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Getting Started to SmallRye Reactive Messaging with RabbitMQ

This guide demonstrates how your Quarkus application can utilize SmallRye Reactive Messaging to interact with RabbitMQ.

这项技术被认为是preview。

preview(预览) 中,不保证向后兼容和在生态系统中的存在。具体的改进可能需要改变配置或API,并且正在计划变得 稳定 。欢迎在我们的 邮件列表 中提供反馈,或在我们的 GitHub问题列表 中提出问题。

For a full list of possible statuses, check our FAQ entry.

Prerequisites

完成这个指南,你需要:

  • 大概15分钟

  • 编辑器

  • 安装JDK 11以上版本并正确配置了 JAVA_HOME

  • Apache Maven 3.9.5

  • Docker and Docker Compose or Podman, and Docker Compose

  • 如果你愿意的话,还可以选择使用Quarkus CLI

  • 如果你想构建原生可执行程序,可以选择安装Mandrel或者GraalVM,并正确配置(或者使用Docker在容器中进行构建)

Architecture

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

Architecture,

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 put the quote request on pending. At the same time the generated request id is sent to the quote-requests exchange.

Producer

The second application, the processor, in turn, will read from the quote-requests queue put a random price to the quote, and send it to an exchange named quotes.

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

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.

Clone the Git repository: git clone https://github.com/quarkusio/quarkus-quickstarts.git, or download an archive.

The solution is located in the rabbitmq-quickstart directory.

Creating the Maven Project

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

To create the producer project, in a terminal run:

CLI
quarkus create app org.acme:rabbitmq-quickstart-producer \
    --extension='smallrye-reactive-messaging-rabbitmq,resteasy-reactive-jackson' \
    --no-code

创建Grade项目,请添加 --gradle 或者 --gradle-kotlin-dsl 参数。

For more information about how to install and use the Quarkus CLI, see the Quarkus CLI guide.

Maven
mvn io.quarkus.platform:quarkus-maven-plugin:3.5.3:create \
    -DprojectGroupId=org.acme \
    -DprojectArtifactId=rabbitmq-quickstart-producer \
    -Dextensions='smallrye-reactive-messaging-rabbitmq,resteasy-reactive-jackson' \
    -DnoCode

创建Grade项目,请添加 -DbuildTool=gradle 或者 -DbuildTool=gradle-kotlin-dsl 参数。

For Windows users:

  • If using cmd, (don’t use backward slash \ and put everything on the same line)

  • If using Powershell, wrap -D parameters in double quotes e.g. "-DprojectArtifactId=rabbitmq-quickstart-producer"

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

  1. The Reactive Messaging RabbitMQ connector

  2. RESTEasy Reactive and its Jackson support to handle JSON payloads

If you already have your Quarkus project configured, you can add the smallrye-reactive-messaging-rabbitmq extension to your project by running the following command in your project base directory:

CLI
quarkus extension add smallrye-reactive-messaging-rabbitmq
Maven
./mvnw quarkus:add-extension -Dextensions='smallrye-reactive-messaging-rabbitmq'
Gradle
./gradlew addExtension --extensions='smallrye-reactive-messaging-rabbitmq'

这将在你的 pom.xml 中添加以下内容:

pom.xml
<dependency>
    <groupId>io.quarkus</groupId>
    <artifactId>quarkus-smallrye-reactive-messaging-rabbitmq</artifactId>
</dependency>
build.gradle
implementation("io.quarkus:quarkus-smallrye-reactive-messaging-rabbitmq")

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

CLI
quarkus create app org.acme:rabbitmq-quickstart-processor \
    --extension='smallrye-reactive-messaging-rabbitmq' \
    --no-code

创建Grade项目,请添加 --gradle 或者 --gradle-kotlin-dsl 参数。

For more information about how to install and use the Quarkus CLI, see the Quarkus CLI guide.

Maven
mvn io.quarkus.platform:quarkus-maven-plugin:3.5.3:create \
    -DprojectGroupId=org.acme \
    -DprojectArtifactId=rabbitmq-quickstart-processor \
    -Dextensions='smallrye-reactive-messaging-rabbitmq' \
    -DnoCode

创建Grade项目,请添加 -DbuildTool=gradle 或者 -DbuildTool=gradle-kotlin-dsl 参数。

For Windows users:

  • If using cmd, (don’t use backward slash \ and put everything on the same line)

  • If using Powershell, wrap -D parameters in double quotes e.g. "-DprojectArtifactId=rabbitmq-quickstart-processor"

At that point you should have the following structure:

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

Open the two projects in your favorite IDE.

The Quote object

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/rabbitmq/model/Quote.java file, with the following content:

package org.acme.rabbitmq.model;

import io.quarkus.runtime.annotations.RegisterForReflection;

@RegisterForReflection
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 +
                '}';
    }
}

JSON representation of Quote objects will be used in messages sent to the RabbitMQ queues and also in the server-sent events sent to browser clients.

Quarkus has built-in capabilities to deal with JSON RabbitMQ messages.

@RegisterForReflection

The @RegisterForReflection annotation instructs Quarkus to include the class (including fields and methods) when building the native executable. This will be useful later when we run the applications as native executables inside containers. Without, the native compilation would remove the fields and methods during the dead-code elimination phase.

Sending quote request

Inside the producer project locate the generated src/main/java/org/acme/rabbitmq/producer/QuotesResource.java file, and update the content to be:

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

import io.smallrye.mutiny.Multi;

@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" channel (which
     * maps to the "quote-requests" RabbitMQ exchange) 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();
    }
}
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 RabbitMQ queue using the emitter.

This channel is mapped to a RabbitMQ exchange using the configuration we will add to the application.properties file. Open the src/main/resource/application.properties file and add:

# Configure the outgoing RabbitMQ exchange `quote-requests`
mp.messaging.outgoing.quote-requests.connector=smallrye-rabbitmq
mp.messaging.outgoing.quote-requests.exchange.name=quote-requests

All we need to specify is the smallrye-rabbitmq connector. By default, reactive messaging maps the channel name quote-requests to the same RabbitMQ exchange name.

Processing quote requests

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

package org.acme.rabbitmq.processor;

import java.util.Random;

import jakarta.enterprise.context.ApplicationScoped;

import org.acme.rabbitmq.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" RabbitMQ queue and giving out a random quote.
 * The result is pushed to the "quotes" RabbitMQ exchange.
 */
@ApplicationScoped
public class QuoteProcessor {

    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(1000);
        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.

The process method is called for every RabbitMQ message from the quote-requests queue, and will send a Quote object to the quotes exchange.

As with the previous example we need to configure the connectors in the application.properties file. Open the src/main/resources/application.properties file and add:

# Configure the incoming RabbitMQ queue `quote-requests`
mp.messaging.incoming.requests.connector=smallrye-rabbitmq
mp.messaging.incoming.requests.queue.name=quote-requests
mp.messaging.incoming.requests.exchange.name=quote-requests

# Configure the outgoing RabbitMQ exchange `quotes`
mp.messaging.outgoing.quotes.connector=smallrye-rabbitmq
mp.messaging.outgoing.quotes.exchange.name=quotes

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

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

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

  • quote-requests → RabbitMQ queue from which we read the quote requests

  • quotes → RabbitMQ exchange in which we write the quotes

Receiving quotes

Back to our producer project. Let’s modify the QuotesResource to consume quotes, bind it to an HTTP endpoint to send events to clients:

import io.smallrye.mutiny.Multi;
//...

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

/**
 * Endpoint retrieving the "quotes" queue 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)

Again we need to configure the incoming quotes channel inside producer project. Add the following inside application.properties file:

# Configure the outgoing `quote-requests` queue
mp.messaging.outgoing.quote-requests.connector=smallrye-rabbitmq

# Configure the incoming `quotes` queue
mp.messaging.incoming.quotes.connector=smallrye-rabbitmq

The HTML page

Final touch, the HTML page reading the converted prices using SSE.

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

<!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <title>Quotes</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").append(row);
        });
    });
    var source = new EventSource("/quotes");
    source.onmessage = (event) => {
      var json = JSON.parse(event.data);
      $(`#${json.id}`).html(function(index, html) {
        return html.replace("Pending", `\$\xA0${json.price}`);
      });
    };
</script>
</html>

Nothing spectacular here. On each received quote, it updates the page.

Get it running

You just need to run both applications using:

> mvn -f rabbitmq-quickstart-producer quarkus:dev

And, in a separate terminal:

> mvn -f rabbitmq-quickstart-processor quarkus:dev

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

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

Running in JVM or Native mode

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

version: '2'

services:

  rabbit:
    image: rabbitmq:3.12-management
    ports:
      - "5672:5672"
    networks:
      - rabbitmq-quickstart-network

  producer:
    image: quarkus-quickstarts/rabbitmq-quickstart-producer:1.0-${QUARKUS_MODE:-jvm}
    build:
      context: rabbitmq-quickstart-producer
      dockerfile: src/main/docker/Dockerfile.${QUARKUS_MODE:-jvm}
    environment:
      RABBITMQ_HOST: rabbit
      RABBITMQ_PORT: 5672
    ports:
      - "8080:8080"
    networks:
      - rabbitmq-quickstart-network

  processor:
    image: quarkus-quickstarts/rabbitmq-quickstart-processor:1.0-${QUARKUS_MODE:-jvm}
    build:
      context: rabbitmq-quickstart-processor
      dockerfile: src/main/docker/Dockerfile.${QUARKUS_MODE:-jvm}
    environment:
      RABBITMQ_HOST: rabbit
      RABBITMQ_PORT: 5672
    networks:
      - rabbitmq-quickstart-network

networks:
  rabbitmq-quickstart-network:
    name: rabbitmq-quickstart

Note how the RabbitMQ broker location is configured. The rabbitmq-host and rabbitmq-port (AMQP_HOST and AMQP_PORT environment variables) properties configure location.

First, make sure you stopped the applications, and build both applications in JVM mode with:

> mvn -f rabbitmq-quickstart-producer clean package
> mvn -f rabbitmq-quickstart-processor clean package

Once packaged, run docker compose up --build. The UI is exposed on http://localhost:8080/quotes.html

要以本地方式运行你的应用程序,我们首先需要构建本地可执行文件:

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

-Dquarkus.native.container-build=true 指示Quarkus构建可以在容器中运行的64位Linux本地可执行文件。然后,使用以下命令运行系统:

> export QUARKUS_MODE=native
> docker compose up --build

与之前一样,UI也是在 http://localhost:8080/quotes.html

进一步探索

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

If you did the Kafka, you have realized that it’s the same code. The only difference is the connector configuration and the JSON mapping.