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Spring Boot + Apache Kafka

This post will guide you to create a simple web application using Spring Boot and Apache Kafka. 

Apache Kafka is a distributed streaming platform which is well known for moving data between systems in a distributed way.

Spring boot provides out of the box integration with Apache Kafka so that you don’t have to write a lot of boiler plate code to integrate Kafka in your web application. 

Let’s get started!

Prerequisites

The only prerequisite is to have Kafka up and running in your environment. And to do that follow the links based on what operating system you’re using:

  1. Install Kafka on windows
  2. Install Kafka on macOS

I generally prefer running all my system dependencies using docker which is an awesome tool for developers. Docker enables developers to focus on writing code and not worry about the system it will run on. If you want to run Kafka using docker, you can use the docker-compose.yaml file that I have added in the github repo. So before running the application just copy the file and perform a docker-compose up -d which will spin up a single Kafka broker, Zookeeper and will also create the required topic. This means you don’t need to perform step 6.

Steps to create Spring Boot + Apache Kafka web application:

Follow the below steps to create a Spring Boot application with which you can produce and consume messages from Kafka using a Rest client.

1) Creating the Web Application Template:

We’ll be using Spring Initializr to create the web application project structure and the easiest way to use Spring Initializr is to use its web interface.

1.1) Go to https://start.spring.io/:

1.2) Enter Group and Artifact details:

1.3) Add Spring Web & Spring for Apache Kafka dependencies:

Then, click on Generate Project

This will generate and download the kafka-spring-app.zip file which is your maven project structure.

1.4) Unzip the file and then import it in your favourite IDE.

After importing the project in your IDE (Intellij in my case), you’ll see a project structure like this:

2) Configure Kafka Producer and Consumer:

We can configure the Kafka producer and consumer either by creating configuration classes (annotating classes with @Configuration annotation) for both producer and consumer or by using application.properties/application.yml file to configure them. In this tutorial, I’ll be demonstrating both for integrity. I personally prefer the latter approach (application.properties/application.yml) as it is quite handy and doesn’t require all the boilerplate code of the configuration class and that’s the beauty of spring boot one should leverage. 

2.1) Creating configuration classes for Kafka consumer and producer:

Creating the consumer config class:

Create a class ConsumerConfig.java in package com.technocratsid.kafkaspringapp.config with the following content:

package com.technocratsid.kafkaspringapp.config;

import java.util.HashMap;
import java.util.Map;

import org.apache.kafka.common.serialization.StringDeserializer;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.annotation.EnableKafka;
import org.springframework.kafka.config.ConcurrentKafkaListenerContainerFactory;
import org.springframework.kafka.core.ConsumerFactory;
import org.springframework.kafka.core.DefaultKafkaConsumerFactory;

@EnableKafka
@Configuration
public class ConsumerConfig {

    @Value("${spring.kafka.bootstrap-servers}")
    private String kafkaServers;

    @Value("${spring.kafka.groupId}")
    private String groupId;

    @Bean
    public ConsumerFactory<String, String> getConsumer() {
        Map<String, Object> configProp = new HashMap<>();
        configProp.put(org.apache.kafka.clients.consumer.ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, kafkaServers);
        configProp.put(org.apache.kafka.clients.consumer.ConsumerConfig.GROUP_ID_CONFIG, groupId);
        configProp.put(org.apache.kafka.clients.consumer.ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        configProp.put(org.apache.kafka.clients.consumer.ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        return new DefaultKafkaConsumerFactory<>(configProp);
    }

    @Bean
    public ConcurrentKafkaListenerContainerFactory<String, String> kafkaListenerContainerFactory() {
        ConcurrentKafkaListenerContainerFactory<String, String> factory = new ConcurrentKafkaListenerContainerFactory<>();
        factory.setConsumerFactory(getConsumer());
        return factory;
    }

}

Note: Here we are declaring ConsumerFactory and ConcurrentKafkaListenerContainerFactory as beans (using @Bean annotation). This tells the spring container to manage them for us. ConsumerFactory is used to specify the strategy to create a Consumer instance(s) and ConcurrentKafkaListenerContainerFactory is used to create and configure containers for @KafkaListener annotated methods.

@Configuration is used to tell Spring that this is a Java-based configuration file and contains the bean definitions.

@EnableKafka annotation tells Spring that we want to talk to Kafka and allows Spring to detect the methods that are annotated with @KafkaListener.

@Value annotation is used to inject value from a properties file based on the property name.

The application.properties file for properties spring.kafka.bootstrap-servers and spring.kafka.groupId is inside src/main/resources and contains the following key value pairs:

spring.kafka.bootstrap-servers=localhost:9092
spring.kafka.groupId=kafka-spring-app

If you wish to run the application with a remote Kafka cluster then edit spring.kafka.bootstrap-servers pointing to your remote brokers.

Creating the producer config class:

Create another class ProducerConfig.java in the same package com.technocratsid.kafkaspringapp.config with the following content:

package com.technocratsid.kafkaspringapp.config;

import java.util.HashMap;
import java.util.Map;

import org.apache.kafka.common.serialization.StringSerializer;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.core.DefaultKafkaProducerFactory;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.core.ProducerFactory;

@Configuration
public class ProducerConfig {

    @Value("${spring.kafka.bootstrap-servers}")
    private String kafkaServers;

    @Bean
    public ProducerFactory<String, String> getProducer() {
        Map<String, Object> configProp = new HashMap<>();
        configProp.put(org.apache.kafka.clients.producer.ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, kafkaServers);
        configProp.put(org.apache.kafka.clients.producer.ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        configProp.put(org.apache.kafka.clients.producer.ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        return new DefaultKafkaProducerFactory<>(configProp);
    }

    @Bean
    public KafkaTemplate<String, String> kafkaTemplate() {
        return new KafkaTemplate<>(getProducer());
    }

}

Note: Here we are declaring ProducerFactory and KafkaTemplate as beans where ProducerFactory is used to specify the strategy to create a Producer instance(s) and KafkaTemplate is a template for executing high-level operations like sending messages to a Kafka topic etc.

The value of kafkaServers is injected from the property spring.kafka.bootstrap-servers of the application.properties file same as ConsumerConfig class.

2.2) Configuring the Kafka consumer and producer using application.properties:

Open the application.properties file inside src/main/resources and add the following key value pairs:

spring.kafka.consumer.bootstrap-servers=localhost:9092
spring.kafka.consumer.group-id=kafka-spring-app
spring.kafka.consumer.auto-offset-reset=earliest
spring.kafka.consumer.key-deserializer=org.apache.kafka.common.serialization.StringDeserializer
spring.kafka.consumer.value-deserializer=org.apache.kafka.common.serialization.StringDeserializer

spring.kafka.producer.bootstrap-servers=localhost:9092
spring.kafka.producer.value-serializer=org.apache.kafka.common.serialization.StringSerializer
spring.kafka.producer.key-serializer=org.apache.kafka.common.serialization.StringSerializer

That’s it!

The above properties will configure the Kafka consumer and producer without having to write a single line of code and that’s the beauty of spring boot.

The key value pair in application.properties (allows to specify configuration) allows spring to do different things. With this file you can tell spring to configure things without writing any code.

3) Creating a consumer service:

Create a class KafkaConsumer.java in package com.technocratsid.kafkaspringapp.service with the following content:

package com.technocratsid.kafkaspringapp.service;

import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Service;

import java.util.ArrayList;
import java.util.List;

@Service
public class KafkaConsumer {

    public static List<String> messages = new ArrayList<>();
    private final static String topic = "technocratsid-kafka-spring";
    private final static String groupId = "kafka-spring-app";

    @KafkaListener(topics = topic, groupId = groupId)
    public void listen(String message) {
        messages.add(message);
    }
}

@KafkaListener allows a method to listen/subscribe to specified topics.

In our case whenever a message is produced on the topic “technocratsid-kafka-spring“, we are adding that message to a List of String (which is adding stuff to memory and it is not a good practice, in real world you might consider writing the messages to some datastore) so that we can display the messages later.

@Service tells Spring that this file performs a business service.

4) Creating a producer service:

Create a class KafkaProducer.java in package com.technocratsid.kafkaspringapp.service with the following content:

package com.technocratsid.kafkaspringapp.service;

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.stereotype.Service;

@Service
public class KafkaProducer {

    @Autowired
    private KafkaTemplate<String, String> kafkaTemplate;

    @Value("${app.topic}")
    private String topic;

    public void produce(String message) {
        kafkaTemplate.send(topic, message);
    }

}

Here we are using the KafkaTemplate send method to send messages to a particular topic.

@Autowired tells Spring to automatically wire or inject the value of variable from the beans which are managed by the the spring container. So in our case the value of kafkaTemplate is injected from the bean kafkaTemplate() defined in ProducerConfig class.

@Service tells Spring that this file performs a business service.

5) Creating a rest controller:

Create a class KafkaController.java in package com.technocratsid.kafkaspringapp.controller with the following content:

package com.technocratsid.kafkaspringapp.controller;

import com.technocratsid.kafkaspringapp.service.KafkaConsumer;
import com.technocratsid.kafkaspringapp.service.KafkaProducer;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.RequestBody;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestMethod;
import org.springframework.web.bind.annotation.RestController;

import java.util.List;

@RestController
public class KafkaController {

    @Autowired
    private KafkaConsumer consumer;

    @Autowired
    private KafkaProducer producer;

    @RequestMapping(value="/send", method= RequestMethod.POST)
    public void send(@RequestBody String data) {
        producer.produce(data);
    }

    @RequestMapping(value="/receive", method=RequestMethod.GET)
    public List<String> receive() {
        return consumer.messages;
    }
}

This class registers two endpoints /send and /receive which sends and receive messages to and from Kafka respectively, where /send is a POST request with String body and /receive returns the sent messages.

6) Create the required Kafka topic:

Before running the application create the following topic:

kafka-topics --bootstrap-server localhost:9092 --topic technocratsid-kafka-spring --create --partitions 1 --replication-factor 1

7) Running the web application:

Either run the KafkaSpringAppApplication class as a Java Application from your IDE or use the following command:

mvn spring-boot:run

8) Testing the web app with a REST client:

To test the Spring Boot + Apache Kafka web application I am using Insomnia REST Client which is my favourite Rest client because of its simple interface. You can use any REST client.

Once your application is up and running, perform a POST request to the URL http://localhost:8080/send with the body {“key1”: “value1”}:

Then, perform a GET request to the URL http://localhost:8080/receive and this is the response you’ll get:

Congratulations on building a Spring Boot + Apache Kafka web application.

Hack into the github repo to see the complete code.

Install Kafka on Windows

This post is a step-by-step guide to install and run Apache Kafka on Windows.

Prerequisite

The only prerequisite for this setup is JRE.

Install Java (Skip if you already have it)

  1. Download Java 8 from here. (Java 8 is recommended by Apache Kafka)
  2. Run the installer and follow the instructions on Installation wizard.
  3. Please note/copy the Destination Folder location.
  4. Go to Control Panel -> System -> Advanced system settings -> Environment Variables.
  5. Create a new user variable named JAVA_HOME and paste the path copied from step 3 to the variable value and click OK.
  6. Now edit PATH variable in User variables and add “%JAVA_HOME%\bin” at the end of the variable value. If it’s an older windows version, then add “;%JAVA_HOME%\bin;” at the end of the text. If PATH variable doesn’t exist create it with the value “%JAVA_HOME%\bin”.
  7. Open command prompt and type “java -version” to validate the installation.
  8. If you get the following output in your command prompt you’re good to go:
java version "1.8.0_231"
Java(TM) SE Runtime Environment (build 1.8.0_231-b11)
Java HotSpot(TM) 64-Bit Server VM (build 25.231-b11, mixed mode)

Steps to install Kafka on windows:

1) Download and extract Apache Kafka from here.

Note: At the time of writing this post the current stable version is 2.4.0. If you’re using Scala for development then make sure to select the Kafka version corresponding to your Scala version.

2) Go to the folder where you’ve extracted Kafka, open the file server.properties in the config folder and then edit the line log.dirs=/tmp/kafka-logs to log.dirs=C:\path_where_kafka_is_extracted\kafka-logs.

Note: If you won’t change log.dirs value, you’ll keep getting the following error:

java.util.NoSuchElementException: key not found: /tmp/kafka-logs

3) Start Zookeeper

Kafka uses ZooKeeper so before starting Kafka you have to make sure that ZooKeeper is up and running. We’ll be running the single node ZooKeeper instance packaged with Kafka. 

Go to your Kafka installation directory and open command prompt and start Zookeeper using the following command:

> bin\windows\zookeeper-server-start.bat config\zookeeper.properties

Once zookeeper is started you should see this in the command prompt:

INFO binding to port 0.0.0.0/0.0.0.0:2181 (org.apache.zookeeper.server.NIOServerCnxnFactory)

4) Start Kafka Server

You need to open another command prompt in the Kafka installation directory and run the following command:

> bin\windows\kafka-server-start.bat \config\server.properties

Once the Kafka server is started you should see something like this in the command prompt:

INFO [KafkaServer id=0] started (kafka.server.KafkaServer)

5) Validate the Kafka setup

Create a Kafka topic:

Open a command prompt in the Kafka installation directory and run the following command:

> bin\windows\kafka-topics.bat --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic testTopic

The above command will create a topic “testTopic” with 1 partition and 1 replication factor.

Produce messages to the created topic:

In the same command prompt start a kafka-console-producer and produce some messages:

> bin\windows\kafka-console-producer.bat --broker-list localhost:9092 --topic testTopic
>Hello
>How are you?

Consume the messages produced by the kafka-console-producer:

Open another command prompt in the Kafka installation directory and start a kafka-console-consumer which subscribes to testTopic:

> bin\windows\kafka-console-consumer.bat --bootstrap-server localhost:9092 --topic testTopic --from-beginning
Hello
How are you?

The messages which are produced by the kafka-console-producer will be visible on the kafka-console-consumer console.

Congratulations on completing a single broker Kafka setup on windows!

Install Kafka on macOS

I really like Homebrew to install stuff on macOS. So in this tutorial I’ll be using Hombrew to install Apache Kafka on macOS.

Install Homebrew:

Open Terminal, paste the following command and then press Return key:

$ /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"

The above command will install Homebrew. Once it is installed, follow the next steps:

1)  Install Java8:

After Homebrew is installed, you can just paste the following commands in Terminal and press Return to install java on macOS:

$ brew tap adoptopenjdk/openjdk
$ brew cask install adoptopenjdk8

The above commands will install openjdk 8. In order to validate the java installation, execute the following command in Terminal:

$ java -version

If you get the following output, it means that java is installed correctly:

openjdk version "1.8.0_212"
OpenJDK Runtime Environment (AdoptOpenJDK)(build 1.8.0_212-b04)
OpenJDK 64-Bit Server VM (AdoptOpenJDK)(build 25.212-b04, mixed mode)

2) Install Kafka:

To install Kafka on macOS: open Terminal, paste the following command and then press Return:

$ brew install kafka

The above command will install Kafka along with Zookeeper.

Start Zookeeper:

To start ZooKeeper, paste the following command in the Terminal and press Return:

$ zookeeper-server-start /usr/local/etc/kafka/zookeeper.properties

Once ZooKeeper is started you’ll see something like this in the console:

INFO binding to port 0.0.0.0/0.0.0.0:2181 (org.apache.zookeeper.server.NIOServerCnxnFactory)

Start Kafka:

To start Kafka, paste the following command in another Terminal and press Return:

$ kafka-server-start /usr/local/etc/kafka/server.properties

Once Kafka is started you’ll see something like this in the console:

INFO [KafkaServer id=0] started (kafka.server.KafkaServer)

Create a Kafka topic:

Open another Terminal and execute the following command to create a topic testTopic with 1 partition and 1 replication factor:

kafka-topics --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic testTopic

Produce messages to the created topic:

In the same Terminal prompt, start a kafka-console-producer and produce some messages:

$ kafka-console-producer --broker-list localhost:9092 --topic testTopic
>Hello
>How are you?

Consume the messages produced by the producer:

Open another Terminal and start a kafka-console-consumer which subscribes to testTopic:

$ kafka-console-consumer --bootstrap-server localhost:9092 --topic testTopic --from-beginning
Hello
How are you?

The messages which are produced by the kafka-console-producer will be visible on the kafka-console-consumer console.

Congratulations on setting up a single broker Kafka setup on macOS!