Question

我正在使用Kafka和Avro进行序列化/反序列化以处理事件。如果不合格的数据不符合avro架构，那么

std::array

并且消息对于相同的偏移量不断增长。是否有可能只是跳过这个偏移并继续读取更多的偏移量，如果再次发生相同的情况，也可以跳过这个？

消费者代码：

.springframework.kafka.listener.KafkaMessageListenerContainer$ListenerConsumer app: host: dcId: envId: url: reqId: jsess: secSessId: logUser: effUser: impUser: channelName: - Container exception
org.apache.kafka.common.errors.SerializationException: Error deserializing key/value for partition EventProcessor-0 at offset 2845. If needed, please seek past the record to continue consumption.

工厂：

@KafkaListener(topics = "EventProcessor", containerFactory = "eventProcessorListenerContainerFactory")
    public void listen(Event payLoad) {

        System.out.println("REceived  message ===> " + payLoad);

    }

Answer 1

尝试根据@Poppy

的建议调整您的政策

SimpleRetryPolicy policy = new SimpleRetryPolicy();
// Set the max retry attempts
policy.setMaxAttempts(5);
// Retry on all exceptions (this is the default)
policy.setRetryableExceptions(new Class[] {Exception.class});
// ... but never retry SerializationException
policy.setFatalExceptions(new Class[] {SerializationException.class}); //<-- here

// Use the policy...
RetryTemplate template = new RetryTemplate();
template.setRetryPolicy(policy);
template.execute(new RetryCallback<Foo>() {
    public Foo doWithRetry(RetryContext context) {
        // business logic here
    }
});

从这里开始：https://docs.spring.io/spring-batch/3.0.x/reference/html/retry.html

Kafka - 如何跳过偏移中的错误消息并消耗其余消息

1 个答案: