聊聊在springboot项目中如何配置多个kafka消费者

前言

不知道大家有没有遇到这样的场景，就是一个项目中要消费多个kafka消息，不同的消费者消费指定kafka消息。遇到这种场景，我们可以通过kafka的提供的api进行配置即可。但很多时候我们会使用spring-kafka来简化开发，可是spring-kafka原生的配置项并没提供多个kafka配置，因此本文就来聊聊如何将spring-kafka进行改造，使之能支持多个kafka配置

正文

1、通过 @ConfigurationProperties指定KafkaProperties前缀

    @Primary
    @ConfigurationProperties(prefix = "lybgeek.kafka.one")
    @Bean
    public KafkaProperties oneKafkaProperties(){
        return new KafkaProperties();
    }
1
2
3
4
5
6

如果有多个就配置多个，形如

    @ConfigurationProperties(prefix = "lybgeek.kafka.two")
    @Bean
    public KafkaProperties twoKafkaProperties(){
        return new KafkaProperties();
    }

    @ConfigurationProperties(prefix = "lybgeek.kafka.three")
    @Bean
    public KafkaProperties threeKafkaProperties(){
        return new KafkaProperties();
    }
1
2
3
4
5
6
7
8
9
10
11

2、配置消费者工厂，消费者工厂绑定对应的KafkaProperties

  @Bean
    public ConsumerFactory twoConsumerFactory(@Autowired @Qualifier("twoKafkaProperties") KafkaProperties twoKafkaProperties){

        return new DefaultKafkaConsumerFactory(twoKafkaProperties.buildConsumerProperties());
    }
1
2
3
4
5

3、配置消费者监听器工厂，并绑定指定消费者工厂以及消费者配置

  @Bean(MultiKafkaConstant.KAFKA_LISTENER_CONTAINER_FACTORY_TWO)
    public KafkaListenerContainerFactory twoKafkaListenerContainerFactory(@Autowired @Qualifier("twoKafkaProperties") KafkaProperties twoKafkaProperties, @Autowired @Qualifier("twoConsumerFactory") ConsumerFactory twoConsumerFactory) {
        ConcurrentKafkaListenerContainerFactory factory = new ConcurrentKafkaListenerContainerFactory();
        factory.setConsumerFactory(twoConsumerFactory);
        factory.setConcurrency(ObjectUtil.isEmpty(twoKafkaProperties.getListener().getConcurrency()) ? Runtime.getRuntime().availableProcessors() : twoKafkaProperties.getListener().getConcurrency());
        factory.getContainerProperties().setAckMode(ObjectUtil.isEmpty(twoKafkaProperties.getListener().getAckMode()) ? ContainerProperties.AckMode.MANUAL:twoKafkaProperties.getListener().getAckMode());

        return factory;
    }

1
2
3
4
5
6
7
8
9
10

完整的配置示例如下

@Configuration
@EnableConfigurationProperties(MultiKafkaComsumeProperties.class)
public class OneKafkaComsumeAutoConfiguration {

    @Bean(MultiKafkaConstant.KAFKA_LISTENER_CONTAINER_FACTORY_ONE)
    public KafkaListenerContainerFactory oneKafkaListenerContainerFactory(@Autowired @Qualifier("oneKafkaProperties") KafkaProperties oneKafkaProperties, @Autowired @Qualifier("oneConsumerFactory") ConsumerFactory oneConsumerFactory) {
        ConcurrentKafkaListenerContainerFactory factory = new ConcurrentKafkaListenerContainerFactory();
        factory.setConsumerFactory(oneConsumerFactory);
        factory.setConcurrency(ObjectUtil.isEmpty(oneKafkaProperties.getListener().getConcurrency()) ? Runtime.getRuntime().availableProcessors() : oneKafkaProperties.getListener().getConcurrency());
        factory.getContainerProperties().setAckMode(ObjectUtil.isEmpty(oneKafkaProperties.getListener().getAckMode()) ? ContainerProperties.AckMode.MANUAL:oneKafkaProperties.getListener().getAckMode());
        return factory;
    }

    @Primary
    @Bean
    public ConsumerFactory oneConsumerFactory(@Autowired @Qualifier("oneKafkaProperties") KafkaProperties oneKafkaProperties){
        return new DefaultKafkaConsumerFactory(oneKafkaProperties.buildConsumerProperties());
    }


    @Primary
    @ConfigurationProperties(prefix = "lybgeek.kafka.one")
    @Bean
    public KafkaProperties oneKafkaProperties(){
        return new KafkaProperties();
    }

}

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29

那个 @Primary要指定一下，不然启动会因为存在多个KafkaProperties,而导致kafka的自动装配不懂要选哪个而报错

@Configuration
@ConditionalOnClass(KafkaTemplate.class)
@EnableConfigurationProperties(KafkaProperties.class)
@Import({ KafkaAnnotationDrivenConfiguration.class, KafkaStreamsAnnotationDrivenConfiguration.class })
public class KafkaAutoConfiguration {

	private final KafkaProperties properties;

	private final RecordMessageConverter messageConverter;

	public KafkaAutoConfiguration(KafkaProperties properties, ObjectProvider<RecordMessageConverter> messageConverter) {
		this.properties = properties;
		this.messageConverter = messageConverter.getIfUnique();
	}

	@Bean
	@ConditionalOnMissingBean(KafkaTemplate.class)
	public KafkaTemplate<?, ?> kafkaTemplate(ProducerFactory<Object, Object> kafkaProducerFactory,
			ProducerListener<Object, Object> kafkaProducerListener) {
		KafkaTemplate<Object, Object> kafkaTemplate = new KafkaTemplate<>(kafkaProducerFactory);
		if (this.messageConverter != null) {
			kafkaTemplate.setMessageConverter(this.messageConverter);
		}
		kafkaTemplate.setProducerListener(kafkaProducerListener);
		kafkaTemplate.setDefaultTopic(this.properties.getTemplate().getDefaultTopic());
		return kafkaTemplate;
	}

	@Bean
	@ConditionalOnMissingBean(ProducerListener.class)
	public ProducerListener<Object, Object> kafkaProducerListener() {
		return new LoggingProducerListener<>();
	}

	@Bean
	@ConditionalOnMissingBean(ConsumerFactory.class)
	public ConsumerFactory<?, ?> kafkaConsumerFactory() {
		return new DefaultKafkaConsumerFactory<>(this.properties.buildConsumerProperties());
	}

	@Bean
	@ConditionalOnMissingBean(ProducerFactory.class)
	public ProducerFactory<?, ?> kafkaProducerFactory() {
		DefaultKafkaProducerFactory<?, ?> factory = new DefaultKafkaProducerFactory<>(
				this.properties.buildProducerProperties());
		String transactionIdPrefix = this.properties.getProducer().getTransactionIdPrefix();
		if (transactionIdPrefix != null) {
			factory.setTransactionIdPrefix(transactionIdPrefix);
		}
		return factory;
	}

	@Bean
	@ConditionalOnProperty(name = "spring.kafka.producer.transaction-id-prefix")
	@ConditionalOnMissingBean
	public KafkaTransactionManager<?, ?> kafkaTransactionManager(ProducerFactory<?, ?> producerFactory) {
		return new KafkaTransactionManager<>(producerFactory);
	}

	@Bean
	@ConditionalOnProperty(name = "spring.kafka.jaas.enabled")
	@ConditionalOnMissingBean
	public KafkaJaasLoginModuleInitializer kafkaJaasInitializer() throws IOException {
		KafkaJaasLoginModuleInitializer jaas = new KafkaJaasLoginModuleInitializer();
		Jaas jaasProperties = this.properties.getJaas();
		if (jaasProperties.getControlFlag() != null) {
			jaas.setControlFlag(jaasProperties.getControlFlag());
		}
		if (jaasProperties.getLoginModule() != null) {
			jaas.setLoginModule(jaasProperties.getLoginModule());
		}
		jaas.setOptions(jaasProperties.getOptions());
		return jaas;
	}

	@Bean
	@ConditionalOnMissingBean
	public KafkaAdmin kafkaAdmin() {
		KafkaAdmin kafkaAdmin = new KafkaAdmin(this.properties.buildAdminProperties());
		kafkaAdmin.setFatalIfBrokerNotAvailable(this.properties.getAdmin().isFailFast());
		return kafkaAdmin;
	}

}

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85

同项目使用多个kafka消费者示例

1、在项目的pom引入spring-kafka GAV

 <dependency>
            <groupId>org.springframework.kafka</groupId>
            <artifactId>spring-kafka</artifactId>
        </dependency>
1
2
3
4

2、在项目的yml中配置如下内容

lybgeek:
    kafka:
        multi:
            comsume-enabled: false
        one:
            producer:
                # kafka生产者服务端地址
                bootstrap-servers: ${KAFKA_PRODUCER_BOOTSTRAP_SERVER:10.1.4.71:32643}
                # 生产者重试的次数
                retries: ${KAFKA_PRODUCER_RETRIES:0}
                # 每次批量发送的数据量
                batch-size: ${KAFKA_PRODUCER_BATCH_SIZE:16384}
                # 每次批量发送消息的缓冲区大小
                buffer-memory: ${KAFKA_PRODUCER_BUFFER_MEMOEY:335554432}
                # 指定消息key和消息体的编码方式
                key-serializer: ${KAFKA_PRODUCER_KEY_SERIALIZER:org.apache.kafka.common.serialization.StringSerializer}
                value-serializer:  ${KAFKA_PRODUCER_KEY_SERIALIZER:org.apache.kafka.common.serialization.StringSerializer}
                # acks=1 只要集群的首领节点收到消息，生产者就会收到一个来自服务器成功响应。
                acks: ${KAFKA_PRODUCER_ACK:1}

            consumer:
                bootstrap-servers: ${KAFKA_ONE_CONSUMER_BOOTSTRAP_SERVER:10.1.4.71:32643}
                # 在偏移量无效的情况下，消费者将从起始位置读取分区的记录
                auto-offset-reset: ${KAFKA_ONE_CONSUMER_AUTO_OFFSET_RESET:earliest}
                #  是否自动提交偏移量，默认值是true,为了避免出现重复数据和数据丢失，可以把它设置为false,然后手动提交偏移量
                enable-auto-commit: ${KAFKA_ONE_CONSUMER_ENABLE_AUTO_COMMIT:false}
                # 指定消息key和消息体的解码方式
                key-deserializer: ${KAFKA_ONE_CONSUMER_KEY_DESERIALIZER:org.apache.kafka.common.serialization.StringDeserializer}
                value-deserializer:  ${KAFKA_ONE_CONSUMER_VALUE_DESERIALIZER:org.apache.kafka.common.serialization.StringDeserializer}
            listener:
                # 在侦听器容器中运行的线程数。
                concurrency: ${KAFKA_ONE_CONSUMER_CONCURRENCY:1}
                missing-topics-fatal: false
                ack-mode: ${KAFKA_ONE_CONSUMER_ACK_MODE:manual}
                
    two:
        producer:
            # kafka生产者服务端地址
            bootstrap-servers: ${KAFKA_PRODUCER_BOOTSTRAP_SERVER:192.168.1.3:9202}
            # 生产者重试的次数
            retries: ${KAFKA_PRODUCER_RETRIES:0}
            # 每次批量发送的数据量
            batch-size: ${KAFKA_PRODUCER_BATCH_SIZE:16384}
            # 每次批量发送消息的缓冲区大小
            buffer-memory: ${KAFKA_PRODUCER_BUFFER_MEMOEY:335554432}
            # 指定消息key和消息体的编码方式
            key-serializer: ${KAFKA_PRODUCER_KEY_SERIALIZER:org.apache.kafka.common.serialization.StringSerializer}
            value-serializer:  ${KAFKA_PRODUCER_KEY_SERIALIZER:org.apache.kafka.common.serialization.StringSerializer}
            # acks=1 只要集群的首领节点收到消息，生产者就会收到一个来自服务器成功响应。
            acks: ${KAFKA_PRODUCER_ACK:1}

            consumer:
                bootstrap-servers: ${KAFKA_ONE_CONSUMER_BOOTSTRAP_SERVER:192.168.1.3:9202}
                # 在偏移量无效的情况下，消费者将从起始位置读取分区的记录
                auto-offset-reset: ${KAFKA_ONE_CONSUMER_AUTO_OFFSET_RESET:earliest}
                #  是否自动提交偏移量，默认值是true,为了避免出现重复数据和数据丢失，可以把它设置为false,然后手动提交偏移量
                enable-auto-commit: ${KAFKA_ONE_CONSUMER_ENABLE_AUTO_COMMIT:false}
                # 指定消息key和消息体的解码方式
                key-deserializer: ${KAFKA_ONE_CONSUMER_KEY_DESERIALIZER:org.apache.kafka.common.serialization.StringDeserializer}
                value-deserializer:  ${KAFKA_ONE_CONSUMER_VALUE_DESERIALIZER:org.apache.kafka.common.serialization.StringDeserializer}
            listener:
                # 在侦听器容器中运行的线程数。
                concurrency: ${KAFKA_ONE_CONSUMER_CONCURRENCY:1}
                missing-topics-fatal: false
                ack-mode: ${KAFKA_ONE_CONSUMER_ACK_MODE:manual}
        
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66

3、配置生产者

 private KafkaTemplate kafkaTemplate;

    @Override
    public MqResp sendSync(MqReq mqReq) {
        ListenableFuture<SendResult<String, String>> result = this.send(mqReq);
        MqResp mqResp = this.buildMqResp(result);
        return mqResp;
    }

1
2
3
4
5
6
7
8
9

这个KafkaTemplate绑定的就是@Primary配置的kafkaProperties

4、配置消费者监听,并绑定containerFactory

@LybGeekKafkaListener(id = "createUser",containerFactory = MultiKafkaConstant.KAFKA_LISTENER_CONTAINER_FACTORY_ONE,topics = Constant.USER_TOPIC)
public class UserComsumer extends BaseComusmeListener {

    @Autowired
    private UserService userService;

    @Override
    public boolean isRepeateConsume(KafkaComsumePayLoad kafkaComsumePayLoad) {
        User user = JSON.parseObject(kafkaComsumePayLoad.getData(),User.class);
        System.out.println("-----------------------");
        return userService.isExistUserByUsername(user.getUsername());
    }

    @Override
    public boolean doBiz(KafkaComsumePayLoad kafkaComsumerPayLoad) {
        User user = JSON.parseObject(kafkaComsumerPayLoad.getData(),User.class);
        System.out.println(user);
        return userService.save(user);
    }
}
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

通过指定containerFactory ，来消费指定的kafka消息

5、测试

  User user = User.builder().username("test")
                .email("test@qq.com")
                .fullname("test")
                .mobile("1350000001")
                .password("1234561")
                .build();
      userService.saveAndPush(user);
1
2
3
4
5
6
7

发送消息，观察控制台输出

: messageKey:【null】，topic：【user-sync】存在重复消息数据-->【{"email":"test@qq.com","fullname":"test","mobile":"1350000000","password":"123456","username":"test"}】
1

会出现这样，是因为数据库已经有这条记录了，刚好验证一下重复消费

总结

本文实现的核心其实就是通过注入多个kafkaProperties来实现多配置 ，不知道大家有没有发现，就是改造后的配置，配置消费者后，生产者仍然也要配置。因为如果不配置，走的就是kafkaProperties默认的配置信息，即为localhost。还有细心的朋友也许会发现我示例中的消费者监听使用的注解是@LybGeekKafkaListener，这个和 @KafkaListener实现的功能基本一致。因为本示例和之前的文章聊聊如何实现一个带幂等模板的kafka消费者监听是同份代码，就直接复用了

demo链接

https://github.com/lyb-geek/springboot-learning/tree/master/springboot-kafka-template