Spring Kafka、Spring Cloud Stream 和 Avro 兼容性未知魔法字节

Spring Kafka, Spring Cloud Stream, and Avro compatibility Unknown magic byte

我在反序列化来自 Kafka 主题的消息时遇到问题。消息已使用 spring-cloud-stream 和 Apache Avro 序列化。我正在使用 Spring Kafka 阅读它们并尝试反序列化它们。如果我使用 spring-cloud 来生成和使用消息,那么我可以很好地反序列化消息。问题是当我使用 Spring Kafka 使用它们然后尝试反序列化时。

我正在使用架构注册表(用于开发的 spring-boot 架构注册表,以及生产中的 Confluent 架构),但反序列化问题似乎发生在事件调用架构注册表之前。

很难 post 这个问题的所有相关代码,所以我 post 在 git 中心的回购中编辑了它:https://github.com/robjwilkins/avro-example

我在主题中发送的对象只是一个简单的 pojo:

@Data
public class Request {
  private String message;
}

在 Kafka 上生成消息的代码如下所示:

@EnableBinding(MessageChannels.class)
@Slf4j
@RequiredArgsConstructor
@RestController
public class ProducerController {

  private final MessageChannels messageChannels;

  @GetMapping("/produce")
  public void produceMessage() {
    Request request = new Request();
    request.setMessage("hello world");
    Message<Request> requestMessage = MessageBuilder.withPayload(request).build();
    log.debug("sending message");
    messageChannels.testRequest().send(requestMessage);
  }
}

和application.yaml:

spring:
  application.name: avro-producer
  kafka:
    bootstrap-servers: localhost:9092
    consumer.group-id: avro-producer
  cloud:
    stream:
      schema-registry-client.endpoint: http://localhost:8071
      schema.avro.dynamic-schema-generation-enabled: true
      kafka:
        binder:
          brokers: ${spring.kafka.bootstrap-servers}
      bindings:
        test-request:
          destination: test-request
          contentType: application/*+avro

那我有一个消费者:

@Slf4j
@Component
public class TopicListener {

    @KafkaListener(topics = {"test-request"})
    public void listenForMessage(ConsumerRecord<String, Request> consumerRecord) {
        log.info("listenForMessage. got a message: {}", consumerRecord);
        consumerRecord.headers().forEach(header -> log.info("header. key: {}, value: {}", header.key(), asString(header.value())));
    }

    private String asString(byte[] byteArray) {
        return new String(byteArray, Charset.defaultCharset());
    }
}

并且消费的项目有application.yaml配置:

spring:
  application.name: avro-consumer
  kafka:
    bootstrap-servers: localhost:9092
    consumer:
      group-id: avro-consumer
      value-deserializer: io.confluent.kafka.serializers.KafkaAvroDeserializer
#      value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
      key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
      properties:
        schema.registry.url: http://localhost:8071

当消费者收到一条消息时,它会导致异常:

2019-01-30 20:01:39.900 ERROR 30876 --- [ntainer#0-0-C-1] o.s.kafka.listener.LoggingErrorHandler   : Error while processing: null

org.apache.kafka.common.errors.SerializationException: Error deserializing key/value for partition test-request-0 at offset 43. If needed, please seek past the record to continue consumption.
Caused by: org.apache.kafka.common.errors.SerializationException: Error deserializing Avro message for id -1
Caused by: org.apache.kafka.common.errors.SerializationException: Unknown magic byte!

我已经完成了反序列化代码到抛出这个异常的地步

public abstract class AbstractKafkaAvroDeserializer extends AbstractKafkaAvroSerDe {
....
private ByteBuffer getByteBuffer(byte[] payload) {
  ByteBuffer buffer = ByteBuffer.wrap(payload);
  if (buffer.get() != 0) {
    throw new SerializationException("Unknown magic byte!");
  } else {
    return buffer;
  }
}

这是因为反序列化器检查序列化对象(字节数组)的字节内容并期望它为 0,但事实并非如此。因此,我质疑序列化对象的 spring-cloud-stream MessageConverter 是否与我用来反序列化对象的 io.confluent 对象兼容。如果它们不兼容,我该怎么办?

感谢您的帮助。

您应该通过在配置中创建 DefaultKafkaConsumerFactory 和您的 TopicListener bean 来显式定义反序列化器,如下所示:

@Configuration
@EnableKafka
public class TopicListenerConfig {

@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.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
    props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, JsonDeserializer.class);
    props.put(ConsumerConfig.GROUP_ID_CONFIG, groupId);
    props.put(JsonDeserializer.TRUSTED_PACKAGES, "com.wilkins.avro.consumer");
    props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");

    return props;
}

@Bean
public ConsumerFactory<String, String> consumerFactory() {
    return new DefaultKafkaConsumerFactory<>(consumerConfigs());
}

@Bean
public KafkaListenerContainerFactory<ConcurrentMessageListenerContainer<String, String>> kafkaListenerContainerFactory() {
    ConcurrentKafkaListenerContainerFactory<String, String> factory =
            new ConcurrentKafkaListenerContainerFactory<>();
    factory.setConsumerFactory(consumerFactory());

    return factory;
}

@Bean
public TopicListener topicListener() {
    return new TopicListener();
}
}

您可以将绑定配置为在本机使用 Kafka 序列化程序。

将生产者 属性 useNativeEncoding 设置为 true 并使用 ...producer.configuration Kafka 属性配置序列化器。

编辑

示例:

spring:
  cloud:
    stream:
# Generic binding properties
      bindings:
        input:
          consumer:
            use-native-decoding: true
          destination: so54448732
          group: so54448732
        output:
          destination: so54448732
          producer:
            use-native-encoding: true
# Kafka-specific binding properties
      kafka:
        bindings:
          input:
            consumer:
              configuration:
                value.deserializer: com.example.FooDeserializer
          output:
            producer:
              configuration:
                value.serializer: com.example.FooSerializer

这个问题的症结在于生产者使用spring-cloud-stream将post消息发送到Kafka,而消费者使用spring-kaka。原因是:

  • 现有系统已经完善,使用spring-cloud-stream
  • 新消费者需要使用相同的方法收听多个主题,仅绑定到主题名称的 csv 列表
  • 需要一次使用一组消息,而不是单独使用,因此它们的内容可以批量写入数据库。

Spring-cloud-stream 当前不允许消费者将一个侦听器绑定到多个主题,并且无法一次使用一组消息(除非我弄错了)。

我找到了一个解决方案,它不需要对使用 spring-cloud-stream 将消息发布到 Kafka 的生产者代码进行任何更改。 Spring-cloud-stream 使用 MessageConverter 来管理序列化和反序列化。在 AbstractAvroMessageConverter 中有方法:convertFromInternalconvertToInternal 处理转换 to/from 字节数组。我的解决方案是扩展此代码(创建扩展 AvroSchemaRegistryClientMessageConverter 的 class),因此我可以重用大部分 spring-cloud-stream 功能,但具有可访问的接口来自我的 spring-kafka KafkaListener。然后我修改了我的 TopicListener 以使用此 class 进行转换:

转换器:

@Component
@Slf4j
public class AvroKafkaMessageConverter extends AvroSchemaRegistryClientMessageConverter {

  public AvroKafkaMessageConverter(SchemaRegistryClient schemaRegistryClient) {
    super(schemaRegistryClient, new NoOpCacheManager());
  }

  public <T> T convertFromInternal(ConsumerRecord<?, ?> consumerRecord, Class<T> targetClass,
      Object conversionHint) {
    T result;
    try {
      byte[] payload = (byte[]) consumerRecord.value();

      Map<String, String> headers = new HashMap<>();
      consumerRecord.headers().forEach(header -> headers.put(header.key(), asString(header.value())));

      MimeType mimeType = messageMimeType(conversionHint, headers);
      if (mimeType == null) {
        return null;
      }

      Schema writerSchema = resolveWriterSchemaForDeserialization(mimeType);
      Schema readerSchema = resolveReaderSchemaForDeserialization(targetClass);

      @SuppressWarnings("unchecked")
      DatumReader<Object> reader = getDatumReader((Class<Object>) targetClass, readerSchema, writerSchema);
      Decoder decoder = DecoderFactory.get().binaryDecoder(payload, null);
      result = (T) reader.read(null, decoder);
    }
    catch (IOException e) {
      throw new RuntimeException("Failed to read payload", e);
    }
    return result;
  }

  private MimeType messageMimeType(Object conversionHint, Map<String, String> headers) {
    MimeType mimeType;
    try {
      String contentType = headers.get(MessageHeaders.CONTENT_TYPE);
      log.debug("contentType: {}", contentType);
      mimeType = MimeType.valueOf(contentType);
    } catch (InvalidMimeTypeException e) {
      log.error("Exception getting object MimeType from contentType header", e);
      if (conversionHint instanceof MimeType) {
        mimeType = (MimeType) conversionHint;
      }
      else {
        return null;
      }
    }
    return mimeType;
  }

  private String asString(byte[] byteArray) {
    String theString = new String(byteArray, Charset.defaultCharset());
    return theString.replace("\"", "");
  }
}

修改后TopicListener

@Slf4j
@Component
@RequiredArgsConstructor
public class TopicListener {

  private final AvroKafkaMessageConverter messageConverter;

  @KafkaListener(topics = {"test-request"})
  public void listenForMessage(ConsumerRecord<?, ?> consumerRecord) {
    log.info("listenForMessage. got a message: {}", consumerRecord);
    Request request = messageConverter.convertFromInternal(
        consumerRecord, Request.class, MimeType.valueOf("application/vnd.*+avr"));
    log.info("request message: {}", request.getMessage());
  }
}

此解决方案一次仅使用一条消息,但可以轻松修改以使用成批消息。

完整的解决方案在这里:https://github.com/robjwilkins/avro-example/tree/develop

感谢这让我使用 nativeencoding 和 spring 节省了时间: 云: 流:

通用绑定属性

  bindings:
    input:
      consumer:
        use-native-decoding: true
      destination: so54448732
      group: so54448732
    output:
      destination: so54448732
      producer:
        use-native-encoding: true

Kafka 特定的绑定属性

  kafka:
    bindings:
      input:
        consumer:
          configuration:
            value.deserializer: com.example.FooDeserializer
      output:
        producer:
          configuration:
            value.serializer: com.example.FooSerializer