A Scala library to create RxScala observables and observers from Kafka consumers and producers
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rx-kafka-json4s/src Release version 0.2.0 Dec 26, 2017



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This library provides a simple way to create Kafka consumers and producers, it uses RxScala under the hood, and provides the ability to turn consumers and producers into RxScala's observables and observers.

Setting up the dependencies

RxKafka is available on Maven Central (since version 0.2.0), and it is cross compiled and published for Scala 2.12 and 2.11.

Older artifacts versions are not available anymore due to the shutdown of my self-hosted Nexus Repository in favour of Bintray

Using SBT, add the following dependency to your build file:

libraryDependencies ++= Seq(
  "io.bfil" %% "rx-kafka-core" % "0.2.0"

Include the following module if you need JSON serialization (it uses Json4s)

libraryDependencies ++= Seq(
  "io.bfil" %% "rx-kafka-json4s" % "0.2.0"

If you have issues resolving the dependency, you can add the following resolver:

resolvers += Resolver.bintrayRepo("bfil", "maven")



The topics in RxKafka are typed, the following is the Topic trait:

trait Topic[T] {
  val name: String
  type Message = T
  val serializer: Serializer[T]
  val deserializer: Deserializer[T]

Topics can be defined by extending the trait, each topic has its own name (used by Kafka), and the type of the message it contains (often needed by the serialization process).

The core module supports basic Java serialization, and exposes an abstract SerializableTopic class that can be easily extended to define new topics that will be serialized using Java serialization, as follows:

case object TestTopic extends SerializableTopic[Test]("test")
case object AnotherTestTopic extends SerializableTopic[AnotherTest]("another-test")

Test and AnotherTest are simple case classes representing the message.

The json4s module provides a similar class, called JsonTopic, that can be used as follows:

case object JsonTestTopic extends JsonTopic[Test]("test")
case object AnotherJsonTestTopic extends JsonTopic[AnotherTest]("another-test")

This topics can then be used to create consumers and producers, and the self contained serialization simplifies the rest of the APIs.


Two types of consumers can be created, consumers consuming a single topic, or multiple topics.

Single-Topic Consumer

To create and use an RxKafka consumer tied to a single topic:

val consumer = KafkaConsumer(TestTopic)

// an iterator can be accessed on the consumer
val iterator = consumer.iterator

// or the consumer can be turned into an Observable[T] where T is the type of the message (in this case it will be Test)
val observable = consumer.toObservable

// you can also call subscribe directly on the Consumer (it's just a proxy to the Observable's subscribe method)
consumer.subscribe { message =>
	// ...

// to close the Kafka connector

Multiple-Topics Consumer

To create and use an RxKafka consumer tied to multiple topics:

val consumer = KafkaConsumer(List(TestTopic, AnotherTestTopic))

// a map of iterators can be accessed on the consumer as a Map[String, Iterator[Any]]
val iterators = consumer.iterators

// or the consumer can be turned into an Observable[Any] which will merge all topics together:
val observable = consumer.toObservable

// you can also call subscribe directly on the `Consumer`
consumer.subscribe { 
  case test: Test => // ...
  case anotherTest: AnotherTest => // ...

// to close the Kafka connector


Two types of producers can be created, producers producing a single topic, or multiple topics.

Single-Topic Producer

To create and use an RxKafka producer for a single topic:

val producer = KafkaProducer(TestTopic)

// plublish a message

// or the producer can be turned into an Observer[T] where T is the type of the message (in this case it will be Test)
val observer = producer.toObserver

// then you can use the Observer API

// stop the Kafka producer

Multiple-Topics Producer

val producer = KafkaProducer()

// plublish a message to a particular topic
producer.publish(TestTopic, Test("test"))
producer.publish(AnotherTestTopic, AnotherTest("test"))

// or the producer can be turned into an Observer[(Topic[T], T)]
val observer = producer.toObserver

// then you can use the Observer API
observer.onNext(TestTopic, Test("test"))
observer.onNext(AnotherTestTopic, AnotherTest("test"))

// stop the Kafka producer


Configuration is supported using Typesafe Config.

To customize default consumers and producers configuration create an application.conf file under your src/main/resources folder.

The following is an example configuration file:

kafka {
	consumer {
		group.id = "default"
		zookeeper.connect = "localhost:2181"
	producer {
		bootstrap.servers = "localhost:9092"

Please Note: the configuration values support different types depending on the configuration, for durations or buffer sizes for example the .ms and .bytes suffixes are not necessary and the configuration allows to specify the actual unit.

For example, in a consumer you should specify configuration values like so:

group.id = "default"
zookeeper.connect = "localhost:2181"
socket.timeout = 30 seconds
socket.receive.buffer = 64B
fetch.message.max = 1M
num.consumer.fetchers = 1
auto.commit.enable = true

For the full list of configurations refer to the Kafka documentation for the Old Consumer and the Producer

Custom Consumers / Producers Configuration

A Typesafe Config object can be passed into the KafkaConsumer and KafkaProducer constructors:

You can define separate blocks into your application.conf:

my-consumer-1 {
  group.id = "group-1"
my-consumer-2 {
  group.id = "group-2"

async-producer {
  producer.type = "async"

Then these configurations can be loaded like this:

import com.typesafe.config.ConfigFactory
val config = ConfigFactory.load

val consumerConfig1 = config.getConfig("my-consumer-1")
val consumerConfig2 = config.getConfig("my-consumer-2")

val asyncProducerConfig = config.getConfig("async-producer")

And they can be specified in the constructor:

val consumer1 = KafkaConsumer(TestTopic, consumerConfig1)
val consumer2 = KafkaConsumer(List(TestTopic, AnotherTestTopic), consumerConfig2)

val asyncProducer = KafkaProducer(asyncProducerConfig)
val asyncTestProducer = KafkaProducer(TestTopic, asyncProducerConfig)

Custom Serialization

Custom serializers are supported and it's really easy to create one, the following are the serialization interfaces:

trait Serializer[-T] {
  def toBytes(obj: T): Array[Byte]

trait Deserializer[+T] {
  def fromBytes(bytes: Array[Byte]): T

As an example, take a look at the implementation of the Json4s serialization in rx-kafka-json4s:

import org.json4s.native.Serialization

class Json4sSerializer[T <: AnyRef](implicit formats: Formats) extends Serializer[T] {
  def toBytes(obj: T): Array[Byte] = Serialization.write(obj).getBytes

class Json4sDeserializer[T: Manifest](implicit formats: Formats) extends Deserializer[T] {
  def fromBytes(bytes: Array[Byte]): T = Serialization.read[T](new String(bytes)) 


This software is licensed under the Apache 2 license, quoted below.

Copyright © 2015-2017 Bruno Filippone http://bfil.io

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at


Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.