server:
port: 8080
spring:
kafka:
bootstrap-servers: 192.168.79.104:9092
producer: # 生产者
retries: 3 # 设置大于 0 的值,则客户端会将发送失败的记录重新发送
batch-size: 16384
buffer-memory: 33554432
acks: 1
# 指定消息key和消息体的编解码方式
key-serializer: org.apache.kafka.common.serialization.StringSerializer
value-serializer: org.apache.kafka.common.serialization.StringSerializer
consumer:
group-id: default-group
enable-auto-commit: false
auto-offset-reset: earliest
key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
max-poll-records: 500
listener:
# 当每一条记录被消费者监听器(ListenerConsumer)处理之后提交
# RECORD
# 当每一批poll()的数据被消费者监听器(ListenerConsumer)处理之后提交
# BATCH
# 当每一批poll()的数据被消费者监听器(ListenerConsumer)处理之后,距离上次提交时间大于TIME时提交
# TIME
# 当每一批poll()的数据被消费者监听器(ListenerConsumer)处理之后,被处理record数量大于等于COUNT时提交
# COUNT
# TIME | COUNT 有一个条件满足时提交
# COUNT_TIME
# 当每一批poll()的数据被消费者监听器(ListenerConsumer)处理之后, 手动调用Acknowledgment.acknowledge()后提交
# MANUAL
# 手动调用Acknowledgment.acknowledge()后立即提交,一般使用这种
# MANUAL_IMMEDIATE
ack-mode: MANUAL_IMMEDIATE
redis:
host: 192.168.79.104
port: 6379
password: 123321
lettuce:
pool:
max-active: 10
max-idle: 10
min-idle: 1
time-between-eviction-runs: 10s
@Configuration
public class KafkaProducerConfig {
@Value("${spring.kafka.bootstrap-servers}")
private String bootstrapServers;
@Bean
public Map<String, Object> producerConfigs() {
Map<String, Object> props = new HashMap<>();
props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
return props;
}
@Bean
public ProducerFactory<String, String> producerFactory() {
return new DefaultKafkaProducerFactory<>(producerConfigs());
}
@Bean
public KafkaTemplate<String, String> kafkaTemplate() {
return new KafkaTemplate<>(producerFactory());
}
}
@RestController
public class KafkaController {
@Autowired
private KafkaTemplate<String, String> kafkaTemplate;
@PostMapping("/send")
public void sendMessage(@RequestBody String message) {
kafkaTemplate.send("my-topic", message);
}
}
@Configuration
@EnableKafka
public class KafkaConsumerConfig {
@Value("${spring.kafka.bootstrap-servers}")
private String bootstrapServers;
@Value("${spring.kafka.consumer.group-id}")
private String groupId;
@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, groupId);
props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
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;
}
}
@Service
public class KafkaConsumer {
@KafkaListener(topics = "my-topic", groupId = "default-group")
public void consume(String message) {
System.out.println("Received message: " + message);
}
}
在上面的代码中,我们使用 @KafkaListener 注解声明了一个消费者方法,用于接收从 my-topic 主题中读取的消息。在这里,我们将消费者组 ID 设置为default-group。
现在,我们已经完成了 Kafka 生产者和消费者的设置。我们可以使用 mvn spring-boot:run 命令启动应用程序,并使用 curl 命令发送 POST 请求到 http://localhost:8080/send 端点,以将消息发送到 Kafka。然后,我们可以在控制台上查看消费者接收到的消息。
这就是使用 Spring Boot 和 Kafka 的基本设置。我们可以根据需要进行更改和扩展,以满足特定的需求。