自定义kafka客户端消费topic

自定义kafka客户端消费topic

结论

使用自定义的KafkaConsumer给spring进行管理，之后在注入topic的set方法中，开单线程主动订阅和读取该topic的消息。

1 背景

后端服务不需要启动时就开始监听消费，而是根据启动的模块或者用户自定义监听需要监听或者停止的topic

2 spring集成2.1.8.RELEASE版本不支持autoStartup属性

使用的spring集成2.1.8.RELEASE的版本，在@KafkaListener注解中没有找到可以直接配置属性autoStartup = "false"来手动启动topic，可能是版本低的原因，如果有可以支持的版本，也可以打在评论区，我去验证一下。

<dependency>
    <groupId>org.springframework.kafka</groupId>
    <artifactId>spring-kafka</artifactId>
    <version>2.1.8.RELEASE</version>
</dependency>

@KafkaListener(topics = "<Kafka主题>", autoStartup = "false") 
public void receive(String message) {    
	// 处理接收到的消息 
}

3 自定义kafka客户端消费topic

3.1 yml配置

spring:
  kafka:
      bootstrap-servers: 19.125.105.6:9092,19.125.105.7,19.125.105.8:9092
      consumer:
        group-id: data-dev
        enable-auto-commit: true
        auto-offset-reset: latest
        auto-commit-interval: 1000
      topic:
        costomTopic: costomData

3.2 KafkaConfig客户端配置

kafka其他配置项和原有的kafka客户端配置一样，只有额外增加了一个cutomConsumer让spring来管理，方便手动启动客户端来使用

import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.common.serialization.StringDeserializer;
import org.apache.kafka.common.serialization.StringSerializer;
import org.springframework.beans.factory.annotation.Value;
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.*;
import org.springframework.kafka.listener.ConcurrentMessageListenerContainer;

import java.util.HashMap;
import java.util.Map;

@Configuration
public class KafkaConfig {

    @Value("${spring.kafka.bootstrap-servers}")
    private String bootstrapServers;
    @Value("${spring.kafka.consumer.group-id}")
    private String groupId;
    @Value("${spring.kafka.consumer.enable-auto-commit}")
    private boolean enableAutoCommit;

    @Value("${spring.kafka.consumer.auto-offset-reset}")
    private String autoOffsetReset;
    //    @Value("${spring.kafka.listener.concurrency}")
//    private Integer concurrency;
    @Value("${spring.kafka.consumer.auto-commit-interval}")
    private Integer autoCommitInterval;

    @Bean
    public KafkaTemplate<String, String> kafkaTemplate() {
        return new KafkaTemplate<>(producerFactory());
    }

    @Bean
    KafkaListenerContainerFactory<ConcurrentMessageListenerContainer<Integer, String>> kafkaContainerFactory() {
        ConcurrentKafkaListenerContainerFactory<Integer, String> factory = new ConcurrentKafkaListenerContainerFactory<>();
        factory.setConsumerFactory(consumerFactory());
        // concurrency
        factory.setConcurrency(3);
        factory.getContainerProperties().setPollTimeout(3000);
        return factory;
    }

    private ProducerFactory<String, String> producerFactory() {
        return new DefaultKafkaProducerFactory<>(producerConfigs());
    }

    public ConsumerFactory<Integer, String> consumerFactory() {
        return new DefaultKafkaConsumerFactory<>(consumerConfigs());
    }

    private Map<String, Object> producerConfigs() {
        Map<String, Object> props = new HashMap<>();
        props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
        props.put(ProducerConfig.RETRIES_CONFIG, 0);
        props.put(ProducerConfig.ACKS_CONFIG, "1");
        props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        return props;
    }

    private Map<String, Object> consumerConfigs() {
        Map<String, Object> props = new HashMap<>();
        props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
        props.put(ConsumerConfig.GROUP_ID_CONFIG, groupId);
        props.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, enableAutoCommit);
        props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        props.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG, autoCommitInterval);
        props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, autoOffsetReset);
        return props;
    }

    @Bean
    public KafkaConsumer cutomConsumer() {
        // 新建一个自定义启动消费者
        KafkaConsumer consumer = new KafkaConsumer<>(consumerConfigs());
        return consumer;
    }
}

3.3 手动启动消费客户端

这里手动启动消费客户端只有在配置了costomTopic才开始启动，如果需要动态指定启停topic

@Component
public class CutomKafkaConsumer {

    // 使用cutomConsumer实例消费
    @Autowired
    private KafkaConsumer cutomConsumer;

    @Value("${spring.kafka.topic.costomTopic:}")
    public void setCostomTopic(String costomTopic) {
        // 手动启动消费类,防止下级模块默认不配置costomTopic导致启动报错
        if (StringUtils.isEmpty(costomTopic)) {
            return;
        }
        // 使这个消费者订阅对应话题
        cutomConsumer.subscribe(Collections.singleton(costomTopic));
        // 单线程拉取消息
        ExecutorService consumerExecutor = Executors.newSingleThreadExecutor();
        consumerExecutor.submit(new Runnable() {
            @Override
            public void run() {
                while (true) {
                    ConsumerRecords<String, String> records = cutomConsumer.poll(3000);
                    if (!records.iterator().hasNext()) {
                        continue;
                    }
                    try {
                        // 捕获异常,防止顶级消费循环被异常中断
                        records.forEach(record -> operate(record));
                    } catch (Exception e) {
                        log.error("消费数据失败,失败原因: {}", e.getMessage(), e);
                    }
                    // 通过异步的方式提交位移
                    cutomConsumer.commitAsync(((offsets, exception) -> {
                        if (exception == null) {
                            offsets.forEach((topicPartition, metadata) -> {
                                System.out.println(topicPartition + " -> offset=" + metadata.offset());
                            });
                        } else {
                            exception.printStackTrace();
                            // 如果出错了，同步提交位移
                            cutomConsumer.commitSync(offsets);
                        }
                    }));
                }
            }
        });
    }
}    

public void operate(ConsumerRecord<String, String> record) {
    log.info("kafkaTwoContainerFactory.operate start. key: {}, value : {}", record.key(), record.value());
}

参考：
Kafka消费者——API开发
Kafka Consumer如何实现精确一次消费数据
Apache Kafka - 灵活控制Kafka消费_动态开启/关闭监听实现
@KafkaListener 详解及消息消费启停控制
kafka多个消费者消费一个topic_kafka消费者组与重平衡机制，了解一下
kafka学习（五）：消费者分区策略（再平衡机制）
Kafka 3.0 源码笔记(3)-Kafka 消费者的核心流程源码分析