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spring boot與kafka集成的簡(jiǎn)單實(shí)例

更新時(shí)間：2017年09月09日 16:58:33 作者：SamHxm

本篇文章主要介紹了spring boot與kafka集成的簡(jiǎn)單實(shí)例，小編覺得挺不錯(cuò)的，現(xiàn)在分享給大家，也給大家做個(gè)參考。一起跟隨小編過來看看吧

本文介紹了spring boot與kafka集成的簡(jiǎn)單實(shí)例，分享給大家，具體如下：

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(wú)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。