Kafka Streams: Unit Testing

Kafka Streams is a powerful API. In Kafka, we can only store our data for consumers to consume. But we always needed a processor with which we can process the data without going to an external tool like Spark, Storm etc. To know more about this and for a quick start you can check out the first blog of this series.

The Need

Now here we are using the Kafka streams in our applications. We are done with the implementation but again the most important thing is left, Testing. So this blog is about how to test the application we have created. For this I’ll be taking the sample app I have created in my previous blog for both High-Level DSL and low-level Processor API.

Traditionally, we test our Kafka application by using an Integration test for which we need to create a zookeeper and a real Kafka Broker. After that, we then need to mock producer and mock consumer for our app to produce the inputs and receive the outputs. That is such a big hassle just to test our app. Testing it for real scenarios and for the actual integration test this is needed without a doubt.

Other than this we got Embedded Kafka. Embedded Kafka provides us with a virtual environment of Kafka broker and it provides us the built-in methods to publish and receive data from topics for testing purposes.

Both the approaches are good for integration test cases for testing Kafka. But we needed something that can provide us with unit tests. So for the unit testing of Kafka Streams there comes something called Mocked Streams.

Mocked Streams

Mocked Stream is a library for Scala for unit testing Kafka Streams. It is available for Scala 2.11.8 onward. It saves us from writing all the code that we used to do for our unit tests and creating a separate Kafka broker just for testing. And we can use any testing tool like FunSuite or FlatSpec with it. Following is one test case code.

it should "change characters to upper case" in {
  val res = MockedStreams().topology{builder =>
    streamOperations.toUpperCase(builder, inTopic).to(outTopic)
    .input[String, String](inTopic, stringSerde, stringSerde, keyValueSeq)
    .output[String, String](outTopic, stringSerde, stringSerde, keyValueSeq.size)

  assert(res.toList == updateKeyValueSeq)

In this test case, we don’t need to do anything except just importing our MockedStream library. So no need for producer-consumer, Kafka broker etc.


To start writing test cases for our Kafka Stream App we first need to add the dependency of MockedStreams

"com.madewithtea" %% "mockedstreams" % "1.3.0" % "test"

Now, all we need to do is just to import the library in our test class and we are good to write our test cases.

It provides us with topology() method which provides us with a KStreamBuilder instance on which we can apply our method to test it.

MockedStreams().topology{builder =>

This method returns an instance of Builder class provided in MockedStream library. we can provide inputs using the input() method and then we can apply the output() method to receive the output of our method. We can apply our streaming config on this Builder instance to provide it with our serdes and time stamp extractor class etc. This config is used to create the builder inside the topology method

val result = MockedStreams().topology{builder =>
  .input(firstInTopic, stringSerde, stringSerde, keyValueSeq)
  .output(firstOutTopic, stringSerde, stringSerde, keyValueSeq.size)

we can use multiple inputs on this Builder instance

val result = MockedStreams().topology{builder =>
 .input(firstInTopic, stringSerde, stringSerde, keyValueSeq)
 .input(secondInTopic, stringSerde, stringSerde, keyValueSeq)
 .output(firstOutTopic, stringSerde, stringSerde, keyValueSeq.size)

Similarly multiple output methods

val resultBuilder = MockedStreams().topology{builder =>
 .input(firstInTopic, stringSerde, stringSerde, keyValueSeq)
 .input(secondInTopic, stringSerde, stringSerde, keyValueSeq)

val firstOutput = resultBuilder.output(firstOutTopic, stringSerde, stringSerde, keyValueSeq.size)
val secondOutput = resultBuilder.output(secondOutTopic, stringSerde, stringSerde, keyValueSeq.size)

For more details, you can visit its official GitHub documentation.

I have continued with the code on my previous repo. Here is the link to the sample application for which test cases are now added.


  1. https://github.com/jpzk/mockedstreams
  2. http://docs.confluent.io/current/streams/index.html


This entry was posted in Apache Kafka, Scala and tagged , , . Bookmark the permalink.

One Response to Kafka Streams: Unit Testing

  1. Pingback: Last Week in Stream Processing & Analytics – 7.8.2017 | Enjoy IT - SOA, Java, Event-Driven Computing and Integration

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