README.md

Module kotlin-kafka

• Rationale
• Goals
• Adding Dependency
• Example

Rationale

At the time of starting this repository I didn't find any bindings between Kafka SDK and Kotlin suspension, or KotlinX Coroutines Flow. These operators should be implemented low-level, so they can guarantee correct cancellation support, and high optimised runtimes.

Some important aspects of Kafka are tricky to implement with the "low-level" Kafka API, especially properly streaming records from Kafka and correctly committing them. Additional complexity is involved in this process, more details here.

To solve these problems a couple of projects in the JVM already exist:

• Alpakka Kafka
• reactor-kafka

There was no implementation for KotlinX Coroutines Flow, you can however quite easily use reactor-kafka with KotlinX Coroutines Reactor bindings.

This project implements the same strategies as [reactor-kafka] directly on top of KotlinX Coroutines to benefit from all their benefits, and to open the door to potentially becoming a Kotlin MPP library in the future.

Goals

• Lean Core library built on top of Kotlin Std & KotlinX Coroutines
• Extensions to easily operate over the Kafka SDK with KotlinX Coroutines and suspend.
• Flow based operators, so you can easily compose KotlinX Flow based Kafka programs
• Strong guarantees about committing record offsets, and performance optimisations in regard to re-balancing/partitioning.
• example for testing Kafka with Test Containers in Kotlin.

Adding Dependency

Simply add the following dependency as implementation in the build.gradle dependencies` block.

dependencies {
  implementation("io.github.nomisrev:kotlin-kafka:0.3.0")
}

Example

@JvmInline
value class Key(val index: Int)

@JvmInline
value class Message(val content: String)

fun main(): Unit = SuspendApp {
  val topicName = "test-topic"
  val msgCount = 10
  val kafka = Kafka.container

  Admin(AdminSettings(kafka.bootstrapServers)).use { client ->
    client.createTopic(NewTopic(topicName, 1, 1))
  }

  launch(Dispatchers.IO) { // Send 20 messages, and then close the producer
    val settings: PublisherSettings<Key, Message> = PublisherSettings(
      kafka.bootstrapServers,
      IntegerSerializer().imap { key: Key -> key.index },
      StringSerializer().imap { msg: Message -> msg.content },
      Acks.All
    )
    KafkaPublisher(settings).use { publisher ->
      publisher.publishScope {
        (1..msgCount).forEach { index ->
          offer(ProducerRecord(topicName, Key(index), Message("msg: $index")))
        }
      }
    }
  }

  launch(Dispatchers.IO) { // Consume 20 messages as a stream, and then close the consumer
    val settings: ReceiverSettings<Key, Message> = ReceiverSettings(
      kafka.bootstrapServers,
      IntegerDeserializer().map(::Key),
      StringDeserializer().map(::Message),
      groupId = UUID.randomUUID().toString(),
      autoOffsetReset = AutoOffsetReset.Earliest
    )
    KafkaReceiver(settings)
      .receive(topicName)
      .take(msgCount)
      .map { "${it.key()} -> ${it.value()}" }
      .collect(::println)
  }
}

You can get the full code here.

Key(index=1) -> Message(content=msg: 1)
Key(index=2) -> Message(content=msg: 2)
Key(index=3) -> Message(content=msg: 3)
Key(index=4) -> Message(content=msg: 4)
Key(index=5) -> Message(content=msg: 5)
Key(index=6) -> Message(content=msg: 6)
Key(index=7) -> Message(content=msg: 7)
Key(index=8) -> Message(content=msg: 8)
Key(index=9) -> Message(content=msg: 9)
Key(index=10) -> Message(content=msg: 10)