您可以使用https://start.spring.io/ 相应地选择必要的版本/依赖项并生成/下载项目。
您可以开始实现kstream api方法(https://kafka.apache.org/10/javadoc/org/apache/kafka/streams/kstream/kstream.html)

开始使用spring boot上的kafka streams的简单方法：
引导您的项目使用https://start.spring.io. 选择cloudstream和spring作为apachekafka流的依赖项。以下是指向预配置项目模板的链接：https://start.spring.io/#!language=java&dependencies=kafka流、云流
在应用程序中定义kstream bean。例如，这是一个非常基本的消费者应用程序。它只是消耗数据并将记录从kstream记录到标准输出。

@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);
        });
    }
}

在这个应用程序中，我们定义了一个输入绑定。spring将用一个名称创建这个绑定 process-in-0 ，即bean函数的名称后跟 -in- ，后跟参数的顺序位置。使用此绑定名称可以设置其他属性，例如主题名称。例如， spring.cloud.stream.bindings.process-in-0.destination=my-topic .
请参阅更多示例-spring cloud stream kafka活页夹参考，编程模型部分。
配置 application.yaml 具体如下：

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

在spring boot中初始化kafka streams应用程序的另一种方法可以在
https://gist.github.com/itzg/e3ebfd7aec220bf0522e23a65b1296c8
这种方法使用kafkastreamsbean调用kafkastreams.start（），它可以提供拓扑或streambuilder bean。

让我先说，如果你是Kafka流的新手，在上面添加spring boot会增加另一个层次的复杂性，Kafka流有一个很大的学习曲线。以下是让你开始的基本知识：pom：

<!-- https://mvnrepository.com/artifact/org.springframework.kafka/spring-kafka -->
<dependency>
  <groupId>org.springframework.kafka</groupId>
  <artifactId>spring-kafka</artifactId>
  <version>2.1.10.RELEASE</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka-clients -->
<dependency>
  <groupId>org.apache.kafka</groupId>
  <artifactId>kafka-clients</artifactId>
  <version>${kafka.version}</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka -->
<dependency>
  <groupId>org.apache.kafka</groupId>
  <artifactId>kafka_2.12</artifactId>
  <version>${kafka.version}</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka-streams -->
<dependency>
  <groupId>org.apache.kafka</groupId>
  <artifactId>kafka-streams</artifactId>
  <version>${kafka.version}</version>
</dependency>
<!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka-streams -->
<dependency>
  <groupId>org.apache.kafka</groupId>
  <artifactId>connect-api</artifactId>
  <version>${kafka.version}</version>
</dependency>

现在是配置对象。下面的代码假设您正在创建两个流应用程序，请记住，每个应用程序代表其自己的处理拓扑：

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);
  }
}

现在是有趣的部分，使用streamsbuilder构建应用程序（本例中的app1）。

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;
  }
}

希望这有帮助。