Learning Kafka Streams with Scala
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The document discusses Kafka Streams and its implementation in Scala, outlining its advantages such as elasticity, scalability, and fault tolerance. It addresses the challenges faced when using Scala due to the lack of a Scala API for Kafka Streams and proposes solutions, including leveraging Scala 2.12 for better compatibility. Examples of Kafka Streams applications in Scala are provided, along with references for further information.
![Example
object WordCountApplication {
def main(args: Array[String]) {
val textLines: KStream[String, String] =
builder.stream("TextLinesTopic")
val wordCounts: KTable[String, Long] = textLines
.flatMapValues(textLine =>
textLine.toLowerCase.split("W+").toIterable.asJava)
.groupBy((_, word) => word)
.count("Counts")
wordCounts.to(Serdes.String(), Serdes.Long(),
"WordsWithCountsTopic")
val streams: KafkaStreams = new KafkaStreams(builder, config)
streams.start()
}
}](https://image.slidesharecdn.com/learning-kafka-streams-with-scala-171024070743/85/Learning-Kafka-Streams-with-Scala-6-320.jpg)
Learning Kafka Streams with Scala
- 1. Learning Kafka Streams with Scala Himanshu Gupta Lead Consultant Knoldus Software LLP Img src - http://danlebrero.com/2017/01/05/proof-of-concept-using-kafkastreams-and-ktables/
- 2. Agenda ● What is Kafka Streams? ● Why do we need to implement it in Scala? ● Challenge ● Solution ● Examples of Kafka Streams with Scala ● Demo
- 3. What is Kafka Streams? The easiest way to write mission-critical real- time applications and microservices with all the benefits of Kafka's server-side cluster technology
- 4. ● Write standard Java applications. ● No separate processing cluster required ● Elastic, highly scalable, fault-tolerant ● Equally viable for small, medium, & large use cases ● Exactly-once processing semantics ● Develop on Mac, Linux, Windows ● Deploy to containers, VM(s), bare metal, cloud ● Fully integrated with Kafka security Key Features
- 5. Where we can use it? Img src - https://kafka.apache.org/documentation/streams/
- 7. Why do we need to implement it in Scala? ● To provide a functional solution to a problem. ● To get better concurrency model. ● To write succinct and concise code. ● To have type safety or static typing.
- 9. Challenge No Scala API Is it really a challenge?
- 10. Challenge No Scala API Is it really a challenge? Yes
- 11. Challenge No Scala API Is it really a challenge? Yes Because Scala does not accept a function literal as a valid expression for any Single Abstract Method (SAM) type
- 12. Example Scala functions don’t implement the Runnable and Callable interfaces even though there’s a simply mapping. val r: Runnable = () => println("Run!") error: type mismatch; found : () => Unit required: Runnable val r: Runnable = () => println("Run!") Compile
- 13. Solution???
- 14. Solution val r: Runnable = new Runnable() { def run() = println("Run!") } Explicitly implement Runnable interface anonymously in Scala
- 15. Solution val r: Runnable = new Runnable() { def run() = println("Run!") } Explicitly implement Runnable interface anonymously in Scala What’s the problem with this approach?
- 16. Solution val r: Runnable = new Runnable() { def run() = println("Run!") } Explicitly implement Runnable interface anonymously in Scala Its too verbose!
- 17. What can be other solution?
- 18. Alternative Solution Use Scala 2.12
- 19. Alternative Solution Use Scala 2.12 But why?
- 20. Alternative Solution Use Scala 2.12 But why? Because Scala 2.12 accepts a function literal as a valid expression for any Single Abstract Method (SAM) type
- 21. Example It works! It doesn’t work!
- 22. Key Features of Scala 2.12 ● A trait compiles directly to an interface with default methods. This improves binary compatibility and Java interoperability. ● Scala and Java 8 interop is also improved for functional code, as methods that take functions can easily be called in both directions using lambda syntax. The FunctionN classes in Scala’s standard library are now Single Abstract Method (SAM) types, and all SAM types are treated uniformly – from type checking through code generation. No class file is generated for a lambda, invokedynamic is used instead.
- 23. Examples of Kafka Streams with Scala
- 24. Example #1 – Simple Pipeline
- 25. Example #2 – Mapped Pipeline (w/o SAM)
- 26. Example #2 – Mapped Pipeline (with SAM)
- 27. Example #2 – Aggregation Pipeline (w/o SAM)
- 28. Example #2 – Aggregation Pipeline (with SAM)
- 29. There are other Examples too - https://github.com/knoldus/kafka-streams-scala-examples
- 30. DEMO
- 32. Thank You