可以使用有状态重试来实现-在这种情况下，每次重试后都会抛出异常，但是状态在重试状态对象中保持，因此该消息的下一次传递将使用下一个延迟等。需要在消息中添加某些内容（例如标题）以唯一标识每个消息。幸运的是，对于Kafka，主题、分区和偏移量提供了该状态的唯一键。但是，目前“RetryingMessageListenerAdapter”不支持有状态重试。您可以在侦听器容器工厂中禁用重试，并在侦听器中使用有状态的“RetryTemplate”，使用其中一个接受“RetryState”参数的“execute”方法。欢迎为框架添加支持有状态重试的GitHub问题; 欢迎贡献！-
已发布拉取请求。
编辑
我刚刚编写了一个测试用例，以演示如何使用具有@KafkaListener的有状态恢复...
package org.springframework.kafka.annotation;
import static org.assertj.core.api.Assertions.assertThat;
import java.util.Map;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.ConcurrentMap;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.TimeUnit;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.junit.ClassRule;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.config.ConcurrentKafkaListenerContainerFactory;
import org.springframework.kafka.config.KafkaListenerContainerFactory;
import org.springframework.kafka.core.DefaultKafkaConsumerFactory;
import org.springframework.kafka.core.DefaultKafkaProducerFactory;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.core.ProducerFactory;
import org.springframework.kafka.listener.SeekToCurrentErrorHandler;
import org.springframework.kafka.support.KafkaHeaders;
import org.springframework.kafka.test.rule.KafkaEmbedded;
import org.springframework.kafka.test.utils.KafkaTestUtils;
import org.springframework.messaging.handler.annotation.Header;
import org.springframework.retry.RetryState;
import org.springframework.retry.backoff.ExponentialBackOffPolicy;
import org.springframework.retry.support.DefaultRetryState;
import org.springframework.retry.support.RetryTemplate;
import org.springframework.test.annotation.DirtiesContext;
import org.springframework.test.context.junit4.SpringRunner;
@RunWith(SpringRunner.class)
@DirtiesContext
public class StatefulRetryTests {
private static final String DEFAULT_TEST_GROUP_ID = "statefulRetry";
@ClassRule
public static KafkaEmbedded embeddedKafka = new KafkaEmbedded(1, true, 1, "sr1");
@Autowired
private Config config;
@Autowired
private KafkaTemplate<Integer, String> template;
@Test
public void testStatefulRetry() throws Exception {
this.template.send("sr1", "foo");
assertThat(this.config.listener1().latch1.await(10, TimeUnit.SECONDS)).isTrue();
assertThat(this.config.listener1().latch2.await(10, TimeUnit.SECONDS)).isTrue();
assertThat(this.config.listener1().result).isTrue();
}
@Configuration
@EnableKafka
public static class Config {
@Bean
public KafkaListenerContainerFactory<?> kafkaListenerContainerFactory() {
ConcurrentKafkaListenerContainerFactory<Integer, String> factory =
new ConcurrentKafkaListenerContainerFactory<>();
factory.setConsumerFactory(consumerFactory());
factory.getContainerProperties().setErrorHandler(new SeekToCurrentErrorHandler());
return factory;
}
@Bean
public DefaultKafkaConsumerFactory<Integer, String> consumerFactory() {
return new DefaultKafkaConsumerFactory<>(consumerConfigs());
}
@Bean
public Map<String, Object> consumerConfigs() {
Map<String, Object> consumerProps =
KafkaTestUtils.consumerProps(DEFAULT_TEST_GROUP_ID, "false", embeddedKafka);
consumerProps.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
return consumerProps;
}
@Bean
public KafkaTemplate<Integer, String> template() {
KafkaTemplate<Integer, String> kafkaTemplate = new KafkaTemplate<>(producerFactory());
return kafkaTemplate;
}
@Bean
public ProducerFactory<Integer, String> producerFactory() {
return new DefaultKafkaProducerFactory<>(producerConfigs());
}
@Bean
public Map<String, Object> producerConfigs() {
return KafkaTestUtils.producerProps(embeddedKafka);
}
@Bean
public Listener listener1() {
return new Listener();
}
}
public static class Listener {
private static final RetryTemplate retryTemplate = new RetryTemplate();
private static final ConcurrentMap<String, RetryState> states = new ConcurrentHashMap<>();
static {
ExponentialBackOffPolicy backOff = new ExponentialBackOffPolicy();
retryTemplate.setBackOffPolicy(backOff);
}
private final CountDownLatch latch1 = new CountDownLatch(3);
private final CountDownLatch latch2 = new CountDownLatch(1);
private volatile boolean result;
@KafkaListener(topics = "sr1", groupId = "sr1")
public void listen1(final String in, @Header(KafkaHeaders.RECEIVED_TOPIC) String topic,
@Header(KafkaHeaders.RECEIVED_PARTITION_ID) int partition,
@Header(KafkaHeaders.OFFSET) long offset) {
String recordKey = topic + partition + offset;
RetryState retryState = states.get(recordKey);
if (retryState == null) {
retryState = new DefaultRetryState(recordKey);
states.put(recordKey, retryState);
}
this.result = retryTemplate.execute(c -> {
this.latch1.countDown();
throw new RuntimeException("retry");
}, c -> {
latch2.countDown();
return true;
}, retryState);
states.remove(recordKey);
}
}
}
并且
Seek to current after exception; nested exception is org.springframework.kafka.listener.ListenerExecutionFailedException: Listener method 'public void org.springframework.kafka.annotation.StatefulRetryTests$Listener.listen1(java.lang.String,java.lang.String,int,long)' threw exception; nested exception is java.lang.RuntimeException: retry
在每次投递尝试之后。
在这种情况下，我添加了一个恢复器来处理重试耗尽后的消息。您可以做其他事情，比如停止容器（但请在单独的线程上执行此操作，就像我们在ContainerStoppingErrorHandler中所做的那样）。
