我正在使用flink(1.7)kafka客户端和Avro4s(2.0.4),我想序列化为字节数组:
class AvroSerializationSchema[IN : SchemaFor : FromRecord: ToRecord] extends SerializationSchema[IN] {
override def serialize(element: IN): Array[Byte] = {
val str = AvroSchema[IN]
val schema: Schema = new Parser().parse(str.toString)
val out = new ByteArrayOutputStream()
val os = AvroOutputStream.data[IN].to(out).build(schema)
os.write(element)
out.close()
out.flush()
os.flush()
os.close()
out.toByteArray
}
}
但是我一直收到此异常:
Error:(15, 35) could not find implicit value for evidence parameter of type com.sksamuel.avro4s.Encoder[IN]
val os = AvroOutputStream.data[IN].to(out).build(schema)
和
Error:(15, 35) not enough arguments for method data: (implicit evidence$3: com.sksamuel.avro4s.Encoder[IN])com.sksamuel.avro4s.AvroOutputStreamBuilder[IN].
Unspecified value parameter evidence$3.
val os = AvroOutputStream.data[IN].to(out).build(schema)
答案 0 :(得分:1)
根据代码IN
必须为Encoder
类型:
object AvroOutputStream {
/**
* An [[AvroOutputStream]] that does not write the schema. Use this when
* you want the smallest messages possible at the cost of not having the schema available
* in the messages for downstream clients.
*/ def binary[T: Encoder] = new AvroOutputStreamBuilder[T](BinaryFormat)
def json[T: Encoder] = new AvroOutputStreamBuilder[T](JsonFormat)
def data[T: Encoder] = new AvroOutputStreamBuilder[T](DataFormat)
}
因此它应该类似于:
class AvroSerializationSchema[IN : Encoder] ...
答案 1 :(得分:1)
写入输出流时,无需使用FromRecord
。那是针对那些想要拥有GenericRecord
供自己使用的人的。您需要使用Encoder
。
class AvroSerializationSchema[IN : SchemaFor : Encoder] extends SerializationSchema[IN] {
override def serialize(element: IN): Array[Byte] = {
val str = AvroSchema[IN]
val schema: Schema = new Parser().parse(str.toString)
val out = new ByteArrayOutputStream()
val os = AvroOutputStream.data[IN].to(out).build(schema)
os.write(element)
out.close()
out.flush()
os.flush()
os.close()
out.toByteArray
}
}