在Spring Boot中配置Kafka非常简单,只需要几个步骤就可以完成。以下是一些关键步骤:
在你的pom.xml
文件中添加Spring Boot Kafka的依赖:
<dependency>
<groupId>org.springframework.kafka</groupId>
<artifactId>spring-kafka</artifactId>
</dependency>
在application.properties
或application.yml
文件中配置Kafka相关的属性。以下是一些常用的配置属性:
# application.properties
spring.kafka.bootstrap-servers=localhost:9092
spring.kafka.consumer.group-id=my-group
spring.kafka.consumer.auto-offset-reset=earliest
spring.kafka.consumer.key-deserializer=org.apache.kafka.common.serialization.StringDeserializer
spring.kafka.consumer.value-deserializer=org.apache.kafka.common.serialization.StringDeserializer
spring.kafka.producer.key-serializer=org.apache.kafka.common.serialization.StringSerializer
spring.kafka.producer.value-serializer=org.apache.kafka.common.serialization.StringSerializer
# application.yml
spring:
kafka:
bootstrap-servers: localhost:9092
consumer:
group-id: my-group
auto-offset-reset: earliest
key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
producer:
key-serializer: org.apache.kafka.common.serialization.StringSerializer
value-serializer: org.apache.kafka.common.serialization.StringSerializer
创建一个配置类,用于创建Kafka的生产者和消费者。以下是一个简单的示例:
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.common.serialization.StringDeserializer;
import org.apache.kafka.common.serialization.StringSerializer;
import org.springframework.beans.factory.annotation.Value;
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.KafkaListenerEndpointRegistrar;
import org.springframework.kafka.config.KafkaListenerEndpointRegistry;
import org.springframework.kafka.core.ConsumerFactory;
import org.springframework.kafka.core.DefaultKafkaConsumerFactory;
import org.springframework.kafka.core.DefaultKafkaProducerFactory;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.core.ProducerFactory;
import java.util.HashMap;
import java.util.Map;
@Configuration
@EnableKafka
public class KafkaConfig {
@Value("${spring.kafka.bootstrap-servers}")
private String bootstrapServers;
@Bean
public Map<String, Object> consumerConfigs() {
Map<String, Object> props = new HashMap<>();
props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
props.put(ConsumerConfig.GROUP_ID_CONFIG, "my-group");
props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
return props;
}
@Bean
public ConsumerFactory<String, String> consumerFactory() {
return new DefaultKafkaConsumerFactory<>(consumerConfigs());
}
@Bean
public ConcurrentKafkaListenerContainerFactory<String, String> kafkaListenerContainerFactory() {
ConcurrentKafkaListenerContainerFactory<String, String> factory = new ConcurrentKafkaListenerContainerFactory<>();
factory.setConsumerFactory(consumerFactory());
return factory;
}
@Bean
public Map<String, Object> producerConfigs() {
Map<String, Object> props = new HashMap<>();
props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
return props;
}
@Bean
public ProducerFactory<String, String> producerFactory() {
return new DefaultKafkaProducerFactory<>(producerConfigs());
}
@Bean
public KafkaTemplate<String, String> kafkaTemplate() {
return new KafkaTemplate<>(producerFactory());
}
@Bean
public KafkaListenerEndpointRegistrar kafkaListenerEndpointRegistrar() {
return new KafkaListenerEndpointRegistrar();
}
@Bean
public KafkaListenerEndpointRegistry kafkaListenerEndpointRegistry() {
return new KafkaListenerEndpointRegistry();
}
}
创建一个监听器类,用于处理Kafka消息。以下是一个简单的示例:
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Component;
@Component
public class KafkaListenerExample {
@KafkaListener(topics = "my-topic", groupId = "my-group")
public void listen(String message) {
System.out.println("Received message: " + message);
}
}
在你的应用程序中,你可以使用KafkaTemplate
发送消息到Kafka。以下是一个简单的示例:
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.stereotype.Component;
@Component
public class KafkaProducerExample {
@Autowired
private KafkaTemplate<String, String> kafkaTemplate;
public void sendMessage(String topic, String message) {
kafkaTemplate.send(topic, message);
}
}
现在你已经成功配置了Spring Boot Kafka,可以开始发送和接收消息了。如果你需要更复杂的配置,可以在application.properties
或application.yml
文件中进行修改,或者在KafkaConfig
类中添加更多的配置方法。