引入相關(guān)依賴

<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>

從依賴項(xiàng)的引入即可看出，當(dāng)前spring boot（1.4.2）還不支持完全以配置項(xiàng)的配置來實(shí)現(xiàn)與kafka的無縫集成。也就意味著必須通過Java config的方式進(jìn)行手工配置。

定義kafka基礎(chǔ)配置

與redisTemplate及jdbcTemplate等類似。spring同樣提供了org.springframework.kafka.core.KafkaTemplate作為kafka相關(guān)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依賴于ProducerFactory，而創(chuàng)建ProducerFactory時(shí)則通過一個(gè)Map指定kafka相關(guān)配置參數(shù)。通過KafkaTemplate對(duì)象即可實(shí)現(xiàn)消息發(fā)送。

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

監(jiān)聽消息配置

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();
    }
}

實(shí)現(xiàn)消息監(jiān)聽的最終目標(biāo)是得到監(jiān)聽器對(duì)象。該監(jiān)聽器對(duì)象自行實(shí)現(xiàn)。

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指定哪個(gè)方法處理消息即可。同時(shí)指定該方法用于監(jiān)聽kafka中哪些topic。

注意事項(xiàng)

定義監(jiān)聽消息配置時(shí)，GROUP_ID_CONFIG配置項(xiàng)的值用于指定消費(fèi)者組的名稱，如果同組中存在多個(gè)監(jiān)聽器對(duì)象則只有一個(gè)監(jiān)聽器對(duì)象能收到消息。

@KafkaListener中topics屬性用于指定kafka topic名稱，topic名稱由消息生產(chǎn)者指定，也就是由kafkaTemplate在發(fā)送消息時(shí)指定。

KEY_DESERIALIZER_CLASS_CONFIG與VALUE_DESERIALIZER_CLASS_CONFIG指定key和value的編碼、解碼策略。kafka用key值確定value存放在哪個(gè)分區(qū)中。

后記

時(shí)間是解決問題的有效手段之一。

在spring boot 1.5版本中即可實(shí)現(xiàn)spring boot與kafka Auto-configuration

http://www.jianshu.com/p/907731a373a4