将Kafka Streams与Serde结合使用，这些Serde依赖于标头中的架构引用

我正在尝试使用Kafka Streams对CDC数据执行KTable-KTable外键联接。我将读取的数据是Avro格式的，但是它被序列化的方式与其他行业序列化程序/反序列化程序(例如。合流架构注册表)，因为架构标识符存储在标头中。

当我设置KTables的Serdes时，我的Kafka Streams应用程序最初运行，但最终失败，因为它在内部调用了带有byte[] serialize(String topic, T data);的序列化程序方法，而不是带有标头的方法(即。byte[] serialize(String topic, Headers headers, T data)在包装序列化程序ValueAndTimestampSerializer中。我正在使用的Serdes无法处理此问题并引发异常。

第一个问题是，有没有人知道如何恳求Kafka Streams在内部调用带有正确方法签名的方法？

我正在探索解决这个问题的方法，包括编写新的Serde，用消息本身中的模式标识符重新序列化。这可能涉及将数据重新复制到新主题或使用拦截器。

但是，我知道ValueTransformer可以访问ProcessorContext中的标头，我想知道是否有更快的方法使用transformValues()。其想法是首先将该值作为byte[]读取，然后将该值反序列化为转换器中的Avro类(请参见下面的示例)。但是，当我这样做时，我会得到一个例外。

StreamsBuilder builder = new StreamsBuilder();
 final KTable<Long, MySpecificClass> myTable = builder.table(
      "my-topic",
       Consumed.with(Serdes.Long(), Serdes.ByteArray())
    )
    .transformValues(MyDeserializerTransformer::new);

 ...

 KTable<Long, JoinResult> joinResultTable = myTable.join(rightTable, MySpecificClass::getJoinKey, myValueJoiner);

 joinResultTable.toStream()...

public class MyDeserializerTransformer implements
    ValueTransformerWithKey<Long, byte[], MySpecificClass> {
  MyAvroDeserializer deserializer;
  ProcessorContext context;

  @Override
  public void init(ProcessorContext context) {
    deserializer = new MyAvroDeserializer();
    this.context = context;
  }

  @Override
  public MySpecificClass transform(Long key, byte[] value) {
    return deserializer.deserialize(context.topic(), context.headers(), value);
  }

  @Override
  public void close() {

  }
}

当我运行它时，我收到一个ClassCastException。我如何解决此问题或找到解决方法？我需要使用辅助状态存储吗？

"class": "org.apache.kafka.streams.errors.StreamsException",
    "msg": "ClassCastException invoking Processor. Do the Processor's input types match the deserialized types? Check the Serde setup and change the default Serdes in StreamConfig or provide correct Serdes via method parameters. Make sure the Processor can accept the deserialized input of type key: java.lang.Long, and value: org.apache.kafka.streams.kstream.internals.Change.
Note that although incorrect Serdes are a common cause of error, the cast exception might have another cause (in user code, for example). For example, if a processor wires in a store, but casts the generics incorrectly, a class cast exception could be raised during processing, but the cause would not be wrong Serdes.",
    "stack": [
      "org.apache.kafka.streams.processor.internals.ProcessorNode.process(ProcessorNode.java:185)",
      "org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forwardInternal(ProcessorContextImpl.java:281)",
      "org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(ProcessorContextImpl.java:260)",
      "org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(ProcessorContextImpl.java:219)",
      "org.apache.kafka.streams.processor.internals.ProcessorContextImpl.forward(ProcessorContextImpl.java:172)",
      "org.apache.kafka.streams.kstream.internals.KTableTransformValues$KTableTransformValuesProcessor.process(KTableTransformValues.java:117)",
      "org.apache.kafka.streams.kstream.internals.KTableTransformValues$KTableTransformValuesProcessor.process(KTableTransformValues.java:87)",
      "org.apache.kafka.streams.processor.internals.ProcessorAdapter.process(ProcessorAdapter.java:71)",
      "org.apache.kafka.streams.processor.internals.ProcessorNode.lambda$process$2(ProcessorNode.java:181)",
      "org.apache.kafka.streams.processor.internals.metrics.StreamsMetricsImpl.maybeMeasureLatency(StreamsMetricsImpl.java:884)",
      "org.apache.kafka.streams.processor.internals.ProcessorNode.process(ProcessorNode.java:181)",
...
"cause": {
 "class": "java.lang.ClassCastException",
      "msg": "class com.package.MySpecificClass cannot be cast to class [B (com.package.MySpecificClass is in unnamed module of loader 'app'; [B is in module java.base of loader 'bootstrap')",
      "stack": [
        "org.apache.kafka.common.serialization.ByteArraySerializer.serialize(ByteArraySerializer.java:19)",
        "org.apache.kafka.streams.kstream.internals.foreignkeyjoin.ForeignJoinSubscriptionSendProcessorSupplier$UnbindChangeProcessor.process(ForeignJoinSubscriptionSendProcessorSupplier.java:102)",
        "org.apache.kafka.streams.kstream.internals.foreignkeyjoin.ForeignJoinSubscriptionSendProcessorSupplier$UnbindChangeProcessor.process(ForeignJoinSubscriptionSendProcessorSupplier.java:72)",
        "org.apache.kafka.streams.processor.internals.ProcessorAdapter.process(ProcessorAdapter.java:71)",
        "org.apache.kafka.streams.processor.internals.ProcessorNode.lambda$process$2(ProcessorNode.java:181)",
        "org.apache.kafka.streams.processor.internals.metrics.StreamsMetricsImpl.maybeMeasureLatency(StreamsMetricsImpl.java:884)",
        "org.apache.kafka.streams.processor.internals.ProcessorNode.process(ProcessorNode.java:181)",

---

解决方案

我能够通过以下方法解决此问题：首先将输入主题作为KStream读取，然后将其转换为具有不同Serde的KTable。第二步，状态存储似乎遇到了未调用带有标头的序列化程序/反序列化程序方法签名的问题。