Worker pool pattern in Node.js - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the Worker Pool Pattern in Node.js?

It is a way to run multiple tasks in parallel by using a fixed number of worker threads. This helps to manage heavy or blocking tasks without freezing the main program.

beginner

Why use a Worker Pool instead of creating a new worker for each task?

Creating a new worker for every task is slow and uses more memory. A worker pool reuses a set number of workers, making the program faster and more efficient.

intermediate

How does the Worker Pool Pattern improve Node.js performance?

It offloads CPU-heavy tasks to worker threads, so the main thread stays free to handle other tasks like user requests, keeping the app responsive.

beginner

What Node.js module is commonly used to implement the Worker Pool Pattern?

The 'worker_threads' module is used to create and manage worker threads in Node.js for the worker pool pattern.

intermediate

Describe a simple flow of how tasks are handled in a Worker Pool.

Tasks are added to a queue. Available workers pick tasks from the queue, process them, then become free to pick new tasks. This cycle repeats to handle many tasks efficiently.

What is the main benefit of using a worker pool in Node.js?

A Run multiple tasks in parallel without blocking the main thread

B Make the code shorter

C Avoid using any threads

D Automatically fix bugs

Worker pools allow parallel task execution, keeping the main thread free and responsive.

Which Node.js module helps create worker threads for a worker pool?

A http

B worker_threads

C fs

D events

The 'worker_threads' module is designed for creating and managing worker threads.

What happens when all workers in a pool are busy and a new task arrives?

A The task waits in a queue until a worker is free

B A new worker is created automatically

C The task is ignored

D The main thread processes the task

Tasks wait in a queue until a worker becomes available to keep resource use controlled.

Why is creating a new worker for each task inefficient?

A Workers use no memory

B It is the recommended way

C It makes the program faster

D It slows down the program and uses more memory

Creating many workers wastes resources and slows down the system.

Which of these is NOT a part of the worker pool pattern?

A Task queue

B Fixed number of workers

C Main thread blocking on tasks

D Workers processing tasks

The main thread should stay free and not block on tasks in the worker pool pattern.

Explain how the worker pool pattern helps keep a Node.js application responsive.

Think about how tasks move from the main thread to workers.

Describe the steps to implement a simple worker pool using Node.js worker_threads.

Focus on worker creation, task management, and communication.

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