springboot之配置双kafka全过程

2023-05-16 11:05:34 配置 springboot 全过程

springboot配置双kafka

使用Spring Boot 2.0.8.RELEASE 版本

引入Maven kafka jar、准备两个kafka；

<dependency>
    <groupId>org.springframework.kafka</groupId>
    <artifactId>spring-kafka</artifactId>
</dependency>

配置yml配置文件

spring:
  kafka:
    bootstrap-servers: 180.167.180.242:9092 #kafka的访问地址，多个用","隔开
    consumer:
      enable-auto-commit: true
      group-id: kafka #群组ID
  outkafka:
    bootstrap-servers: localhost:9092 #kafka的访问地址，多个用","隔开
    consumer:
      enable-auto-commit: true
      group-id: kafka_1 #群组ID

配置KafkaConfig类

import java.util.HashMap;
import java.util.Map;
 
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.context.annotation.Primary;
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.core.DefaultKafkaProducerFactory;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.core.ProducerFactory;
import org.springframework.kafka.listener.ConcurrentMessageListenerContainer;
 
@Configuration
@EnableKafka
public class KafkaConfig {
    @Value("${spring.kafka.bootstrap-servers}")
    private String innerServers;
    @Value("${spring.kafka.consumer.group-id}")
    private String innerGroupid;
    @Value("${spring.kafka.consumer.enable-auto-commit}")
    private String innerEnableAutoCommit;
 
    @Bean
    @Primary//理解为默认优先选择当前容器下的消费者工厂
    KafkaListenerContainerFactory<ConcurrentMessageListenerContainer<Integer, String>> kafkaListenerContainerFactory() {
        ConcurrentKafkaListenerContainerFactory<Integer, String> factory = new ConcurrentKafkaListenerContainerFactory<>();
        factory.setConsumerFactory(consumerFactory());
        factory.setConcurrency(3);
        factory.getContainerProperties().setPollTimeout(3000);
        return factory;
    }
 
    @Bean//第一个消费者工厂的bean
    public ConsumerFactory<Integer, String> consumerFactory() {
        return new DefaultKafkaConsumerFactory<>(consumerConfigs());
    }
 
    @Bean
    public Map<String, Object> consumerConfigs() {
        Map<String, Object> props = new HashMap<>();
        props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, innerServers);
        props.put(ConsumerConfig.GROUP_ID_CONFIG, innerGroupid);
        props.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, innerEnableAutoCommit);
//        props.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG, "100");
//        props.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG, "15000");
        props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        return props;
    }
    
    @Bean //生产者工厂配置
    public ProducerFactory<String, String> producerFactory() {
        return new DefaultKafkaProducerFactory<>(senderProps());
    }
    
    @Bean //kafka发送消息模板
    public KafkaTemplate<String, String> kafkaTemplate() {
        return new KafkaTemplate<String, String>(producerFactory());
    }
    
    
    private Map<String, Object> senderProps() {
        Map<String, Object> props = new HashMap<>();
        props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, innerServers);
        
        props.put(ProducerConfig.RETRIES_CONFIG, 0);
        
        props.put(ProducerConfig.ACKS_CONFIG, "1");
        
        // 以下配置当缓存数量达到16kb，就会触发网络请求，发送消息
//        props.put(ProducerConfig.BATCH_SIZE_CONFIG, 16384);
        // 每条消息在缓存中的最长时间，如果超过这个时间就会忽略batch.size的限制，由客户端立即将消息发送出去
//        props.put(ProducerConfig.LINGER_MS_CONFIG, 1);
//        props.put(ProducerConfig.BUFFER_MEMORY_CONFIG, 33554432);
        props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        return props;
    }
    
    @Value("${spring.outkafka.bootstrap-servers}")
    private String outServers;
    @Value("${spring.outkafka.consumer.group-id}")
    private String outGroupid;
    @Value("${spring.outkafka.consumer.enable-auto-commit}")
    private String outEnableAutoCommit;
    
 
    static {
        
    }
    
    
    @Bean
    KafkaListenerContainerFactory<ConcurrentMessageListenerContainer<Integer, String>> kafkaListenerContainerFactoryOutSchedule() {
        ConcurrentKafkaListenerContainerFactory<Integer, String> factory = new ConcurrentKafkaListenerContainerFactory<>();
        factory.setConsumerFactory(consumerFactoryOutSchedule());
        factory.setConcurrency(3);
        factory.getContainerProperties().setPollTimeout(3000);
        return factory;
    }
 
    @Bean
    public ConsumerFactory<Integer, String> consumerFactoryOutSchedule() {
        return new DefaultKafkaConsumerFactory<>(consumerConfigsOutSchedule());
    }
 
    
    @Bean
    public Map<String, Object> consumerConfigsOutSchedule() {
        Map<String, Object> props = new HashMap<>();
        props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, outServers);
        props.put(ConsumerConfig.GROUP_ID_CONFIG, outGroupid);
        props.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, outEnableAutoCommit);
        props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        return props;
    }
    
    @Bean //生产者工厂配置
    public ProducerFactory<String, String> producerOutFactory() {
        return new DefaultKafkaProducerFactory<>(senderOutProps());
    }
    
    @Bean //kafka发送消息模板
    public KafkaTemplate<String, String> kafkaOutTemplate() {
        return new KafkaTemplate<String, String>(producerOutFactory());
    }
    
    
    private Map<String, Object> senderOutProps() {
        Map<String, Object> props = new HashMap<>();
        props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, outServers);
        
        props.put(ProducerConfig.RETRIES_CONFIG, 0);
        
        props.put(ProducerConfig.ACKS_CONFIG, "1");
        
        // 以下配置当缓存数量达到16kb，就会触发网络请求，发送消息
//        props.put(ProducerConfig.BATCH_SIZE_CONFIG, 16384);
        // 每条消息在缓存中的最长时间，如果超过这个时间就会忽略batch.size的限制，由客户端立即将消息发送出去
//        props.put(ProducerConfig.LINGER_MS_CONFIG, 1);
//        props.put(ProducerConfig.BUFFER_MEMORY_CONFIG, 33554432);
        props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        return props;
    }
}

发送工具类MyKafkaProducer

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.support.SendResult;
import org.springframework.scheduling.annotation.EnableScheduling;
import org.springframework.stereotype.Component;
import org.springframework.util.concurrent.ListenableFuture;
 
import lombok.extern.slf4j.Slf4j;
 

@Component // 这个必须加入容器不然，不会执行
@EnableScheduling // 这里是为了测试加入定时调度
@Slf4j
public class MyKafkaProducer {
 
    @Autowired
    private KafkaTemplate<String, String> kafkaTemplate;
 
    @Autowired
    private KafkaTemplate<String, String> kafkaOutTemplate;
 
    public ListenableFuture<SendResult<String, String>> send(String topic, String key, String JSON) {
        ListenableFuture<SendResult<String, String>> result = kafkaTemplate.send(topic, key, json);
        log.info("inner kafka send #topic=" + topic + "#key=" + key + "#json=" + json + "#推送成功===========");
        return result;
    }
 
    public ListenableFuture<SendResult<String, String>> sendOut(String topic, String key, String json) {
        ListenableFuture<SendResult<String, String>> result = kafkaOutTemplate.send(topic, key, json);
        log.info("out kafka send #topic=" + topic + "#key=" + key + "#json=" + json + "#推送成功===========");
        return result;
    }
 
}

测试类

@Slf4j
@RunWith(SpringJUnit4ClassRunner.class)
@SpringBootTest(classes={OesBcServiceApplication.class})
public class MoreKafkaTest {
    
    @Autowired
    private MyKafkaProducer kafkaProducer;
    
    @Test
    public void sendInner() {
        for (int i = 0; i < 1; i++) {
            kafkaProducer.send("inner_test", "douzi" + i, "liyuehua" + i);
            kafkaProducer.sendOut("out_test", "douziout" + i, "fanbingbing" + i);
        }
    }
}

接收类

@Component
@Slf4j
public class KafkaConsumer {  
    @KafkaListener(topics={"inner_test"}, containerFactory="kafkaListenerContainerFactory")
    public void innerlistener(ConsumerRecord<String, String> record) {
        log.info("inner kafka receive #key=" + record.key() + "#value=" + record.value());
    }
    
    @KafkaListener(topics={"out_test"}, containerFactory="kafkaListenerContainerFactoryOutSchedule")
    public void outListener(ConsumerRecord<String, String> record) {
        log.info("out kafka receive #key=" + record.key() + "#value=" + record.value());
    }
}

测试结果

07-11 12:41:27.811 INFO [com.wondertek.oes.bc.service.send.MyKafkaProducer] - inner kafka send #topic=inner_test#key=douzi0#json=liyuehua0#推送成功===========

07-11 12:41:27.995 INFO [com.wondertek.oes.bc.service.send.KafkaConsumer] - inner kafka receive #key=douzi0#value=liyuehua0
07-11 12:41:28.005 INFO [com.wondertek.oes.bc.service.send.MyKafkaProducer] - out kafka send #topic=out_test#key=douziout0#json=fanbingbing0#推送成功===========
07-11 12:41:28.013 INFO [com.wondertek.oes.bc.service.send.KafkaConsumer] - out kafka receive #key=douziout0#value=fanbingbing0

总结

以上为个人经验，希望能给大家一个参考，也希望大家多多支持。

相关文章

springboot之配置双kafka全过程

目录

springboot配置双kafka

引入Maven kafka jar、准备两个kafka；

配置yml配置文件

配置KafkaConfig类

发送工具类MyKafkaProducer

测试类

接收类

测试结果

总结