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