我想创建一个通用的avro反序列化程序，并与kafka/flink一起使用。
为此，我必须从flink api扩展反序列化模式：

import java.io.ByteArrayInputStream

import com.sksamuel.avro4s.{AvroInputStream, FromRecord, SchemaFor, ToRecord}
import org.apache.flink.api.common.serialization.DeserializationSchema
import org.apache.flink.api.common.typeinfo.TypeInformation
import org.apache.flink.api.java.typeutils.TypeExtractor

class FidesGenericAvroDeserializer[T](implicit schema: SchemaFor[T], toRecord: ToRecord[T], fromRecord: FromRecord[T])
  extends DeserializationSchema[T] {

  override def isEndOfStream(nextElement: T): Boolean = false

  override def deserialize(message: Array[Byte]): T = {
    AvroInputStream.binary[T](new ByteArrayInputStream(message)).iterator.toSeq.head
  }

  override def getProducedType: TypeInformation[T] = TypeExtractor.getForClass(classOf[T])
}

这样做会导致编译时出现问题，因为t似乎不是类：

class type required but T found
override def getProducedType: TypeInformation[T] = TypeExtractor.getForClass(classOf[T])