Worker pool pattern in Node.js - Mini Project: Build & Apply

Worker Pool Pattern in Node.js

📖 Scenario: You are building a Node.js application that needs to process multiple CPU-intensive tasks efficiently. To avoid blocking the main thread, you will use the worker pool pattern to distribute tasks across multiple worker threads.

🎯 Goal: Create a worker pool that manages a fixed number of worker threads. The pool will accept tasks and assign them to available workers, ensuring tasks run concurrently without blocking the main thread.

📋 What You'll Learn

Create a list of tasks to process

Set a maximum number of worker threads in the pool

Implement logic to assign tasks to workers using the worker pool pattern

Complete the worker pool setup to handle task execution and results

💡 Why This Matters

🌍 Real World

Worker pools help Node.js applications perform CPU-heavy tasks without blocking the main event loop, improving responsiveness and throughput.

💼 Career

Understanding worker pools is important for backend developers building scalable and efficient Node.js services that handle parallel processing.

1

Create the list of tasks

Create a constant array called tasks with these exact numbers: 100000000, 200000000, 300000000, 400000000, 500000000.

Node.js

# Create the tasks array with the specified numbers
# Your code here

Hint

Use const tasks = [100000000, 200000000, 300000000, 400000000, 500000000]; to create the array.

2

Set the maximum number of workers

Create a constant called maxWorkers and set it to 2 to limit the number of worker threads in the pool.

Node.js

const tasks = [100000000, 200000000, 300000000, 400000000, 500000000];
# Define maxWorkers to 2
# Your code here

Hint

Use const maxWorkers = 2; to set the worker limit.

3

Implement the worker pool logic

Import Worker from 'worker_threads'. Create a function called runTask that takes a number task and returns a Promise. Inside, create a new Worker using new Worker('./worker.js', { workerData: task }). Resolve the Promise when the worker sends a message, and reject if the worker emits an error.

Node.js

const tasks = [100000000, 200000000, 300000000, 400000000, 500000000];
const maxWorkers = 2;

// Import Worker and create runTask function
# Your code here

Hint

Use require('worker_threads') to import Worker. Wrap the worker creation in a Promise and handle message and error events.

4

Complete the worker pool to process all tasks

Create an async function called runWorkerPool. Inside, create an empty array results. Use a while loop to process tasks while tasks.length > 0. In each loop, create an array promises by slicing tasks to get up to maxWorkers tasks, then map each to runTask. Use await Promise.all(promises) to get results and push them into results. Remove processed tasks from tasks. Finally, return results. Then call runWorkerPool().

Node.js

const { Worker } = require('worker_threads');
const tasks = [100000000, 200000000, 300000000, 400000000, 500000000];
const maxWorkers = 2;

function runTask(task) {
    return new Promise((resolve, reject) => {
        const worker = new Worker('./worker.js', { workerData: task });
        worker.on('message', resolve);
        worker.on('error', reject);
        worker.on('exit', (code) => {
            if (code !== 0) reject(new Error(`Worker stopped with exit code ${code}`));
        });
    });
}

// Create runWorkerPool async function to process all tasks
# Your code here

Hint

Use a while loop to process tasks in batches of maxWorkers. Use Promise.all to wait for all workers in the batch to finish.

Practice

1. What is the main purpose of using the worker pool pattern in Node.js?

easy

A. To increase the memory usage by creating many workers

B. To avoid using any background threads or workers

C. To slow down the program by running tasks one after another

D. To run multiple tasks concurrently using a fixed number of workers

Solution

1. Step 1: Understand the worker pool pattern concept

   The worker pool pattern uses a limited number of workers to handle many tasks efficiently without creating too many threads.

2. Step 2: Identify the main goal in Node.js context

   It allows running tasks concurrently but limits the number of workers to keep resource use balanced and improve speed.

3. Final Answer:

   To run multiple tasks concurrently using a fixed number of workers -> Option D

4. Quick Check:

   Worker pool = fixed workers + concurrent tasks [OK]

Hint: Worker pool means fixed workers handle many tasks concurrently [OK]

Common Mistakes:

• Thinking worker pool creates unlimited workers
• Believing it slows down the program
• Confusing it with single-threaded execution

2. Which of the following is the correct way to create a worker pool using Node.js worker_threads module?

easy

A. const { Worker } = require('worker_threads'); const pool = new WorkerPool(4);

B. const pool = new WorkerPool(4); const { Worker } = require('worker_threads');

C. const { Worker } = require('worker_threads'); const pool = WorkerPool(4);

D. const pool = new Worker('worker.js', 4);

Solution

1. Step 1: Import Worker correctly from worker_threads

   The correct import is: const { Worker } = require('worker_threads');

2. Step 2: Create a worker pool instance properly

   Assuming a WorkerPool class exists, it should be instantiated with new WorkerPool(4); to create 4 workers.

3. Final Answer:

   const { Worker } = require('worker_threads'); const pool = new WorkerPool(4); -> Option A

4. Quick Check:

   Correct import + new instance = const { Worker } = require('worker_threads'); const pool = new WorkerPool(4); [OK]

Hint: Import Worker first, then create pool with new keyword [OK]

Common Mistakes:

• Calling WorkerPool without new keyword
• Wrong order of import and instantiation
• Using Worker constructor incorrectly

3. Given this simplified worker pool code snippet, what will be logged to the console?

const { Worker } = require('worker_threads');

class WorkerPool {
  constructor(size) {
    this.workers = Array(size).fill(null).map(() => new Worker('./worker.js'));
  }
  runTask(task) {
    return new Promise((resolve) => {
      const worker = this.workers.pop();
      worker.once('message', (result) => {
        this.workers.push(worker);
        resolve(result);
      });
      worker.postMessage(task);
    });
  }
}

const pool = new WorkerPool(2);
pool.runTask('task1').then(console.log);
pool.runTask('task2').then(console.log);

medium

A. Runs tasks sequentially, logs task1 then task2

B. Outputs results of task1 and task2 as they complete, order not guaranteed

C. Only task1 result is logged, task2 is ignored

D. Throws an error because workers array is empty after first pop

Solution

1. Step 1: Understand worker allocation and reuse

   The pool starts with 2 workers. Each runTask pops a worker, uses it, then pushes it back after message received.

2. Step 2: Analyze concurrency and output order

   Both tasks run concurrently on separate workers. Results log as tasks complete, order may vary.

3. Final Answer:

   Outputs results of task1 and task2 as they complete, order not guaranteed -> Option B

4. Quick Check:

   Workers reused, tasks run concurrently [OK]

Hint: Workers pop and push back, tasks run in parallel [OK]

Common Mistakes:

• Assuming workers array empties causing error
• Thinking tasks run one after another
• Believing only first task logs

4. Identify the bug in this worker pool code snippet and choose the correct fix:

class WorkerPool {
  constructor(size) {
    this.workers = [];
    for (let i = 0; i < size; i++) {
      this.workers.push(new Worker('./worker.js'));
    }
  }

  runTask(task) {
    if (this.workers.length === 0) {
      throw new Error('No workers available');
    }
    const worker = this.workers.pop();
    worker.once('message', (result) => {
      resolve(result);
      this.workers.push(worker);
    });
    worker.postMessage(task);
  }
}

medium

A. Replace pop() with shift() to get workers in order

B. Remove the check for empty workers array

C. Add a Promise wrapper around runTask and return it

D. Call worker.terminate() after task completes

Solution

1. Step 1: Check runTask return and resolve usage

   runTask uses resolve inside callback but does not return a Promise or define resolve, causing error.

2. Step 2: Fix by wrapping runTask in a Promise and returning it

   Wrap the logic inside return new Promise((resolve) => { ... }) so resolve is defined and caller can await result.

3. Final Answer:

   Add a Promise wrapper around runTask and return it -> Option C

4. Quick Check:

   runTask must return Promise with resolve [OK]

Hint: runTask uses resolve but lacks Promise wrapper [OK]

Common Mistakes:

• Ignoring missing Promise causes runtime error
• Removing worker availability check breaks logic
• Terminating worker too early stops reuse

5. You want to process 10 CPU-heavy tasks using a worker pool of size 3. Which approach best ensures all tasks run efficiently without overloading the system?

hard

A. Create 3 workers, queue tasks, assign next task when a worker finishes

B. Create 10 workers, one per task, and run all at once

C. Run all tasks in the main thread sequentially without workers

D. Create 3 workers but assign all tasks to the first worker only

Solution

1. Step 1: Understand resource limits and worker pool size

   Creating too many workers (10) can overload CPU and memory. Using 3 workers limits resource use.

2. Step 2: Use a task queue to assign tasks as workers become free

   Queue tasks and assign next task to a worker when it finishes ensures all tasks run efficiently without overload.

3. Final Answer:

   Create 3 workers, queue tasks, assign next task when a worker finishes -> Option A

4. Quick Check:

   Fixed workers + queued tasks = efficient processing [OK]

Hint: Use fixed workers and queue tasks for efficiency [OK]

Common Mistakes:

• Creating too many workers causing overload
• Running tasks sequentially wasting concurrency
• Assigning all tasks to one worker blocking others