Filas de tarefas com Supabase e workers
Explore estratégias para implementar o processamento de tarefas em segundo plano e filas de mensagens usando o Supabase e serviços externos de processamento.
Filas de tarefas com Supabase e workers é uma aula grátis de Supabase Backend as a Service no CoddyKit. Esta é a aula 2 de 3. 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 Supabase Backend as a Service, e seu progresso é sincronizado entre a web e o app CoddyKit. O curso de Supabase Backend as a Service inclui 3 aulas no total.
Partes desta aula ainda não foram traduzidas e aparecem em inglês.
Tasks: Background vs. Foreground
Imagine your app needs to send a welcome email, process a large image, or generate a report. If your user has to wait for these long tasks to finish, their experience suffers.
These are background tasks: operations that don't need immediate user interaction and can run independently without blocking the user interface.
Introducing Task Queues
A task queue (or message queue) is a system that allows different parts of your application to communicate asynchronously. It acts like a temporary holding area for tasks.
- Producers: Add tasks to the queue.
- Consumers (Workers): Pick up tasks from the queue and process them.
This decouples the task creation from its execution.
Why Use a Task Queue?
Task queues bring several key benefits to your application architecture:
- Improved Responsiveness: Users don't wait for long operations.
- Scalability: You can add more workers to handle increased load.
- Reliability: Tasks can be retried if they fail.
- Decoupling: Separates task submission from task execution.
Supabase as a Simple Queue
While Supabase isn't a dedicated message queue, its powerful PostgreSQL database can serve as a simple task queue for many use cases. We can create a dedicated table to store tasks.
A typical tasks table might have columns like:
id(Primary Key)payload(JSONB, for task data)status(e.g., 'pending', 'processing', 'completed', 'failed')created_at(Timestamp)processed_at(Timestamp, nullable)
Enqueueing Tasks (Producer)
To enqueue a task, your client-side application or API endpoint simply inserts a new row into the tasks table with a 'pending' status. The payload column holds all the necessary data for the worker to process.
For example, to send a welcome email after user signup:
import { createClient } from '@supabase/supabase-js';
const supabaseUrl = 'YOUR_SUPABASE_URL';
const supabaseKey = 'YOUR_SUPABASE_ANON_KEY';
const supabase = createClient(supabaseUrl, supabaseKey);
async function enqueueWelcomeEmail(userId, email) {
const { data, error } = await supabase
.from('tasks')
.insert({
type: 'send_welcome_email',
payload: { userId, email },
status: 'pending'
});
if (error) {
console.error('Error enqueueing task:', error.message);
} else {
console.log('Welcome email task enqueued!');
}
}
// Example usage (not runnable directly without Supabase setup)
// enqueueWelcomeEmail('user123', 'test@example.com');Introducing External Workers
An external worker is a separate application or service that continuously monitors the task queue for new jobs. When it finds a 'pending' task, it picks it up, processes it, and updates its status.
Workers can be written in any language (Node.js, Python, Go) and run on various platforms (servers, serverless functions, containers). They connect to your Supabase database to read and update task records.
Dequeueing Tasks (Consumer/Worker)
A worker needs to:
- Fetch 'pending' tasks.
- Mark a task as 'processing' to prevent other workers from picking it up.
- Execute the task logic using the
payload. - Update the task status to 'completed' or 'failed'.
Workers can either poll (periodically check) or use Supabase's Realtime feature to listen for new task insertions.
Code: Simple Worker Logic (Polling)
Here's a simplified Node.js worker logic that polls the Supabase tasks table every few seconds. Remember to replace placeholder values.
// worker.js
const { createClient } = require('@supabase/supabase-js');
const SUPABASE_URL = 'YOUR_SUPABASE_URL';
const SUPABASE_KEY = 'YOUR_SUPABASE_SERVICE_ROLE_KEY'; // Use service key for workers
const supabase = createClient(SUPABASE_URL, SUPABASE_KEY);
async function processTask(task) {
console.log(`Processing task ${task.id}: ${task.type}`);
// Simulate work (e.g., sending email, processing image)
await new Promise(resolve => setTimeout(resolve, 2000));
console.log(`Task ${task.id} processed.`);
// In a real app, this would involve calling an email API etc.
}
async function runWorker() {
console.log('Worker started, looking for tasks...');
setInterval(async () => {
try {
// Fetch one pending task and lock it by updating status
const { data: tasks, error } = await supabase
.from('tasks')
.select('*')
.eq('status', 'pending')
.order('created_at', { ascending: true })
.limit(1);
if (error) throw error;
if (tasks.length > 0) {
const task = tasks[0];
// Atomically update status to 'processing'
const { error: updateError } = await supabase
.from('tasks')
.update({ status: 'processing', processed_at: new Date().toISOString() })
.eq('id', task.id)
.eq('status', 'pending'); // Ensure no other worker picked it up
if (updateError) {
if (updateError.code === '40600') { // Row already updated by another process
console.log(`Task ${task.id} already picked up.`);
return;
}
throw updateError;
}
await processTask(task);
// Update status to 'completed'
await supabase
.from('tasks')
.update({ status: 'completed' })
.eq('id', task.id);
} else {
// console.log('No pending tasks.');
}
} catch (err) {
console.error('Worker error:', err.message);
// Implement error handling, e.g., update task status to 'failed'
}
}, 5000); // Poll every 5 seconds
}
// To run this: node worker.js
// (Requires 'npm install @supabase/supabase-js' and a Supabase project)
runWorker();Task States & Reliability
Properly managing task states is crucial for reliability:
- Pending: Task is waiting to be processed.
- Processing: Worker has picked up the task.
- Completed: Task finished successfully.
- Failed: Task encountered an error.
For failed tasks, you might implement retries (e.g., after a delay) and ensure tasks are idempotent (running them multiple times has the same effect as running once) to prevent unintended side effects.
Queueing Question
You've learned about using Supabase and external workers for task queues. Consider a scenario where a user uploads a large video file that needs transcoding.
Recap: Task Queues & Workers
We've explored how task queues enable efficient background processing in your applications. By using Supabase as a simple queue and external workers, you can:
- Offload long-running operations.
- Improve user experience by keeping your app responsive.
- Build more scalable and robust systems.
This pattern is fundamental for building complex, high-performance web and mobile applications.
Perguntas Frequentes
A aula “Filas de tarefas com Supabase e workers” é grátis?
Sim — o texto completo de “Filas de tarefas com Supabase e workers” 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 Supabase Backend as a Service, atualize para CoddyKit PRO. O curso de Supabase Backend as a Service inclui 3 aulas no total.
O que vou aprender em “Filas de tarefas com Supabase e workers”?
Explore estratégias para implementar o processamento de tarefas em segundo plano e filas de mensagens usando o Supabase e serviços externos de processamento. Você pratica Supabase Backend as a Service 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 Supabase Backend as a Service?
Nenhuma experiência prévia é necessária. Supabase Backend as a Service 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 2 de 3.
Quanto tempo leva a aula “Filas de tarefas com Supabase e workers”?
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 Supabase Backend as a Service?
Sim. Cada aula de Supabase Backend as a Service 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
- Integração com serviços externos
- Filas de tarefas com Supabase e workers
- Agendamento de Tarefas Recorrentes com pg_cron