Kafka Streams with Spring Boot

Question

I want to work with Kafka Streams real time processing in my spring boot project. So I need Kafka Streams configuration or I want to use KStreams or KTable, but I could not find example on the internet.

I did producer and consumer now I want to stream real time.

Answer 1

Let me start by saying that if you are new to Kafka streams, adding spring-boot on top of it is adding another level of complexity, and Kafka streams has a big learning curve as is. Here are the basics to get you going: pom:

<!-- https://mvnrepository.com/artifact/org.springframework.kafka/spring-kafka -->
<dependency>
  <groupId>org.springframework.kafka</groupId>
  <artifactId>spring-kafka</artifactId>
  <version>${spring.version}</version>
</dependency>

<!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka-clients -->
<dependency>
  <groupId>org.apache.kafka</groupId>
  <artifactId>kafka-clients</artifactId>
  <version>${kafka.version}</version>
</dependency>

<!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka-streams -->
<dependency>
  <groupId>org.apache.kafka</groupId>
  <artifactId>kafka-streams</artifactId>
  <version>${kafka.version}</version>
</dependency>

Now the configuration object. The code below assumes you are creating two stream apps, and keep in mind that each app represents its own processing topology:

import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.common.serialization.Serdes;
import org.apache.kafka.streams.StreamsConfig;
import org.apache.kafka.streams.processor.FailOnInvalidTimestamp;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.annotation.KafkaStreamsDefaultConfiguration;
import org.springframework.kafka.core.StreamsBuilderFactoryBean;

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

@Configuration
public class KafkaStreamConfig {

  @Value("${delivery-stats.stream.threads:1}")
  private int threads;

  @Value("${delivery-stats.kafka.replication-factor:1}")
  private int replicationFactor;

  @Value("${messaging.kafka-dp.brokers.url:localhost:9092}")
  private String brokersUrl;


  @Bean(name = KafkaStreamsDefaultConfiguration.DEFAULT_STREAMS_CONFIG_BEAN_NAME)
  public StreamsConfig kStreamsConfigs() {
    Map<String, Object> config = new HashMap<>();
    config.put(StreamsConfig.APPLICATION_ID_CONFIG, "default");
    setDefaults(config);
    return new StreamsConfig(config);
  }


  public void setDefaults(Map<String, Object> config) {
    config.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, brokersUrl);
    config.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass());
    config.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.String().getClass());
    config.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
    config.put(StreamsConfig.DEFAULT_TIMESTAMP_EXTRACTOR_CLASS_CONFIG, FailOnInvalidTimestamp.class);
  }

  @Bean("app1StreamBuilder")
  public StreamsBuilderFactoryBean app1StreamBuilderFactoryBean() {
    Map<String, Object> config = new HashMap<>();
    setDefaults(config);
    config.put(StreamsConfig.PROCESSING_GUARANTEE_CONFIG, StreamsConfig.EXACTLY_ONCE);
    config.put(StreamsConfig.APPLICATION_ID_CONFIG, "app1");
    config.put(StreamsConfig.COMMIT_INTERVAL_MS_CONFIG, 30000);
    config.put(StreamsConfig.NUM_STREAM_THREADS_CONFIG, threads);
    config.put(StreamsConfig.REPLICATION_FACTOR_CONFIG, replicationFactor);
    return new StreamsBuilderFactoryBean(config);
  }

  @Bean("app2StreamBuilder")
  public StreamsBuilderFactoryBean app2StreamBuilderFactoryBean() {
    Map<String, Object> config = new HashMap<>();
    setDefaults(config);
    config.put(StreamsConfig.PROCESSING_GUARANTEE_CONFIG, StreamsConfig.EXACTLY_ONCE);
    config.put(StreamsConfig.APPLICATION_ID_CONFIG, "app2");
    config.put(StreamsConfig.COMMIT_INTERVAL_MS_CONFIG, 30000);
    config.put(StreamsConfig.NUM_STREAM_THREADS_CONFIG, threads);
    config.put(StreamsConfig.REPLICATION_FACTOR_CONFIG, replicationFactor);
    return new StreamsBuilderFactoryBean(config);
  }
}

Now comes the fun part, using the the streamsBuilder to build your app (app1 in this example).

import lombok.extern.slf4j.Slf4j;
import org.apache.kafka.common.serialization.Serdes;
import org.apache.kafka.streams.KeyValue;
import org.apache.kafka.streams.StreamsBuilder;
import org.apache.kafka.streams.kstream.Consumed;
import org.apache.kafka.streams.kstream.KStream;
import org.apache.kafka.streams.kstream.Produced;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.context.annotation.Bean;
import org.springframework.stereotype.Component;

@Component
@Slf4j
public class App1 {
  @SuppressWarnings("unchecked")
  @Bean("app1StreamTopology")
  public KStream<String, Long> startProcessing(@Qualifier("app1StreamBuilder") StreamsBuilder builder) {

    final KStream<String, Long> toSquare = builder.stream("toSquare", Consumed.with(Serdes.String(), Serdes.Long()));
    toSquare.map((key, value) -> { // do something with each msg, square the values in our case
      return KeyValue.pair(key, value * value);
    }).to("squared", Produced.with(Serdes.String(), Serdes.Long())); // send downstream to another topic

    return toSquare;
  }
}

Hope this helps.

Kafka commands to create a topic and send data into the topic

Create Topic:

kafka-topics.bat --zookeeper localhost:2181 --create --topic toSquare --replication-factor 1 --partitions 1

Send data to topic:

kafka-console-producer --broker-list localhost:9092 --topic testStreamsIn --property parse.key=true --property key.separator=,
test,12345678

Answer 2

Easy way to get started with Kafka Streams on Spring Boot:

1. Bootstrap your project using https://start.spring.io. Select Cloud Stream and Spring for Apache Kafka Streams as dependencies. Here is the link to preconfigured project template: https://start.spring.io/#!language=java&dependencies=kafka-streams,cloud-stream

2. Define KStream bean in you app. As an example, this is a very basic consumer application. It simply consumes data and logs records from the KStream to the standard output.

   @SpringBootApplication
   public class Application {
   
       public static void main(String[] args) {
           SpringApplication.run(Main.class, args);
       }
   
       @Bean
       public java.util.function.Consumer<KStream<String, String>> process() {
           return stream -> stream.foreach((key, value) -> {
               System.out.println(key + ":" + value);
           });
       }
   }
   

   In this application, we defined a single input binding. Spring will create this binding with a name process-in-0, i.e. the name of the bean function followed by -in-, followed by the ordinal position of the parameter. You use this binding name to set other properties such as topic name. For example, spring.cloud.stream.bindings.process-in-0.destination=my-topic.

   See more examples here - Spring Cloud Stream Kafka Binder Reference, Programming Model section.

3. Configure application.yaml as follows:

   spring:
     cloud:
       stream:
         bindings:
           process-in-0.destination: my-topic
         kafka:
           streams:
             binder:
               applicationId: my-app
               brokers: localhost:9092
               configuration:
                 default:
                   key:
                     serde: org.apache.kafka.common.serialization.Serdes$StringSerde
                   value:
                     serde: org.apache.kafka.common.serialization.Serdes$StringSerde
   

Answer 3

you can create new spring boot project from scratch using https://start.spring.io/ select the necessary versions/dependencies accordingly and generate/download the project.

you can start implementing the kstream api methods (https://kafka.apache.org/10/javadoc/org/apache/kafka/streams/kstream/KStream.html)