spring boot与kafka集成的简单实例

2019-11-26 11:26:30

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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@EnableKafkapublic 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");orkafkaTemplate.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@EnableKafkapublic 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。