spring boot与kafka集成的简单实例

2019-06-15 IT学院 IT学院
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本文介绍了spring boot与kafka集成的简单实例,分享给大家,具体如下:

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

 

总结

以上所述是IT学院给大家介绍的spring boot与kafka集成的简单实例 ,希望对大家有所帮助,如果大家有任何疑问欢迎给我们留言,小编会及时回复大家的!