Kafka Streams with Spring Boot

Question

我想在我的 spring 引导项目中使用 Kafka Streams 实时处理。所以我需要 Kafka Streams 配置或者我想使用 KStreams 或 KTable，但我在互联网上找不到示例。

我做了生产者和消费者，现在我想实时流式传输。

Answer 1

您可以使用从头开始创建新的 spring 引导项目 https://start.spring.io/ select 相应地 versions/dependencies 和 generate/download 项目。

您可以开始实施 kstream api 方法 (https://kafka.apache.org/10/javadoc/org/apache/kafka/streams/kstream/KStream.html)

Answer 2

首先我要说的是，如果您是 Kafka 流的新手，在其之上添加 spring-boot 会增加另一个级别的复杂性，而 Kafka 流本身具有很大的学习曲线。以下是让您前进的基础知识： 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>

现在是配置对象。下面的代码假定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 构建您的应用程序（本例中为 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;
  }
}

希望对您有所帮助。

Kafka 命令创建主题并将数据发送到主题

创建主题：

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

向主题发送数据：

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

Answer 3

在 Spring Boot 上开始使用 Kafka Streams 的简单方法：

Bootstrap 您的项目使用 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
在您的应用程序中定义 KStream bean。例如，这是一个非常基本的消费者应用程序。它只是使用数据并将记录从 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，我们定义了一个单一的输入绑定。 Spring 将使用名称 process-in-0 创建此绑定，即 bean 函数的名称后跟 -in-，然后是参数的序号位置。您使用此绑定名称来设置其他属性，例如主题名称。例如，spring.cloud.stream.bindings.process-in-0.destination=my-topic.

查看更多示例here - Spring Cloud Stream Kafka Binder 参考，编程模型部分。

配置application.yaml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

Kafka Streams with Spring Boot

Kafka Streams with Spring Boot

apache-kafka

spring-boot

apache-kafka-streams

spring-kafka