Returning Job Data

When a worker completes a job, you often need to return data that can be accessed by other parts of your application. BullMQ provides several ways to handle job results.

Basic Return Values

Return data from your processor function:

import { Worker } from 'bullmq';

const worker = new Worker('tasks', async job => {
  // Perform async processing
  const result = await doSomeAsyncProcessing(job.data);
  
  // Return the result
  return result;
});

The return value can be any JSON-serializable object: strings, numbers, booleans, objects, arrays, or null.

Accessing Return Values

From Worker Events

Listen to the completed event on the worker:

import { Worker } from 'bullmq';

const worker = new Worker('tasks', async job => {
  const data = await processData(job.data);
  return { success: true, data };
});

worker.on('completed', (job, returnvalue) => {
  console.log(`Job ${job.id} completed with result:`, returnvalue);
  // Output: { success: true, data: ... }
});

From Queue Events

Use QueueEvents to listen across all workers:

import { QueueEvents } from 'bullmq';

const queueEvents = new QueueEvents('tasks');

queueEvents.on('completed', ({ jobId, returnvalue }) => {
  console.log(`Job ${jobId} completed with:`, returnvalue);
});

QueueEvents provides a global view of all job events, regardless of which worker processed the job.

From the Job Instance

Retrieve the return value later:

import { Queue, Job } from 'bullmq';

const queue = new Queue('tasks');

// Add a job
const job = await queue.add('process-user', { userId: 123 });

// Wait for completion
await job.waitUntilFinished(queueEvents);

// Access the return value
const result = job.returnvalue;
console.log('Result:', result);

Using getJob

Fetch the job and its result later:

import { Queue } from 'bullmq';

const queue = new Queue('tasks');

// Add a job and store its ID
const job = await queue.add('process-data', { value: 42 });
const jobId = job.id;

// Later, retrieve the job
const retrievedJob = await queue.getJob(jobId);

if (retrievedJob && await retrievedJob.isCompleted()) {
  console.log('Return value:', retrievedJob.returnvalue);
}

Return Value Examples

Simple Values

// Return a string
const worker1 = new Worker('tasks', async job => {
  return 'Success';
});

// Return a number
const worker2 = new Worker('calculations', async job => {
  return 42;
});

// Return a boolean
const worker3 = new Worker('checks', async job => {
  return true;
});

Complex Objects

import { Worker } from 'bullmq';

const worker = new Worker('user-processing', async job => {
  const user = await fetchUser(job.data.userId);
  const profile = await enrichProfile(user);
  const stats = await calculateStats(user);
  
  return {
    userId: user.id,
    email: user.email,
    profileComplete: profile.completeness,
    stats: {
      posts: stats.postCount,
      followers: stats.followerCount,
    },
    processedAt: new Date().toISOString(),
  };
});

worker.on('completed', (job, result) => {
  console.log('User processed:', result.userId);
  console.log('Profile completeness:', result.profileComplete);
  console.log('Stats:', result.stats);
});

Arrays

import { Worker } from 'bullmq';

const worker = new Worker('batch-process', async job => {
  const items = job.data.items;
  const results = [];
  
  for (const item of items) {
    const processed = await processItem(item);
    results.push({
      id: item.id,
      status: processed.success ? 'completed' : 'failed',
      timestamp: Date.now(),
    });
  }
  
  return results;
});

Storing Results Reliably

Storing data in the completed event handler is less reliable because the event handler could fail while the job still completes successfully.

Not recommended:

// ❌ Less reliable - event handler can fail
worker.on('completed', async (job, result) => {
  // If this fails, the job is still marked completed
  // but the result isn't stored!
  await database.saveResult(result);
});

Recommended:

// ✅ More reliable - part of job processing
const worker = new Worker('tasks', async job => {
  const result = await processData(job.data);
  
  // Store result as part of the job
  await database.saveResult(result);
  
  // Return the result as well
  return result;
});

If storing the result fails in the processor, the job will fail and can be retried. If storing fails in an event handler, the job is already completed and the failure goes unnoticed.

Using a Results Queue

For robust microservice architectures, use a dedicated results queue:

import { Queue, Worker } from 'bullmq';

// Processing queue
const taskQueue = new Queue('tasks');
const resultsQueue = new Queue('results');

// Task worker that produces results
const taskWorker = new Worker('tasks', async job => {
  const result = await processTask(job.data);
  
  // Send result to results queue
  await resultsQueue.add('store-result', {
    taskId: job.id,
    result: result,
    processedAt: new Date().toISOString(),
  });
  
  return result;
});

// Results worker that stores results
const resultsWorker = new Worker('results', async job => {
  // Reliably store the result
  await database.saveResult(job.data);
  
  // Notify other services if needed
  await notificationService.send({
    type: 'task-completed',
    taskId: job.data.taskId,
  });
});

Benefits:

Reliability: Results are stored in Redis until successfully processed
Decoupling: Result storage can be handled by a separate service
Retry logic: Failed storage operations are automatically retried
Resilience: If the results service is down, results queue up automatically

Microservice Pattern

Chain services together using result queues:

import { Queue, Worker } from 'bullmq';

// Service 1: Data Fetching
const fetchQueue = new Queue('fetch-data');
const processQueue = new Queue('process-data');

const fetchWorker = new Worker('fetch-data', async job => {
  const data = await externalAPI.fetch(job.data.url);
  
  // Send to processing queue
  await processQueue.add('process', {
    originalJobId: job.id,
    data: data,
  });
  
  return { fetched: true, recordCount: data.length };
});

// Service 2: Data Processing
const storageQueue = new Queue('store-data');

const processWorker = new Worker('process-data', async job => {
  const processed = await transform(job.data.data);
  
  // Send to storage queue
  await storageQueue.add('store', {
    originalJobId: job.data.originalJobId,
    processed: processed,
  });
  
  return { processed: true, itemCount: processed.length };
});

// Service 3: Data Storage
const storageWorker = new Worker('store-data', async job => {
  await database.bulkInsert(job.data.processed);
  
  return {
    stored: true,
    originalJobId: job.data.originalJobId,
  };
});

Combining Return Values with Progress

import { Worker } from 'bullmq';

const worker = new Worker('batch-upload', async job => {
  const files = job.data.files;
  const uploaded = [];
  
  for (let i = 0; i < files.length; i++) {
    const file = files[i];
    
    // Report progress
    await job.updateProgress({
      current: i + 1,
      total: files.length,
      currentFile: file.name,
    });
    
    // Upload and track result
    const result = await uploadFile(file);
    uploaded.push({
      filename: file.name,
      url: result.url,
      size: result.size,
    });
  }
  
  // Return final results
  return {
    totalFiles: files.length,
    uploaded: uploaded,
    totalSize: uploaded.reduce((sum, f) => sum + f.size, 0),
  };
});

worker.on('progress', (job, progress) => {
  console.log(`Upload progress: ${progress.current}/${progress.total}`);
  console.log(`Current file: ${progress.currentFile}`);
});

worker.on('completed', (job, result) => {
  console.log(`Uploaded ${result.totalFiles} files`);
  console.log(`Total size: ${result.totalSize} bytes`);
});

TypeScript Type Safety

Define return value types:

import { Worker, Job } from 'bullmq';

interface TaskData {
  userId: string;
  operation: string;
}

interface TaskResult {
  success: boolean;
  message: string;
  data?: any;
  timestamp: number;
}

const worker = new Worker<TaskData, TaskResult>(
  'tasks',
  async (job: Job<TaskData, TaskResult>) => {
    const result: TaskResult = {
      success: true,
      message: `Processed ${job.data.operation} for ${job.data.userId}`,
      timestamp: Date.now(),
    };
    
    return result; // Type-checked!
  },
);

worker.on('completed', (job, returnvalue: TaskResult) => {
  // returnvalue is typed as TaskResult
  console.log(returnvalue.message);
  console.log(returnvalue.timestamp);
});

Best Practices

Return meaningful data

Include useful information like IDs, counts, timestamps, and status indicators.

Keep return values JSON-serializable

Avoid functions, circular references, or non-serializable objects.

Store critical data in the processor

Don’t rely solely on event handlers for important data persistence.

Use results queues for microservices

Decouple services and improve reliability with dedicated results queues.

Include context in return values

Add timestamps, job IDs, and other metadata to make results self-describing.

Handle large results appropriately

For large data, store in external storage (S3, database) and return references.

Handling Large Results

For large data, avoid storing everything in Redis:

import { Worker } from 'bullmq';
import { uploadToS3 } from './storage';

const worker = new Worker('large-data', async job => {
  const largeData = await generateLargeDataset(job.data);
  
  // Upload to external storage
  const s3Url = await uploadToS3(largeData, {
    bucket: 'my-bucket',
    key: `results/${job.id}.json`,
  });
  
  // Return reference, not the data itself
  return {
    dataUrl: s3Url,
    size: largeData.length,
    generatedAt: new Date().toISOString(),
  };
});

Workers Overview

Learn about worker basics

Queue Events

Monitor job events globally

Job API

Job instance methods and properties

Retrying Failing Jobs

Handle job failures

Getting Started

Core Concepts

Queue Management

Workers

Job Types & Features

Job Schedulers

Flows

Advanced Features

Patterns & Best Practices

Redis Integration

Framework Integration

Production & Operations

Migration Guides

Returning Job Data

Basic Return Values

Accessing Return Values

From Worker Events

From Queue Events

From the Job Instance

Using getJob

Return Value Examples

Simple Values

Complex Objects

Arrays

Storing Results Reliably

Using a Results Queue

Microservice Pattern

Combining Return Values with Progress

TypeScript Type Safety

Best Practices

Handling Large Results

Workers Overview

Queue Events

Job API

Retrying Failing Jobs

API Reference

Build docs developers (and LLMs) love

Getting Started

Core Concepts

Queue Management

Workers

Job Types & Features

Job Schedulers

Flows

Advanced Features

Patterns & Best Practices

Redis Integration

Framework Integration

Production & Operations

Migration Guides

​Basic Return Values

​Accessing Return Values

​From Worker Events

​From Queue Events

​From the Job Instance

​Using getJob

​Return Value Examples

​Simple Values

​Complex Objects

​Arrays

​Storing Results Reliably

​Using a Results Queue

​Microservice Pattern

​Combining Return Values with Progress

​TypeScript Type Safety

​Best Practices

​Handling Large Results

​Related Topics

Workers Overview

Queue Events

Job API

Retrying Failing Jobs

​API Reference

Build docs developers (and LLMs) love

Basic Return Values

Accessing Return Values

From Worker Events

From Queue Events

From the Job Instance

Using getJob

Return Value Examples

Simple Values

Complex Objects

Arrays

Storing Results Reliably

Using a Results Queue

Microservice Pattern

Combining Return Values with Progress

TypeScript Type Safety

Best Practices

Handling Large Results

Related Topics

API Reference