WebSockets & Real-Time Systems with Spring · Aula

Construção de serviços reativos em tempo real

Desenvolva serviços reativos de ponta a ponta em tempo real que tirem partido do Project Reactor.

Construção de serviços reativos em tempo real é uma aula grátis de WebSockets & Real-Time Systems with Spring no CoddyKit. Esta é a aula 3 de 4. Você pode ler a aula completa abaixo gratuitamente — depois pratica ao vivo no navegador com um editor de código integrado e um tutor de IA 24/7. Faz parte do caminho de aprendizado de WebSockets & Real-Time Systems with Spring, e seu progresso é sincronizado entre a web e o app CoddyKit. O curso de WebSockets & Real-Time Systems with Spring inclui 4 aulas no total.

Partes desta aula ainda não foram traduzidas e aparecem em inglês.

Reactive Real-Time Services

Welcome! In this lesson, we'll build end-to-end reactive real-time services using Spring WebFlux and Project Reactor.

Reactive services are excellent for handling many concurrent connections efficiently. They offer better scalability and responsiveness compared to traditional blocking approaches.

Project Reactor: Flux & Mono

At the heart of reactive programming in Spring is Project Reactor. It provides two key types for handling data streams:

Flux: Represents a stream of 0 to N items. Think of it as a publisher that can emit multiple values over time.
Mono: Represents a stream of 0 to 1 item. Useful for operations that return a single result or no result (like void).

These types allow us to compose asynchronous operations in a clear and non-blocking way.

WebFlux WebSocket Handlers

Spring WebFlux uses the WebSocketHandler interface to manage WebSocket connections. Its main method, handle(), takes a WebSocketSession and returns a Mono.

This Mono signifies that the handling process is complete once the reactive stream it represents finishes. We can use Flux inside to send continuous messages.

Designing a Reactive Data Source

To build a real-time service, we need a source of data. Let's create a simple Flux that emits a message periodically. This simulates a real-time data feed, like a stock ticker or a sensor reading.

We'll use Flux.interval() to generate events and map() to transform them into useful messages.

Implementing a Ticker Service

Here's a basic WebSocketHandler that sends a 'tick' message every second. It uses the Flux.interval() we discussed.

The session.send() method takes a Flux to push data to the client.

import org.springframework.web.reactive.socket.WebSocketHandler;
import org.springframework.web.reactive.socket.WebSocketMessage;
import org.springframework.web.reactive.socket.WebSocketSession;
import reactor.core.publisher.Flux;
import reactor.core.publisher.Mono;

import java.time.Duration;

public class TimeTickerHandler implements WebSocketHandler {

    @Override
    public Mono<Void> handle(WebSocketSession session) {
        // Send messages to the client
        Flux<WebSocketMessage> output = Flux.interval(Duration.ofSeconds(1))
            .map(i -> session.textMessage("Tick #" + i));

        // Receive messages from the client (and ignore them for now)
        // We use .then() to ensure the Mono<Void> completes only when the session closes.
        Mono<Void> input = session.receive().then();

        return session.send(output).and(input);
    }
}

Full Runnable Ticker Service

To make our TimeTickerHandler runnable, we need a Spring Boot application. This example sets up the WebFlux server and registers our handler.

Access this via ws://localhost:8080/ticker in a WebSocket client (like Postman or a browser's DevTools console) to see it in action.

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.Bean;
import org.springframework.web.reactive.handler.SimpleUrlHandlerMapping;
import org.springframework.web.reactive.socket.WebSocketHandler;
import org.springframework.web.reactive.socket.WebSocketMessage;
import org.springframework.web.reactive.socket.WebSocketSession;
import org.springframework.web.reactive.socket.server.support.WebSocketHandlerAdapter;
import reactor.core.publisher.Flux;
import reactor.core.publisher.Mono;

import java.time.Duration;
import java.util.HashMap;
import java.util.Map;

@SpringBootApplication
public class ReactiveTickerApplication {

    public static void main(String[] args) {
        SpringApplication.run(ReactiveTickerApplication.class, args);
    }

    @Bean
    public SimpleUrlHandlerMapping webSocketHandlerMapping(WebSocketHandler webSocketHandler) {
        Map<String, WebSocketHandler> map = new HashMap<>();
        map.put("/ticker", webSocketHandler);
        return new SimpleUrlHandlerMapping(map, 1);
    }

    @Bean
    public WebSocketHandler webSocketHandler() {
        return new WebSocketHandler() {
            @Override
            public Mono<Void> handle(WebSocketSession session) {
                // Send a 'tick' message every second
                Flux<WebSocketMessage> output = Flux.interval(Duration.ofSeconds(1))
                    .map(i -> session.textMessage("Tick #" + i + " at " + System.currentTimeMillis()));

                // Handle incoming messages (e.g., echo them back, or process commands)
                // For this example, we'll just log and then complete the input stream
                Mono<Void> input = session.receive()
                    .doOnNext(msg -> System.out.println("Received: " + msg.getPayloadAsText()))
                    .then(); // ensures the Mono completes after processing all incoming

                return session.send(output).and(input);
            }
        };
    }

    @Bean
    public WebSocketHandlerAdapter handlerAdapter() {
        return new WebSocketHandlerAdapter();
    }
}

Handling Client Input

Our previous ticker only sent data. To make it truly interactive, we can also process messages coming from the client.

The session.receive() method returns a Flux that represents incoming messages. You can subscribe to this Flux to react to client input, for example, by filtering, transforming, or using the data to control the output stream.

Error Handling in Reactive Streams

Errors can occur in any part of a reactive pipeline. Project Reactor provides operators to handle these gracefully, preventing your application from crashing:

onErrorResume(): Recovers from an error by switching to an alternative publisher.
doOnError(): Performs a side-effect (like logging) when an error occurs, then re-throws it or completes.
retry(): Retries the sequence if an error occurs.

Using these helps build robust real-time services that can recover from transient issues.

Backpressure Management

Backpressure is crucial for reactive systems. It's a mechanism where a consumer can signal to a producer that it's receiving data too quickly and needs the producer to slow down.

Project Reactor handles backpressure automatically. When a client can't keep up, the WebSocket connection might buffer messages or eventually close, but the server-side Flux won't overwhelm itself or the network.

Reactive Service Concepts

Which of the following are key characteristics of building reactive real-time services with Spring WebFlux and Project Reactor?

Recap: Reactive Real-Time

We've explored how to build reactive real-time services using Spring WebFlux and Project Reactor.

We saw how Flux can generate continuous data streams.
We implemented a WebSocketHandler to push these streams to clients.
We configured a basic Spring Boot application to host our reactive WebSocket endpoint.
We touched upon error handling and backpressure, vital for robust systems.

These principles enable highly scalable and responsive real-time applications.

Perguntas Frequentes

A aula “Construção de serviços reativos em tempo real” é grátis?

Sim — o texto completo de “Construção de serviços reativos em tempo real” é grátis para ler aqui na web. Para praticá-la interativamente (um editor de código integrado e um tutor de IA 24/7) e desbloquear o restante do curso de WebSockets & Real-Time Systems with Spring, atualize para CoddyKit PRO. O curso de WebSockets & Real-Time Systems with Spring inclui 4 aulas no total.

O que vou aprender em “Construção de serviços reativos em tempo real”?

Desenvolva serviços reativos de ponta a ponta em tempo real que tirem partido do Project Reactor. Você pratica WebSockets & Real-Time Systems with Spring com código prático que executa diretamente no navegador, e um tutor de IA 24/7 responde suas dúvidas enquanto trabalha na aula.

Preciso ter experiência prévia para começar WebSockets & Real-Time Systems with Spring?

Nenhuma experiência prévia é necessária. WebSockets & Real-Time Systems with Spring no CoddyKit é estruturado para alunos iniciantes até avançados, então você pode começar aqui ou desde o início e aprender no seu ritmo. Esta é a aula 3 de 4.

Quanto tempo leva a aula “Construção de serviços reativos em tempo real”?

A maioria das aulas CoddyKit leva cerca de 5–10 minutos. Cada uma é compacta e interativa, então você faz progresso constante e retoma exatamente de onde parou entre web e app.

Posso escrever e executar código nesta aula de WebSockets & Real-Time Systems with Spring?

Sim. Cada aula de WebSockets & Real-Time Systems with Spring inclui um editor de código integrado, então você escreve e executa código real direto no navegador e recebe feedback de IA instantaneamente — nenhuma configuração local necessária.

Todas as aulas deste curso

Introdução à programação reativa
Manipuladores WebSocket do WebFlux
Construção de serviços reativos em tempo real
Gerenciamento da contrapressão em fluxos reativos

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