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Re: KafkaProducer with generic (Avro) serialization schema


Thanks for the suggestions.

Unfortunately I cannot make FromRecord/ForRecord/SchemaFor serializable, since those classes are out of my control. I use those from the avro4s library (https://github.com/sksamuel/avro4s). The problem here, especially with the deserializer is that I need to convert an Avro 'GenericRecord' to a Scala case class. Avro is written in Java, so thats a bit problematic and therefore I need to Avro4s library. Avro4s tries to verify on compile-time if the generic is actually convertible from/to a generic record, that is why I need those context bounds. 

As for @Aljoscha's workaround, I don't understand how this would solve it? Because doesn't that just move the problem? If I create a factory, I still need the generic (with context bounds) I specify at my KafkaConsumer/Deserialization schema.

@Fabian I'm not sure if I understand your proposal. I still need the context bounds for those compile-time macro's of Avro4s. 

Once again, thanks for your help so far!


Op wo 2 mei 2018 om 16:48 schreef Fabian Hueske <fhueske@xxxxxxxxx>:
Hi Wouter,

you can try to make the SerializationSchema serializable by overriding Java's serialization methods writeObject() and readObject() similar as Flink's AvroRowSerializationSchema [1] does.

2018-05-02 16:34 GMT+02:00 Piotr Nowojski <piotr@xxxxxxxxxxxxxxxxx>:

My Scala knowledge is very limited (and my Scala's serialization knowledge is non existent), but one way or another you have to make your SerializationSchema serialisable. If indeed this is the problem, maybe a better place to ask this question is on Stack Overflow or some scala specific mailing list/board (unless someone else from the Flink's community can provide an answer to this problem)? 


On 1 May 2018, at 16:30, Wouter Zorgdrager <zorgdragerw@xxxxxxxxx> wrote:

So, I'm still struggling with this issue. I dived a bit more into the problem and I'm pretty sure that the problem is that I have to (implicitly) pass the SchemaFor and RecordTo classes to my serialization schema (otherwise I can't make it generic). However those class aren't serializable, but of course I can't annotate them transient nor make it a lazy val which gives me the current issue. 

I hope someone has some leads for me. 


Op do 26 apr. 2018 om 23:03 schreef Wouter Zorgdrager <zorgdragerw@xxxxxxxxx>:
Hi Bill,

Thanks for your answer. However this proposal isn't going to solve my issue, since the problem here is that the context bounds I need to give in order to serialize it to Avro (SchemaFor, ToRecord and FromRecord) aren't serializable classes. This results in Flink not being able to serialize the KafkaProducer failing the whole job. 


Op do 26 apr. 2018 om 00:42 schreef Nortman, Bill <William.Nortman@xxxxxxxxx>:

The things I would try would first in you are you class Person and Address have getters and setters and a no argument constructor.


From: Wouter Zorgdrager [mailto:zorgdragerw@xxxxxxxxx]
Sent: Wednesday, April 25, 2018 7:17 AM
To: user@xxxxxxxxxxxxxxxx
Subject: KafkaProducer with generic (Avro) serialization schema


Dear reader,


I'm currently working on writing a KafkaProducer which is able to serialize a generic type using avro4s.

However this serialization schema is not serializable itself. Here is my code for this:


The serialization schema:

class AvroSerializationSchema[IN : SchemaFor : FromRecord: ToRecord] extends SerializationSchema[IN] {


  override def serialize(element: IN): Array[Byte] = {

    val byteArray = new ByteArrayOutputStream()

    val avroSer = AvroOutputStream.binary[IN](byteArray)





    return byteArray.toByteArray




The job code:

case class Person(name : String, age : Int, address : Address)

case class Address(city : String, street : String)


class SimpleJob {



  private lazy val serSchema : AvroSerializationSchema[Person] = new AvroSerializationSchema[Person]()


  def start() = {

    val testPerson = Person("Test", 100, Address("Test", "Test"))


    val env = StreamExecutionEnvironment.getExecutionEnvironment






    env.execute("Flink sample job")




  def createKafkaSink() : RichSinkFunction[Person] = {

    //set some properties

    val properties = new Properties()

    properties.put("bootstrap.servers", "")

    properties.put("zookeeper.connect", "")


    new FlinkKafkaProducer011[Person]("persons", serSchema, properties)





The code does compile, however it gives the following error on runtime: InvalidProgramException: Object org.apache.flink.streaming.util.serialization.KeyedSerializationSchemaWrapper@639c2c1d is not serializable.


I assume this means that my custom SerializationSchema is not serializable due to the use of SchemaFor, FromRecord and ToRecord. 

Anyone knows a solution or workaround?


Thanks in advance!


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