Create an Apache Kafka Client App for Clojure on Confluent Platform

In this tutorial, you will run a Clojure 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 8 or higher (Clojure 1.10 recommends using Java 8 or Java 11)
  • The Leiningen tool to compile and run the demos

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 Clojure.

    cd clients/cloud/clojure/
    
  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. Run the producer, passing in arguments for:

    • the local file with configuration parameters to connect to your Kafka cluster
    • the topic name
    lein producer $HOME/.confluent/java.config test1
    

    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}
    Produced record to topic test1 partition [0] @ offest 0
    Produced record to topic test1 partition [0] @ offest 1
    Produced record to topic test1 partition [0] @ offest 2
    Produced record to topic test1 partition [0] @ offest 3
    Produced record to topic test1 partition [0] @ offest 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] @ offest 5
    Produced record to topic test1 partition [0] @ offest 6
    Produced record to topic test1 partition [0] @ offest 7
    Produced record to topic test1 partition [0] @ offest 8
    Produced record to topic test1 partition [0] @ offest 9
    10 messages were produced to topic test1!
    
  2. 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 topic name you used earlier
    lein consumer $HOME/.confluent/java.config test1
    
  2. Verify the consumer received all the messages. You should see:

    …
    Waiting for message in KafkaConsumer.poll
    Consumed record with key alice and value {"count":0}, and updated total count to 0
    Consumed record with key alice and value {"count":1}, and updated total count to 1
    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 6
    Consumed record with key alice and value {"count":4}, and updated total count to 10
    Consumed record with key alice and value {"count":5}, and updated total count to 15
    Consumed record with key alice and value {"count":6}, and updated total count to 21
    Consumed record with key alice and value {"count":7}, and updated total count to 28
    Consumed record with key alice and value {"count":8}, and updated total count to 36
    Consumed record with key alice and value {"count":9}, and updated total count to 45
    Waiting for message in KafkaConsumer.poll
    …
    
  3. View the consumer code