理并生产到主题 B,作为一个单一的原子动作。为了实现这一点,我看到了两个选项:
- 如here 所述,使用 spring-kafka @Kafkalistener 和 KafkaTemplate。
- 使用 Streams eos(exactly-once)功能。
我已成功验证选项 #1。成功,我的意思是如果我的处理失败(抛出 IllegalArgumentException)来自主题 A 的消费消息继续被 KafkaListener 消费。这是我所期望的,因为未提交偏移量并且使用了DefaultAfterRollbackProcessor。
如果我使用流从主题 A 消费、处理和发送到主题 B(选项 #2)而不是 KafkaListener,我希望看到相同的行为。但是,即使在我处理 IllegalArgumentException 时抛出了消息,流也只会使用一次。这是预期的行为吗?
在 Streams 情况下,我唯一的配置如下:
@Configuration
@EnableKafkaStreams
public class KafkaStreamsConfiguration {
@Bean(name = KafkaStreamsDefaultConfiguration.DEFAULT_STREAMS_CONFIG_BEAN_NAME)
public StreamsConfig kStreamsConfigs() {
Map<String, Object> props = new HashMap<>();
props.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, "http://localhost:9092");
props.put(StreamsConfig.APPLICATION_ID_CONFIG, "calculate-tax-sender-invoice-stream");
props.put(AbstractKafkaAvroSerDeConfig.SCHEMA_REGISTRY_URL_CONFIG, "http://localhost:8082");
// this should be enough to enable transactions
props.put(StreamsConfig.PROCESSING_GUARANTEE_CONFIG, StreamsConfig.EXACTLY_ONCE);
return new StreamsConfig(props);
}
}
//required to create and start a new KafkaStreams, as when an exception is thrown the stream dies
// see here: https://docs.spring.io/spring-kafka/reference/html/_reference.html#after-rollback
@Bean(name = KafkaStreamsDefaultConfiguration.DEFAULT_STREAMS_BUILDER_BEAN_NAME)
public StreamsBuilderFactoryBean myKStreamBuilder(StreamsConfig streamsConfig) {
StreamsBuilderFactoryBean streamsBuilderFactoryBean = new StreamsBuilderFactoryBean(streamsConfig);
streamsBuilderFactoryBean.setUncaughtExceptionHandler(new Thread.UncaughtExceptionHandler() {
@Override
public void uncaughtException(Thread t, Throwable e) {
log.debug("StopStartStreamsUncaughtExceptionHandler caught exception {}, stopping StreamsThread ..", e);
streamsBuilderFactoryBean.stop();
log.debug("creating and starting a new StreamsThread ..");
streamsBuilderFactoryBean.start();
}
});
return streamsBuilderFactoryBean;
}
我的直播是这样的:
@Autowired
public SpecificAvroSerde<InvoiceEvents> eventSerde;
@Autowired
private TaxService taxService;
@Bean
public KStream<String, InvoiceEvents> kStream(StreamsBuilder builder) {
KStream<String, InvoiceEvents> kStream = builder.stream("A",
Consumed.with(Serdes.String(), eventSerde));
kStream
.mapValues(v ->
{
// get tax from possibly remote service
// an IllegalArgumentException("Tax calculation failed") is thrown by getTaxForInvoice()
int tax = taxService.getTaxForInvoice(v);
// create a TaxCalculated event
InvoiceEvents taxCalculatedEvent = InvoiceEvents.newBuilder().setType(InvoiceEvent.TaxCalculated).setTax(tax).build();
log.debug("Generating TaxCalculated event: {}", taxCalculatedEvent);
return taxCalculatedEvent;
})
.to("B", Produced.with(Serdes.String(), eventSerde));
return kStream;
}
快乐路径流场景有效:如果在处理过程中没有抛出异常,则消息正确显示在主题 B 中。
我的单元测试:
@Test
public void calculateTaxForInvoiceTaxCalculationFailed() throws Exception {
log.debug("running test calculateTaxForInvoiceTaxCalculationFailed..");
Mockito.when(taxService.getTaxForInvoice(any(InvoiceEvents.class)))
.thenThrow(new IllegalArgumentException("Tax calculation failed"));
InvoiceEvents invoiceCreatedEvent = createInvoiceCreatedEvent();
List<KeyValue<String, InvoiceEvents>> inputEvents = Arrays.asList(
new KeyValue<String, InvoiceEvents>("A", invoiceCreatedEvent));
Properties producerConfig = new Properties();
producerConfig.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "http://localhost:9092");
producerConfig.put(ProducerConfig.ACKS_CONFIG, "all");
producerConfig.put(ProducerConfig.RETRIES_CONFIG, 1);
producerConfig.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getName());
producerConfig.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, KafkaAvroSerializer.class.getName());
producerConfig.put(AbstractKafkaAvroSerDeConfig.SCHEMA_REGISTRY_URL_CONFIG, "http://localhost:8082");
producerConfig.put(ProducerConfig.CLIENT_ID_CONFIG, "unit-test-producer");
// produce with key
IntegrationTestUtils.produceKeyValuesSynchronously("A", inputEvents, producerConfig);
// wait for 30 seconds - I should observe re-consumptions of invoiceCreatedEvent, but I do not
Thread.sleep(30000);
// ...
}
更新: 在我的单元测试中,我发送了 50 个 invoiceEvents (orderId=1,...,50),我处理它们并将它们发送到目标主题。
在我的日志中,我看到的行为如下:
invoiceEvent.orderId = 43 → consumed and successfully processed
invoiceEvent.orderId = 44 → consumed and IlleagalArgumentException thrown
..new stream starts..
invoiceEvent.orderId = 44 → consumed and successfully processed
invoiceEvent.orderId = 45 → consumed and successfully processed
invoiceEvent.orderId = 46 → consumed and successfully processed
invoiceEvent.orderId = 47 → consumed and successfully processed
invoiceEvent.orderId = 48 → consumed and successfully processed
invoiceEvent.orderId = 49 → consumed and successfully processed
invoiceEvent.orderId = 50 → consumed and IlleagalArgumentException thrown
...
[29-0_0-producer] task [0_0] Error sending record (key A value {"type": ..., "payload": {**"id": "46"**, ... }}} timestamp 1529583666036) to topic invoice-with-tax.t due to {}; No more records will be sent and no more offsets will be recorded for this task.
..new stream starts..
invoiceEvent.**orderId = 46** → consumed and successfully processed
invoiceEvent.orderId = 47 → consumed and successfully processed
invoiceEvent.orderId = 48 → consumed and successfully processed
invoiceEvent.orderId = 49 → consumed and successfully processed
invoiceEvent.orderId = 50 → consumed and successfully processed
为什么在第二次失败后,从 invoiceEvent.orderId = 46 重新消费?
【问题讨论】:
-
问题是,您在输出主题中看到了什么?启用完全一次,保证输出主题包含一个结果,就好像没有发生错误一样。是否重新使用数据取决于输出是否在失败之前成功写入。什么时候抛出异常有点不清楚?
-
感谢马蒂亚斯的快速回复!在我的单元测试中,我总是从 taxService.getTaxForInvoice(v) 中抛出 IllegalArgumentException 异常。我的期望是消息应该被重新消费,但我只看到初始消费(即没有重新消费)。我试图了解我的预期是否正确。
-
我编辑了我的帖子以包含单元测试。
-
如果抛出异常,
StreamThread会死掉,不会自动重启。在观察到第一个异常(通过未捕获的异常处理程序)后,您是否关闭()Kafka Streams,创建一个新的,然后重新启动它? -
提交是基于挂钟时间通过参数
commit.interval.ms进行的配置。如果您希望每条消息都提交,则设置max.poll.records=1是正确的,但还不够。您还需要为每条记录手动请求提交(您可以插入仅转发数据并请求提交的transformValues步骤)。参照。 stackoverflow.com/questions/43416178/…
标签: apache-kafka apache-kafka-streams spring-kafka