Getting Started to Quarkus Messaging with Apache Kafka

本指南演示了 Quarkus 应用如何使用 Quarkus Messaging 与 Apache Kafka 进行交互。

This guide demonstrates how your Quarkus application can utilize Quarkus Messaging to interact with Apache Kafka.

Prerequisites

Unresolved directive in kafka-getting-started.adoc - include::{includes}/prerequisites.adoc[]

Architecture

在本指南中，我们将开发两个与 Kafka 通信的应用。第一个应用向 Kafka 发送 quote request，并从 quote 主题使用 Kafka 消息。第二个应用接收 quote request，并回复 quote。

In this guide, we are going to develop two applications communicating with Kafka. The first application sends a quote request to Kafka and consumes Kafka messages from the quote topic. The second application receives the quote request and sends a quote back.

第一个应用 producer，将让用户通过 HTTP 终端请求一些报价。对于每个报价请求，都会生成一个随机识别符并返回给用户，以标记报价请求为 pending。同时，生成的请求 ID 会通过 Kafka 主题 quote-requests 发送。

The first application, the producer, will let the user request some quotes over an HTTP endpoint. For each quote request a random identifier is generated and returned to the user, to mark the quote request as pending. At the same time, the generated request id is sent over a Kafka topic quote-requests.

第二个应用 processor，将读取 quote-requests 主题，向报价添加一个随机价格，并发送到名为 quotes 的 Kafka 主题。

The second application, the processor, will read from the quote-requests topic, put a random price to the quote, and send it to a Kafka topic named quotes.

最后，_producer_将读取报价并使用服务器发送事件将它们发送到浏览器。因此，用户将看到报价价格从 _pending_实时更新为收到的价格。

Lastly, the producer will read the quotes and send them to the browser using server-sent events. The user will therefore see the quote price updated from pending to the received price in real-time.

Solution

我们建议您按照下一节中的说明一步步创建应用程序。但是，您可以直接转到已完成的示例。

We recommend that you follow the instructions in the next sections and create applications step by step. However, you can go right to the completed example.

克隆 Git 存储库： git clone {quickstarts-clone-url}，或下载 {quickstarts-archive-url}[存档]。

Clone the Git repository: git clone {quickstarts-clone-url}, or download an {quickstarts-archive-url}[archive].

解决方案位于 kafka-quickstart directory。

The solution is located in the kafka-quickstart directory.

Creating the Maven Project

首先，我们需要创建两个项目：producer_和 _processor。

First, we need to create two projects: the producer and the processor.

要在终端中创建 _producer_项目，请运行：

To create the producer project, in a terminal run:

Unresolved directive in kafka-getting-started.adoc - include::{includes}/devtools/create-app.adoc[]

此命令可创建项目结构，并选择我们将要使用的两个 Quarkus 扩展：

This command creates the project structure and selects two Quarkus extensions we will be using:

Quarkus REST (formerly RESTEasy Reactive) and its Jackson support (to handle JSON) to serve the HTTP endpoint.
The Kafka connector for Reactive Messaging

要从相同目录创建 _processor_项目，请运行：

To create the processor project, from the same directory, run:

Unresolved directive in kafka-getting-started.adoc - include::{includes}/devtools/create-app.adoc[]

那时，你应该有以下结构：

At that point, you should have the following structure:

.
├── kafka-quickstart-processor
│  ├── README.md
│  ├── mvnw
│  ├── mvnw.cmd
│  ├── pom.xml
│  └── src
│     └── main
│        ├── docker
│        ├── java
│        └── resources
│           └── application.properties
└── kafka-quickstart-producer
   ├── README.md
   ├── mvnw
   ├── mvnw.cmd
   ├── pom.xml
   └── src
      └── main
         ├── docker
         ├── java
         └── resources
            └── application.properties

在你的首选 IDE 中打开这两个项目。

Open the two projects in your favorite IDE.

Dev Services

使用 dev 模式或进行测试时无需启动 Kafka 代理。Quarkus 会自动为您启动一个代理。详情请参见 Dev Services for Kafka。

No need to start a Kafka broker when using the dev mode or for tests. Quarkus starts a broker for you automatically. See Dev Services for Kafka for details.

The Quote object

Quote 类将同时用于 producer 和 processor 项目。为了简单起见，我们将复制代码。在两个项目中，都创建 src/main/java/org/acme/kafka/model/Quote.java 文件，内容如下：

The Quote class will be used in both producer and processor projects. For the sake of simplicity, we will duplicate the class. In both projects, create the src/main/java/org/acme/kafka/model/Quote.java file, with the following content:

package org.acme.kafka.model;

public class Quote {

    public String id;
    public int price;

    /**
    * Default constructor required for Jackson serializer
    */
    public Quote() { }

    public Quote(String id, int price) {
        this.id = id;
        this.price = price;
    }

    @Override
    public String toString() {
        return "Quote{" +
                "id='" + id + '\'' +
                ", price=" + price +
                '}';
    }
}

发送到 Kafka 主题的消息和发送到 Web 浏览器的服务器发送事件中将使用 Quote 对象的 JSON 表示形式。

JSON representation of Quote objects will be used in messages sent to the Kafka topic and also in the server-sent events sent to web browsers.

Quarkus 具有处理 JSON Kafka 消息的内置功能。在下一节中，我们将为 Jackson 创建序列化程序/解序列化程序类。

Quarkus has built-in capabilities to deal with JSON Kafka messages. In a following section, we will create serializer/deserializer classes for Jackson.

Sending quote request

在 producer 项目中，创建 src/main/java/org/acme/kafka/producer/QuotesResource.java 文件，并添加以下内容：

Inside the producer project, create the src/main/java/org/acme/kafka/producer/QuotesResource.java file and add the following content:

package org.acme.kafka.producer;

import java.util.UUID;

import jakarta.ws.rs.GET;
import jakarta.ws.rs.POST;
import jakarta.ws.rs.Path;
import jakarta.ws.rs.Produces;
import jakarta.ws.rs.core.MediaType;

import org.acme.kafka.model.Quote;
import org.eclipse.microprofile.reactive.messaging.Channel;
import org.eclipse.microprofile.reactive.messaging.Emitter;

@Path("/quotes")
public class QuotesResource {

    @Channel("quote-requests")
    Emitter<String> quoteRequestEmitter; (1)

    /**
     * Endpoint to generate a new quote request id and send it to "quote-requests" Kafka topic using the emitter.
     */
    @POST
    @Path("/request")
    @Produces(MediaType.TEXT_PLAIN)
    public String createRequest() {
        UUID uuid = UUID.randomUUID();
        quoteRequestEmitter.send(uuid.toString()); (2)
        return uuid.toString(); (3)
    }
}

1	Inject a Reactive Messaging `Emitter` to send messages to the `quote-requests` channel.
2	On a post request, generate a random UUID and send it to the Kafka topic using the emitter.
3	Return the same UUID to the client.

quote-requests 通道将被管理为 Kafka 主题，因为它是类路径中的唯一连接器。如果未另行指示（比如在本示例中），Quarkus 将通道名称用作主题名称。因此在本示例中，应用会写入 quote-requests 主题。Quarkus 还会自动配置序列化程序，因为它发现 Emitter 会生成 String 值。

The quote-requests channel is going to be managed as a Kafka topic, as that’s the only connector on the classpath. If not indicated otherwise, like in this example, Quarkus uses the channel name as topic name. So, in this example, the application writes into the quote-requests topic. Quarkus also configures the serializer automatically, because it finds that the Emitter produces String values.

当你有多个连接器时，你需要在应用程序配置中指明你要在其中使用哪个连接器。

When you have multiple connectors, you would need to indicate which connector you want to use in the application configuration.

Processing quote requests

现在，让我们使用报价请求并提供价格。在 processor 项目中，创建 src/main/java/org/acme/kafka/processor/QuotesProcessor.java 文件，并添加以下内容：

Now let’s consume the quote request and give out a price. Inside the processor project, create the src/main/java/org/acme/kafka/processor/QuotesProcessor.java file and add the following content:

package org.acme.kafka.processor;

import java.util.Random;

import jakarta.enterprise.context.ApplicationScoped;

import org.acme.kafka.model.Quote;
import org.eclipse.microprofile.reactive.messaging.Incoming;
import org.eclipse.microprofile.reactive.messaging.Outgoing;

import io.smallrye.reactive.messaging.annotations.Blocking;

/**
 * A bean consuming data from the "quote-requests" Kafka topic (mapped to "requests" channel) and giving out a random quote.
 * The result is pushed to the "quotes" Kafka topic.
 */
@ApplicationScoped
public class QuotesProcessor {

    private Random random = new Random();

    @Incoming("requests") (1)
    @Outgoing("quotes")   (2)
    @Blocking             (3)
    public Quote process(String quoteRequest) throws InterruptedException {
        // simulate some hard working task
        Thread.sleep(200);
        return new Quote(quoteRequest, random.nextInt(100));
    }
}

1	Indicates that the method consumes the items from the `requests` channel.
2	Indicates that the objects returned by the method are sent to the `quotes` channel.
3	Indicates that the processing is blocking and cannot be run on the caller thread.

对于来自 quote-requests 主题的每个 Kafka record，反应消息都会调用 process 方法，并将返回的 Quote 对象发送到 quotes 通道。在这种情况下，我们需要在 application.properties 文件中配置通道，以配置 requests 和 quotes 通道：

For every Kafka record from the quote-requests topic, Reactive Messaging calls the process method, and sends the returned Quote object to the quotes channel. In this case, we need to configure the channel in the application.properties file, to configures the requests and quotes channels:

%dev.quarkus.http.port=8081

# Configure the incoming `quote-requests` Kafka topic
mp.messaging.incoming.requests.topic=quote-requests
mp.messaging.incoming.requests.auto.offset.reset=earliest

请注意，在这种情况下，我们有一个入站和一个出站连接器配置，每个都明确命名。配置属性的结构如下：

Note that in this case we have one incoming and one outgoing connector configuration, each one distinctly named. The configuration properties are structured as follows:

mp.messaging.[outgoing|incoming].{channel-name}.property=value

channel-name 片段必须与 @Incoming 和 @Outgoing 注释中设置的值相匹配：

The channel-name segment must match the value set in the @Incoming and @Outgoing annotation:

quote-requests → Kafka topic from which we read the quote requests
quotes → Kafka topic in which we write the quotes

Kafka 文档的 Producer configuration 和 Consumer configuration 部分提供了此配置的更多详细信息。这些属性使用前缀 kafka 配置。Kafka Reference Guide - Configuration 中提供了详尽的配置属性列表。

More details about this configuration is available on the Producer configuration and Consumer configuration section from the Kafka documentation. These properties are configured with the prefix kafka. An exhaustive list of configuration properties is available in Kafka Reference Guide - Configuration.

当消费者组没有提交的偏移量时，mp.messaging.incoming.requests.auto.offset.reset=earliest 指示应用程序从第一个偏移量开始读取主题。换句话说，它还将处理我们在启动处理器应用程序之前发送的消息。

mp.messaging.incoming.requests.auto.offset.reset=earliest instructs the application to start reading the topics from the first offset, when there is no committed offset for the consumer group. In other words, it will also process messages sent before we start the processor application.

无需设置序列化器或反序列化器。Quarkus 会检测它们，如果未找到任何，则使用 JSON 序列化生成它们。

There is no need to set serializers or deserializers. Quarkus detects them, and if none are found, generates them using JSON serialization.

Receiving quotes

回到我们的 producer 项目。让我们修改 QuotesResource 以使用 Kafka 的引号并通过服务器发送事件将它们发送回客户端：

Back to our producer project. Let’s modify the QuotesResource to consume quotes from Kafka and send them back to the client via Server-Sent Events:

import io.smallrye.mutiny.Multi;

...

@Channel("quotes")
Multi<Quote> quotes; (1)

/**
 * Endpoint retrieving the "quotes" Kafka topic and sending the items to a server sent event.
 */
@GET
@Produces(MediaType.SERVER_SENT_EVENTS) (2)
public Multi<Quote> stream() {
    return quotes; (3)
}

1	Injects the `quotes` channel using the `@Channel` qualifier
2	Indicates that the content is sent using `Server Sent Events`
3	Returns the stream (Reactive Stream)

无需配置任何内容，因为 Quarkus 会自动将 quotes 通道关联到 quotes Kafka 主题。它还将为 Quote 类生成一个反序列化器。

No need to configure anything, as Quarkus will automatically associate the quotes channel to the quotes Kafka topic. It will also generate a deserializer for the Quote class.

Message serialization in Kafka

在此示例中，我们使用 Jackson 序列化/反序列化 Kafka 消息。有关消息序列化的更多选项，请参见 Kafka Reference Guide - Serialization。

Message serialization in Kafka

In this example we used Jackson to serialize/deserialize Kafka messages. For more options on message serialization, see Kafka Reference Guide - Serialization.

我们强烈建议采用使用模式注册表的“合同优先”方法。若要了解有关如何将 Apache Kafka 与模式注册表和 Avro 一起使用的更多信息，请遵循适用于 Avro 的 Using Apache Kafka with Schema Registry and Avro 指南，或者可以遵循 Using Apache Kafka with Schema Registry and JSON Schema 指南。

We strongly suggest adopting a contract-first approach using a schema registry. To learn more about how to use Apache Kafka with the schema registry and Avro, follow the Using Apache Kafka with Schema Registry and Avro guide for Avro or you can follow the Using Apache Kafka with Schema Registry and JSON Schema guide..

The HTML page

最后一步，请求报价并显示通过 SSE 获取的价格的 HTML 页面。

Final touch, the HTML page requesting quotes and displaying the prices obtained over SSE.

在 producer 项目内，使用以下内容创建 src/main/resources/META-INF/resources/quotes.html 文件：

Inside the producer project, create the src/main/resources/META-INF/resources/quotes.html file with the following content:

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>Prices</title>

    <link rel="stylesheet" type="text/css"
          href="https://cdnjs.cloudflare.com/ajax/libs/patternfly/3.24.0/css/patternfly.min.css">
    <link rel="stylesheet" type="text/css"
          href="https://cdnjs.cloudflare.com/ajax/libs/patternfly/3.24.0/css/patternfly-additions.min.css">
</head>
<body>
<div class="container">
    <div class="card">
        <div class="card-body">
            <h2 class="card-title">Quotes</h2>
            <button class="btn btn-info" id="request-quote">Request Quote</button>
            <div class="quotes"></div>
        </div>
    </div>
</div>
</body>
<script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
<script>
    $("#request-quote").click((event) => {
        fetch("/quotes/request", {method: "POST"})
        .then(res => res.text())
        .then(qid => {
            var row = $(`<h4 class='col-md-12' id='${qid}'>Quote # <i>${qid}</i> | <strong>Pending</strong></h4>`);
            $(".quotes").prepend(row);
        });
    });

    var source = new EventSource("/quotes");
    source.onmessage = (event) => {
      var json = JSON.parse(event.data);
      $(`#${json.id}`).html((index, html) => {
        return html.replace("Pending", `\$\xA0${json.price}`);
      });
    };
</script>
</html>

这里没有什么特别之处。当用户单击按钮时，将发出 HTTP 请求以请求报价，并将待处理报价添加到列表中。对于通过 SSE 收到的每个报价，都会更新列表中的相应项目。

Nothing spectacular here. When the user clicks the button, HTTP request is made to request a quote, and a pending quote is added to the list. On each quote received over SSE, the corresponding item in the list is updated.

Get it running

您只需要运行这两个应用程序。在一个终端中，运行：

You just need to run both applications. In one terminal, run:

mvn -f producer quarkus:dev

在另一个终端中，运行：

In another terminal, run:

mvn -f processor quarkus:dev

Quarkus 自动启动一个 Kafka 代理，配置应用程序，并在不同应用程序之间共享 Kafka 代理实例。有关更多详细信息，请参见 Dev Services for Kafka。

Quarkus starts a Kafka broker automatically, configures the application and shares the Kafka broker instance between different applications. See Dev Services for Kafka for more details.

在浏览器中打开 http://localhost:8080/quotes.html，然后通过单击按钮请求一些报价。

Open http://localhost:8080/quotes.html in your browser and request some quotes by clicking the button.

Running in JVM or Native mode

当不在 dev 或测试模式下运行时，需要启动 Kafka 代理。您可以遵循 Apache Kafka website 中的说明，或使用以下内容创建一个 docker-compose.yaml 文件：

When not running in dev or test mode, you will need to start your Kafka broker. You can follow the instructions from the Apache Kafka website or create a docker-compose.yaml file with the following content:

version: '3.5'

services:

  zookeeper:
    image: quay.io/strimzi/kafka:0.41.0-kafka-3.7.0
    command: [
      "sh", "-c",
      "bin/zookeeper-server-start.sh config/zookeeper.properties"
    ]
    ports:
      - "2181:2181"
    environment:
      LOG_DIR: /tmp/logs
    networks:
      - kafka-quickstart-network

  kafka:
    image: quay.io/strimzi/kafka:0.41.0-kafka-3.7.0
    command: [
      "sh", "-c",
      "bin/kafka-server-start.sh config/server.properties --override listeners=$${KAFKA_LISTENERS} --override advertised.listeners=$${KAFKA_ADVERTISED_LISTENERS} --override zookeeper.connect=$${KAFKA_ZOOKEEPER_CONNECT}"
    ]
    depends_on:
      - zookeeper
    ports:
      - "9092:9092"
    environment:
      LOG_DIR: "/tmp/logs"
      KAFKA_ADVERTISED_LISTENERS: PLAINTEXT://kafka:9092
      KAFKA_LISTENERS: PLAINTEXT://0.0.0.0:9092
      KAFKA_ZOOKEEPER_CONNECT: zookeeper:2181
    networks:
      - kafka-quickstart-network

  producer:
    image: quarkus-quickstarts/kafka-quickstart-producer:1.0-${QUARKUS_MODE:-jvm}
    build:
      context: producer
      dockerfile: src/main/docker/Dockerfile.${QUARKUS_MODE:-jvm}
    depends_on:
      - kafka
    environment:
      KAFKA_BOOTSTRAP_SERVERS: kafka:9092
    ports:
      - "8080:8080"
    networks:
      - kafka-quickstart-network

  processor:
    image: quarkus-quickstarts/kafka-quickstart-processor:1.0-${QUARKUS_MODE:-jvm}
    build:
      context: processor
      dockerfile: src/main/docker/Dockerfile.${QUARKUS_MODE:-jvm}
    depends_on:
      - kafka
    environment:
      KAFKA_BOOTSTRAP_SERVERS: kafka:9092
    networks:
      - kafka-quickstart-network

networks:
  kafka-quickstart-network:
    name: kafkaquickstart

确保首先使用以下内容在 JVM 模式下构建这两个应用程序：

Make sure you first build both applications in JVM mode with:

mvn -f producer package
mvn -f processor package

打包后，运行 docker-compose up。

Once packaged, run docker-compose up.

这是一个开发集群，请勿在生产中使用。

This is a development cluster, do not use in production.

您还可以将我们的应用程序构建并运行为原生可执行文件。首先，将这两个应用程序编译为原生：

You can also build and run our applications as native executables. First, compile both applications as native:

mvn -f producer package -Dnative -Dquarkus.native.container-build=true
mvn -f processor package -Dnative -Dquarkus.native.container-build=true

通过以下方式运行系统：

Run the system with:

export QUARKUS_MODE=native
docker-compose up --build

Going further

本指南已说明了如何使用 Quarkus 与 Kafka 进行交互。它利用 SmallRye Reactive Messaging 构建数据流应用程序。

This guide has shown how you can interact with Kafka using Quarkus. It utilizes SmallRye Reactive Messaging to build data streaming applications.

有关功能和配置选项的详尽列表，请检查 Reference guide for Apache Kafka Extension。

For the exhaustive list of features and configuration options, check the Reference guide for Apache Kafka Extension.

在本指南中，我们探讨了如何使用 Quarkus 消息传递扩展与 Apache Kafka 进行交互。用于 Kafka 的 Quarkus 扩展还允许 using Kafka clients directly。

In this guide we explore how we can interact with Apache Kafka using the Quarkus Messaging extensions. Quarkus extension for Kafka also allows using Kafka clients directly.