是否可以在没有在ConfluentRegistryAvroDeserializationSchema中给出Reader模式的情况下反序列化Avro消息(使用来自Kafka的消息)

问题描述

我正在使用Apache Flink中的Kafka连接器来访问 Confluent Kafka 服务的流.

I am using Kafka Connector in Apache Flink for access to streams served by Confluent Kafka.

除架构注册表URL ConfluentRegistryAvroDeserializationSchema.forGeneric(...)外，期望使用读取器"架构.我不想提供读取的架构，而是要使用相同的编写者的架构(在注册表中查找)来读取消息，因为Consumer将没有最新的架构.

Apart from schema registry url ConfluentRegistryAvroDeserializationSchema.forGeneric(...) expecting 'reader' schema. Instead of providing read schema I want to use same writer's schema(lookup in registry) for reading the message too because Consumer will not have latest schema.

FlinkKafkaConsumer010<GenericRecord> myConsumer =
        new FlinkKafkaConsumer010<>("topic-name", ConfluentRegistryAvroDeserializationSchema.forGeneric(<reader schema goes here>, "http://host:port"), properties);
myConsumer.setStartFromLatest();

https://ci .apache.org/projects/flink/flink-docs-release-1.9/dev/connectors/kafka.html 使用这些反序列化模式记录将与从Schema Registry检索并转换为静态提供的模式一起读取".

https://ci.apache.org/projects/flink/flink-docs-release-1.9/dev/connectors/kafka.html"Using these deserialization schema record will be read with the schema that was retrieved from Schema Registry and transformed to a statically provided"

由于我不想保留用户端的架构定义，如何使用编写者的架构反序列化来自Kafka的Avro消息?

Since I do not want to keep schema definition at consumer side how do I deserialize Avro message from Kafka using writer's schema?

感谢您的帮助！

推荐答案

我认为无法直接使用ConfluentRegistryAvroDeserializationSchema.forGeneric.它旨在与阅读器架构一起使用，并且它们具有对此进行检查的前提条件.

I don't think it is possible to use directly ConfluentRegistryAvroDeserializationSchema.forGeneric. It is intended to be used with a reader schema and they have preconditions checking for this.

您必须实现自己的.导入两个东西:

You have to implement your own. Two import things:

• 将specific.avro.reader设置为false(否则将获得特定记录)
• KafkaAvroDeserializer必须延迟初始化(因为它本身无法序列化，因为它拥有对架构注册表客户端的引用)

• Set specific.avro.reader to false (other wise you'll get specific records)
• The KafkaAvroDeserializer has to be lazily initialized (because it isn't serializable it self, as it holds a reference to the schema registry client)

import io.confluent.kafka.schemaregistry.client.CachedSchemaRegistryClient;
import io.confluent.kafka.schemaregistry.client.SchemaRegistryClient;
import io.confluent.kafka.serializers.AbstractKafkaAvroSerDeConfig;
import io.confluent.kafka.serializers.KafkaAvroDeserializer;
import io.confluent.kafka.serializers.KafkaAvroDeserializerConfig;
import java.util.HashMap;
import java.util.Map;
import org.apache.avro.generic.GenericRecord;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.api.java.typeutils.TypeExtractor;
import org.apache.flink.streaming.util.serialization.KeyedDeserializationSchema;

public class KafkaGenericAvroDeserializationSchema
    implements KeyedDeserializationSchema<GenericRecord> {

  private final String registryUrl;
  private transient KafkaAvroDeserializer inner;

  public KafkaGenericAvroDeserializationSchema(String registryUrl) {
    this.registryUrl = registryUrl;
  }

  @Override
  public GenericRecord deserialize(
      byte[] messageKey, byte[] message, String topic, int partition, long offset) {
    checkInitialized();
    return (GenericRecord) inner.deserialize(topic, message);
  }

  @Override
  public boolean isEndOfStream(GenericRecord nextElement) {
    return false;
  }

  @Override
  public TypeInformation<GenericRecord> getProducedType() {
    return TypeExtractor.getForClass(GenericRecord.class);
  }

  private void checkInitialized() {
    if (inner == null) {
      Map<String, Object> props = new HashMap<>();
      props.put(AbstractKafkaAvroSerDeConfig.SCHEMA_REGISTRY_URL_CONFIG, registryUrl);
      props.put(KafkaAvroDeserializerConfig.SPECIFIC_AVRO_READER_CONFIG, false);
      SchemaRegistryClient client =
          new CachedSchemaRegistryClient(
              registryUrl, AbstractKafkaAvroSerDeConfig.MAX_SCHEMAS_PER_SUBJECT_DEFAULT);
      inner = new KafkaAvroDeserializer(client, props);
    }
  }
}

env.addSource(
  new FlinkKafkaConsumer<>(
    topic, 
    new KafkaGenericAvroDeserializationSchema(schemaReigstryUrl), 
    kafkaProperties));

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