Create a Kafka Client App for Kotlin for Use With Confluent Platform

In this tutorial, you will run a Kotlin client application that produces messages to and consumes messages from an Apache Kafka® cluster.

After you run the tutorial, use the provided source code as a reference to develop your own Kafka client application.

Prerequisites

Client

  • Java 1.8 or higher to run the demo application.

Kafka Cluster

The easiest way to follow this tutorial is with Confluent Cloud because you don’t have to run a local Kafka cluster. From the Console, click on LEARN to provision a cluster and click on Clients to get the cluster-specific configurations and credentials to set for your client application.

You can alternatively use the supported CLI or REST API, or the community-supported ccloud-stack utility for Confluent Cloud.

If you don’t want to use Confluent Cloud, you can also use this tutorial with a Kafka cluster running on your local host or any other remote server.

Setup

  1. Clone the confluentinc/examples GitHub repository and check out the latest branch.

    git clone https://github.com/confluentinc/examples
cd examples
git checkout latest

  2. Change directory to the example for Kotlin.

    cd clients/cloud/kotlin/

  3. Create a local file (for example, at $HOME/.confluent/java.config) with configuration parameters to connect to your Kafka cluster. Starting with one of the templates below, customize the file with connection information to your cluster. Substitute your values for {{ BROKER_ENDPOINT }}, {{CLUSTER_API_KEY }}, and {{ CLUSTER_API_SECRET }} (see Configure Confluent Cloud Clients for instructions on how to manually find these values, or use the ccloud-stack utility for Confluent Cloud to automatically create them).

    • Template configuration file for Confluent Cloud

      # Required connection configs for Kafka producer, consumer, and admin
bootstrap.servers={{ BROKER_ENDPOINT }}
security.protocol=SASL_SSL
sasl.jaas.config=org.apache.kafka.common.security.plain.PlainLoginModule required username='{{ CLUSTER_API_KEY }}' password='{{ CLUSTER_API_SECRET }}';
sasl.mechanism=PLAIN
# Required for correctness in Apache Kafka clients prior to 2.6
client.dns.lookup=use_all_dns_ips

# Best practice for higher availability in Apache Kafka clients prior to 3.0
session.timeout.ms=45000

# Best practice for Kafka producer to prevent data loss 
acks=all

    • Template configuration file for local host

      # Kafka
bootstrap.servers=localhost:9092

Basic Producer and Consumer

In this example, the producer application writes Kafka data to a topic in your Kafka cluster. If the topic does not already exist in your Kafka cluster, the producer application will use the Kafka Admin Client API to create the topic. Each record written to Kafka has a key representing a username (for example, alice) and a value of a count, formatted as json (for example, {"count": 0}). The consumer application reads the same Kafka topic and keeps a rolling sum of the count as it processes each record.

Produce Records

  1. Build the client examples:

    ./gradlew clean build

  2. Run the producer, passing in arguments for:

    • the local file with configuration parameters to connect to your Kafka Cluster
    • the topic name
    ./gradlew runApp -PmainClass="io.confluent.examples.clients.cloud.ProducerExample" \
     -PconfigPath="$HOME/.confluent/java.config" \
     -Ptopic="test1"

  3. Verify the producer sent all the messages. You should see:

    ...
Producing record: alice        {"count":0}
Producing record: alice        {"count":1}
Producing record: alice        {"count":2}
Producing record: alice        {"count":3}
Producing record: alice        {"count":4}
Producing record: alice        {"count":5}
Producing record: alice        {"count":6}
Producing record: alice        {"count":7}
Producing record: alice        {"count":8}
Producing record: alice        {"count":9}
Produced record to topic test1 partition [0] @ offset 0
Produced record to topic test1 partition [0] @ offset 1
Produced record to topic test1 partition [0] @ offset 2
Produced record to topic test1 partition [0] @ offset 3
Produced record to topic test1 partition [0] @ offset 4
Produced record to topic test1 partition [0] @ offset 5
Produced record to topic test1 partition [0] @ offset 6
Produced record to topic test1 partition [0] @ offset 7
Produced record to topic test1 partition [0] @ offset 8
Produced record to topic test1 partition [0] @ offset 9
10 messages were produced to topic test1
...

  4. View the producer code.

Consume Records

  1. Run the consumer, passing in arguments for:

    • the local file with configuration parameters to connect to your Kafka cluster
    • the same topic name you used earlier.
    ./gradlew runApp -PmainClass="io.confluent.examples.clients.cloud.ConsumerExample"\
     -PconfigPath="$HOME/.confluent/java.config"\
     -Ptopic="test1"

  2. Verify that the consumer received all the messages. You should see:

    ...
Consumed record with key alice and value {"count":0}, and updated total count to 1
Consumed record with key alice and value {"count":1}, and updated total count to 2
Consumed record with key alice and value {"count":2}, and updated total count to 3
Consumed record with key alice and value {"count":3}, and updated total count to 4
Consumed record with key alice and value {"count":4}, and updated total count to 5
Consumed record with key alice and value {"count":5}, and updated total count to 6
Consumed record with key alice and value {"count":6}, and updated total count to 7
Consumed record with key alice and value {"count":7}, and updated total count to 8
Consumed record with key alice and value {"count":8}, and updated total count to 9
Consumed record with key alice and value {"count":9}, and updated total count to 10

  3. When you are done, press CTRL-C.

  4. View the consumer code.

Kafka Streams

  1. Run the Kafka Streams application, passing in arguments for:

    • the local file with configuration parameters to connect to your Kafka cluster
    • the same topic name you used earlier
    ./gradlew runApp -PmainClass="io.confluent.examples.clients.cloud.StreamsExample" \
     -PconfigPath="$HOME/.confluent/java.config" \
     -Ptopic="test1"

  2. Verify the consumer received all the messages. You should see:

    ...
[Consumed record]: alice, 0
[Consumed record]: alice, 1
[Consumed record]: alice, 2
[Consumed record]: alice, 3
[Consumed record]: alice, 4
[Consumed record]: alice, 5
[Consumed record]: alice, 6
[Consumed record]: alice, 7
[Consumed record]: alice, 8
[Consumed record]: alice, 9
...
[Running count]: alice, 0
[Running count]: alice, 1
[Running count]: alice, 3
[Running count]: alice, 6
[Running count]: alice, 10
[Running count]: alice, 15
[Running count]: alice, 21
[Running count]: alice, 28
[Running count]: alice, 36
[Running count]: alice, 45
...

  3. When you are done, press CTRL-C.

  4. View the Kafka Streams code.