Kafka + Spring Batch Listener刷新批处理

问题描述

使用Kafka经纪人:1.0.1spring-kafka:2.1.6.发布

Using Kafka Broker: 1.0.1spring-kafka: 2.1.6.RELEASE

我正在使用具有以下设置的批处理使用者:

I'm using a batched consumer with the following settings:

// Other settings are not shown..
props.put(ConsumerConfig.MAX_POLL_RECORDS_CONFIG, "100");

我通过以下方式使用spring侦听器:

I use spring listener in the following way:

 @KafkaListener(topics = "${topics}", groupId = "${consumer.group.id}")
    public void receive(final List<String> data,
                        @Header(KafkaHeaders.RECEIVED_PARTITION_ID) final List<Integer> partitions,
                        @Header(KafkaHeaders.RECEIVED_TOPIC) Set<String> topics,
                        @Header(KafkaHeaders.OFFSET) final List<Long> offsets) { // ......code... }

我总是发现一些消息保留在批处理中，而在我的侦听器中未收到.看来，如果其余消息小于批处理大小，则不会消耗该消息(可能在内存中并发布给我的侦听器).有什么方法可以设置一个时间间隔后自动刷新批处理，从而避免不刷新消息?用批处理者来处理这种情况的最佳方法是什么?

I always find the a few messages remain in the batch and not received in my listener. It appears to be that if the remaining messages are less than a batch size, it isn't consumed (may be in memory and published to my listener). Is there any way to have a setting to auto-flush the batch after a time interval so as to avoid the messages not being flushed?What's the best way to deal with such kind of situation with a batch consumer?

推荐答案

我刚刚进行了测试，没有任何问题...

I just ran a test without any problems...

@SpringBootApplication
public class So50370851Application {

    public static void main(String[] args) {
        SpringApplication.run(So50370851Application.class, args);
    }

    @Bean
    public ApplicationRunner runner(KafkaTemplate<String, String> template) {
        return args -> {
            for (int i = 0; i < 230; i++) {
                template.send("so50370851", "foo" + i);
            }
        };
    }

    @KafkaListener(id = "foo", topics = "so50370851")
    public void listen(List<String> in) {
        System.out.println(in.size());
    }

    @Bean
    public NewTopic topic() {
        return new NewTopic("so50370851", 1, (short) 1);
    }

}

和

spring.kafka.consumer.auto-offset-reset=earliest
spring.kafka.consumer.enable-auto-commit=false
spring.kafka.consumer.max-poll-records=100
spring.kafka.listener.type=batch

和

100
100
30

这意味着问题出在发送方.

That implies the problem is on the sending side.

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