How to ensure constant Avro schema generation and avoid the 'Too many schema objects created for x' exception?

Question

I am experiencing a reproducible error while producing Avro messages with reactive kafka and avro4s. Once the identityMapCapacity of the client (CachedSchemaRegistryClient) is reached, serialization fails with

java.lang.IllegalStateException: Too many schema objects created for <myTopic>-value

This is unexpected, since all messages should have the same schema - they are serializations of the same case class.

val avroProducerSettings: ProducerSettings[String, GenericRecord] = 
  ProducerSettings(system, Serdes.String().serializer(), 
  avroSerde.serializer())
 .withBootstrapServers(settings.bootstrapServer)

val avroProdFlow: Flow[ProducerMessage.Message[String, GenericRecord, String],
                    ProducerMessage.Result[String, GenericRecord, String],
                    NotUsed] = Producer.flow(avroProducerSettings)

val avroQueue: SourceQueueWithComplete[Message[String, GenericRecord, String]] = 
  Source.queue(bufferSize, overflowStrategy)
  .via(avroProdFlow)
  .map(logResult)
  .to(Sink.ignore)
  .run()

...
queue.offer(msg)

The serializer is a KafkaAvroSerializer, instantiated with a new CachedSchemaRegistryClient(settings.schemaRegistry, 1000)

Generating the GenericRecord:

def toAvro[A](a: A)(implicit recordFormat: RecordFormat[A]): GenericRecord =
  recordFormat.to(a)

val makeEdgeMessage: (Edge, String) => Message[String, GenericRecord, String] = { (edge, topic) =>
  val edgeAvro: GenericRecord = toAvro(edge)
  val record   = new ProducerRecord[String, GenericRecord](topic, edge.id, edgeAvro)
  ProducerMessage.Message(record, edge.id)
}

The schema is created deep in the code (io.confluent.kafka.serializers.AbstractKafkaAvroSerDe#getSchema, invoked by io.confluent.kafka.serializers.AbstractKafkaAvroSerializer#serializeImpl) where I have no influence on it, so I have no idea how to fix the leak. Looks to me like the two confluent projects do not work well together.

The issues I have found here, here and here do not seem to address my use case.

The two workarounds for me are currently:

• not use schema registry - not a long-term solution obviously
• create custom SchemaRegistryClient not relying on object identity - doable but I would like to avoid creating more issues than by reimplementing

Is there a way to generate or cache a consistent schema depending on message/record type and use it with my setup?

Answer 1

edit 2017.11.20

The issue in my case was that each instance of GenericRecord carrying my message has been serialized by a different instance of RecordFormat, containing a different instance of the Schema. The implicit resolution here generated a new instance each time.

def toAvro[A](a: A)(implicit recordFormat: RecordFormat[A]): GenericRecord = recordFormat.to(a)

The solution was to pin the RecordFormat instance to a val and reuse it explicitly. Many thanks to https://github.com/heliocentrist for explaining the details.

original response:

After waiting for a while (also no answer for the github issue) I had to implement my own SchemaRegistryClient. Over 90% is copied from the original CachedSchemaRegistryClient, just translated into scala. Using a scala mutable.Map fixed the memory leak. I have not performed any comprehensive tests, so use at your own risk.

import java.util

import io.confluent.kafka.schemaregistry.client.rest.entities.{ Config, SchemaString }
import io.confluent.kafka.schemaregistry.client.rest.entities.requests.ConfigUpdateRequest
import io.confluent.kafka.schemaregistry.client.rest.{ RestService, entities }
import io.confluent.kafka.schemaregistry.client.{ SchemaMetadata, SchemaRegistryClient }
import org.apache.avro.Schema

import scala.collection.mutable

class CachingSchemaRegistryClient(val restService: RestService, val identityMapCapacity: Int)
    extends SchemaRegistryClient {

  val schemaCache: mutable.Map[String, mutable.Map[Schema, Integer]] = mutable.Map()
  val idCache: mutable.Map[String, mutable.Map[Integer, Schema]] =
    mutable.Map(null.asInstanceOf[String] -> mutable.Map())
  val versionCache: mutable.Map[String, mutable.Map[Schema, Integer]] = mutable.Map()

  def this(baseUrl: String, identityMapCapacity: Int) {
    this(new RestService(baseUrl), identityMapCapacity)
  }

  def this(baseUrls: util.List[String], identityMapCapacity: Int) {
    this(new RestService(baseUrls), identityMapCapacity)
  }

  def registerAndGetId(subject: String, schema: Schema): Int =
    restService.registerSchema(schema.toString, subject)

  def getSchemaByIdFromRegistry(id: Int): Schema = {
    val restSchema: SchemaString = restService.getId(id)
    (new Schema.Parser).parse(restSchema.getSchemaString)
  }

  def getVersionFromRegistry(subject: String, schema: Schema): Int = {
    val response: entities.Schema = restService.lookUpSubjectVersion(schema.toString, subject)
    response.getVersion.intValue
  }

  override def getVersion(subject: String, schema: Schema): Int = synchronized {
    val schemaVersionMap: mutable.Map[Schema, Integer] =
      versionCache.getOrElseUpdate(subject, mutable.Map())

    val version: Integer = schemaVersionMap.getOrElse(
      schema, {
        if (schemaVersionMap.size >= identityMapCapacity) {
          throw new IllegalStateException(s"Too many schema objects created for $subject!")
        }

        val version = new Integer(getVersionFromRegistry(subject, schema))
        schemaVersionMap.put(schema, version)
        version
      }
    )
    version.intValue()
  }

  override def getAllSubjects: util.List[String] = restService.getAllSubjects()

  override def getByID(id: Int): Schema = synchronized { getBySubjectAndID(null, id) }

  override def getBySubjectAndID(subject: String, id: Int): Schema = synchronized {
    val idSchemaMap: mutable.Map[Integer, Schema] = idCache.getOrElseUpdate(subject, mutable.Map())
    idSchemaMap.getOrElseUpdate(id, getSchemaByIdFromRegistry(id))
  }

  override def getSchemaMetadata(subject: String, version: Int): SchemaMetadata = {
    val response = restService.getVersion(subject, version)
    val id       = response.getId.intValue
    val schema   = response.getSchema
    new SchemaMetadata(id, version, schema)
  }

  override def getLatestSchemaMetadata(subject: String): SchemaMetadata = synchronized {
    val response = restService.getLatestVersion(subject)
    val id       = response.getId.intValue
    val version  = response.getVersion.intValue
    val schema   = response.getSchema
    new SchemaMetadata(id, version, schema)
  }

  override def updateCompatibility(subject: String, compatibility: String): String = {
    val response: ConfigUpdateRequest = restService.updateCompatibility(compatibility, subject)
    response.getCompatibilityLevel
  }

  override def getCompatibility(subject: String): String = {
    val response: Config = restService.getConfig(subject)
    response.getCompatibilityLevel
  }

  override def testCompatibility(subject: String, schema: Schema): Boolean =
    restService.testCompatibility(schema.toString(), subject, "latest")

  override def register(subject: String, schema: Schema): Int = synchronized {
    val schemaIdMap: mutable.Map[Schema, Integer] =
      schemaCache.getOrElseUpdate(subject, mutable.Map())

    val id = schemaIdMap.getOrElse(
      schema, {
        if (schemaIdMap.size >= identityMapCapacity)
          throw new IllegalStateException(s"Too many schema objects created for $subject!")
        val id: Integer = new Integer(registerAndGetId(subject, schema))
        schemaIdMap.put(schema, id)
        idCache(null).put(id, schema)
        id
      }
    )
    id.intValue()
  }
}