spring boot与kafka集成

引入相关依赖

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter</artifactId>
</dependency>

<dependency>
    <groupId>org.springframework.kafka</groupId>
    <artifactId>spring-kafka</artifactId>
    <version>1.1.1.RELEASE</version>
</dependency>

从依赖项的引入即可看出，当前spring boot（1.4.2）还不支持完全以配置项的配置来实现与kafka的无缝集成。也就意味着必须通过java config的方式进行手工配置。

定义kafka基础配置

与redisTemplate及jdbcTemplate等类似。spring同样提供了org.springframework.kafka.core.KafkaTemplate作为kafka相关api操作的入口。

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

import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.common.serialization.StringSerializer;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.annotation.EnableKafka;
import org.springframework.kafka.core.DefaultKafkaProducerFactory;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.core.ProducerFactory;

@Configuration
@EnableKafka
public class KafkaProducerConfig {

    public Map<String, Object> producerConfigs() {
        Map<String, Object> props = new HashMap<>();
        props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "192.168.179.200:9092");
        props.put(ProducerConfig.RETRIES_CONFIG, 0);
        props.put(ProducerConfig.BATCH_SIZE_CONFIG, 4096);
        props.put(ProducerConfig.LINGER_MS_CONFIG, 1);
        props.put(ProducerConfig.BUFFER_MEMORY_CONFIG, 40960);
        props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        return props;
    }
    
    public ProducerFactory<String, String> producerFactory() {
        return new DefaultKafkaProducerFactory<>(producerConfigs());
    }

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

KafkaTemplate依赖于ProducerFactory，而创建ProducerFactory时则通过一个Map指定kafka相关配置参数。通过KafkaTemplate对象即可实现消息发送。

kafkaTemplate.send("test-topic", "hello");
or
kafkaTemplate.send("test-topic", "key-1", "hello");

监听消息配置

import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.common.serialization.StringDeserializer;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.annotation.EnableKafka;
import org.springframework.kafka.config.ConcurrentKafkaListenerContainerFactory;
import org.springframework.kafka.config.KafkaListenerContainerFactory;
import org.springframework.kafka.core.ConsumerFactory;
import org.springframework.kafka.core.DefaultKafkaConsumerFactory;
import org.springframework.kafka.listener.ConcurrentMessageListenerContainer;

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

@Configuration
@EnableKafka
public class KafkaConsumerConfig {

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

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

    
    public Map<String, Object> consumerConfigs() {
        Map<String, Object> propsMap = new HashMap<>();
        propsMap.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "192.168.179.200:9092");
        propsMap.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, false);
        propsMap.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG, "100");
        propsMap.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG, "15000");
        propsMap.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        propsMap.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        propsMap.put(ConsumerConfig.GROUP_ID_CONFIG, "test-group");
        propsMap.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "latest");
        return propsMap;
    }

    @Bean
    public Listener listener() {
        return new Listener();
    }
}

实现消息监听的最终目标是得到监听器对象。该监听器对象自行实现。

import org.apache.kafka.clients.consumer.ConsumerRecord;
    import org.springframework.kafka.annotation.KafkaListener;
    
    import java.util.Optional;
    
    public class Listener {

    @KafkaListener(topics = {"test-topic"})
    public void listen(ConsumerRecord<?, ?> record) {
        Optional<?> kafkaMessage = Optional.ofNullable(record.value());
        if (kafkaMessage.isPresent()) {
            Object message = kafkaMessage.get();
            System.out.println("listen1 " + message);
        }
    }
}

只需用@KafkaListener指定哪个方法处理消息即可。同时指定该方法用于监听kafka中哪些topic。

注意事项

定义监听消息配置时，GROUP_ID_CONFIG配置项的值用于指定消费者组的名称，如果同组中存在多个监听器对象则只有一个监听器对象能收到消息。

@KafkaListener中topics属性用于指定kafka topic名称，topic名称由消息生产者指定，也就是由kafkaTemplate在发送消息时指定。

KEY_DESERIALIZER_CLASS_CONFIG与VALUE_DESERIALIZER_CLASS_CONFIG指定key和value的编码、解码策略。kafka用key值确定value存放在哪个分区中。

后记

时间是解决问题的有效手段之一。

在spring boot 1.5版本中即可实现spring boot与kafka Auto-configuration