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标题:
Spring Boot 集成 Kafka
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作者:
一给
时间:
2024-10-19 06:18
标题:
Spring Boot 集成 Kafka
Spring Boot 与 Kafka 集成是实现高效消息通报和数据流处理的常见方式。Spring Boot 提供了简化 Kafka 设置和使用的功能,使得集成过程变得更加直观和高效。以下是 Spring Boot 集成 Kafka 的详细步调,包括设置、生产者和斲丧者的实现以及一些高级特性。
1. 添加依赖
首先,你必要在 Spring Boot 项目标 pom.xml 文件中添加 Kafka 相干的依赖。使用 Spring Boot 的起步依赖可以简化设置。
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-kafka</artifactId>
</dependency>
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2. 设置 Kafka
2.1. 设置文件
在 application.properties 或 application.yml 文件中设置 Kafka 相干属性。
application.properties
:
# Kafka 服务器地址
spring.kafka.bootstrap-servers=localhost:9092
# Kafka 消费者配置
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
# Kafka 生产者配置
spring.kafka.producer.key-serializer=org.apache.kafka.common.serialization.StringSerializer
spring.kafka.producer.value-serializer=org.apache.kafka.common.serialization.StringSerializer
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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
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2.2. Kafka 设置类
在 Spring Boot 中,你可以使用 @Configuration 注解创建一个设置类,来界说 Kafka 的生产者和斲丧者设置。
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.common.serialization.StringDeserializer;
import org.apache.kafka.common.serialization.StringSerializer;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.core.ConsumerFactory;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.core.ProducerFactory;
import org.springframework.kafka.core.DefaultKafkaConsumerFactory;
import org.springframework.kafka.core.DefaultKafkaProducerFactory;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.listener.ConcurrentMessageListenerContainer;
import org.springframework.kafka.listener.config.ContainerProperties;
import org.springframework.kafka.annotation.EnableKafka;
import org.springframework.kafka.config.ConcurrentKafkaListenerContainerFactory;
import org.springframework.kafka.core.ConsumerFactory;
import org.springframework.kafka.core.ProducerFactory;
import org.springframework.kafka.core.DefaultKafkaConsumerFactory;
import org.springframework.kafka.core.DefaultKafkaProducerFactory;
import java.util.HashMap;
import java.util.Map;
@Configuration
@EnableKafka
public class KafkaConfig {
@Bean
public ProducerFactory<String, String> producerFactory() {
Map<String, Object> configProps = new HashMap<>();
configProps.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
configProps.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
configProps.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
return new DefaultKafkaProducerFactory<>(configProps);
}
@Bean
public KafkaTemplate<String, String> kafkaTemplate() {
return new KafkaTemplate<>(producerFactory());
}
@Bean
public ConsumerFactory<String, String> consumerFactory() {
Map<String, Object> configProps = new HashMap<>();
configProps.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
configProps.put(ConsumerConfig.GROUP_ID_CONFIG, "my-group");
configProps.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
configProps.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
return new DefaultKafkaConsumerFactory<>(configProps);
}
@Bean
public ConcurrentKafkaListenerContainerFactory<String, String> kafkaListenerContainerFactory() {
ConcurrentKafkaListenerContainerFactory<String, String> factory =
new ConcurrentKafkaListenerContainerFactory<>();
factory.setConsumerFactory(consumerFactory());
return factory;
}
}
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3. 实现 Kafka 生产者
3.1. 生产者服务
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.stereotype.Service;
@Service
public class KafkaProducerService {
@Autowired
private KafkaTemplate<String, String> kafkaTemplate;
private static final String TOPIC = "my_topic";
public void sendMessage(String message) {
kafkaTemplate.send(TOPIC, message);
}
}
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3.2. 控制器示例
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.PostMapping;
import org.springframework.web.bind.annotation.RequestBody;
import org.springframework.web.bind.annotation.RestController;
@RestController
public class KafkaController {
@Autowired
private KafkaProducerService kafkaProducerService;
@PostMapping("/send")
public void sendMessage(@RequestBody String message) {
kafkaProducerService.sendMessage(message);
}
}
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4. 实现 Kafka 斲丧者
4.1. 斲丧者服务
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Service;
@Service
public class KafkaConsumerService {
@KafkaListener(topics = "my_topic", groupId = "my-group")
public void listen(String message) {
System.out.println("Received message: " + message);
}
}
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5. 高级特性
5.1. 消息事务
Kafka 支持消息事务,确保消息的原子性。
生产者设置
:
spring.kafka.producer.enable-idempotence=true
spring.kafka.producer.transaction-id-prefix=my-transactional-id
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使用事务
:
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.core.ProducerFactory;
import org.springframework.kafka.core.TransactionTemplate;
import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;
@Service
public class KafkaTransactionalService {
private final KafkaTemplate<String, String> kafkaTemplate;
private final TransactionTemplate transactionTemplate;
public KafkaTransactionalService(KafkaTemplate<String, String> kafkaTemplate, TransactionTemplate transactionTemplate) {
this.kafkaTemplate = kafkaTemplate;
this.transactionTemplate = transactionTemplate;
}
@Transactional
public void sendMessageInTransaction(String message) {
kafkaTemplate.executeInTransaction(t -> {
kafkaTemplate.send("my_topic", message);
return true;
});
}
}
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5.2. 异步发送与回调
异步发送
:
public void sendMessageAsync(String message) {
kafkaTemplate.send("my_topic", message).addCallback(
result -> System.out.println("Sent message: " + message),
ex -> System.err.println("Failed to send message: " + ex.getMessage())
);
}
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总结
Spring Boot 与 Kafka 的集成使得消息队列的使用变得更加简朴和高效。通过上述步调,你可以轻松地设置 Kafka、实现生产者和斲丧者,并使用 Spring Boot 提供的强大功能来处理消息流。相识 Kafka 的高级特性(如事务和异步处理)能够帮助你更好地满意业务需求,确保系统的高可用性和数据同等性。
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