Forking workers per CPU core in Node.js - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the purpose of forking workers per CPU core in Node.js?

Forking workers per CPU core allows Node.js to create multiple child processes, each running on a separate CPU core. This helps to utilize all CPU cores efficiently and improves the performance of CPU-bound tasks.

beginner

Which Node.js module is commonly used to fork workers for each CPU core?

The 'cluster' module is used to fork workers in Node.js. It helps create child processes that share the same server port, enabling load balancing across CPU cores.

beginner

How do you determine the number of CPU cores available in a Node.js application?

You can use the 'os' module's 'cpus()' method, which returns an array of CPU core info. The length of this array indicates the number of CPU cores available.

intermediate

What happens if a worker process crashes in a cluster setup?

If a worker crashes, the master process can listen for the 'exit' event and fork a new worker to replace it. This ensures the application remains available and resilient.

intermediate

Why should you avoid sharing state directly between worker processes?

Each worker runs in its own process with separate memory. Sharing state directly is not possible and can cause bugs. Instead, use inter-process communication or external stores like databases.

Which Node.js module helps you create worker processes for each CPU core?

A cluster

B http

C fs

D events

The 'cluster' module is designed to fork worker processes to utilize multiple CPU cores.

How do you find the number of CPU cores in Node.js?

A os.cpus().length

B os.cpuCount()

C process.cpuCount

D os.cores()

The 'os.cpus()' method returns an array of CPU cores, so its length gives the number of cores.

What is the role of the master process in a cluster?

A Handles all HTTP requests alone

B Runs the database

C Forks worker processes and manages them

D Manages file system operations

The master process forks and manages worker processes in a cluster setup.

If a worker process crashes, what should the master process do?

A Log the error and stop all workers

B Restart the entire server

C Do nothing

D Fork a new worker to replace it

The master process should fork a new worker to keep the application running smoothly.

Why can't worker processes share memory directly?

A Because Node.js forbids it

B Because they run in separate processes

C Because of network restrictions

D Because of file system locks

Worker processes run in separate memory spaces, so direct memory sharing is not possible.

Explain how to use the cluster module to fork workers per CPU core in Node.js.

Think about how the master process manages workers and uses CPU info.

Describe why forking workers per CPU core improves Node.js application performance.

Consider how multiple CPU cores can be used to do more work at the same time.

Practice

1. What is the main reason to fork workers equal to the number of CPU cores in a Node.js app?

easy

A. To make the app run slower for debugging purposes

B. To use all CPU cores and improve performance by running tasks in parallel

C. To reduce memory usage by limiting the number of processes

D. To avoid using the cluster module

Solution

1. Step 1: Understand CPU cores and parallelism

   Each CPU core can run one process at a time, so using all cores means better performance.

2. Step 2: Role of forking workers

   Forking workers equal to CPU cores lets Node.js run multiple tasks simultaneously, improving speed.

3. Final Answer:

   To use all CPU cores and improve performance by running tasks in parallel -> Option B

4. Quick Check:

   Fork workers = use all cores = better performance [OK]

Hint: More workers = more CPU cores used = faster app [OK]

Common Mistakes:

• Thinking forking reduces memory usage
• Believing forking slows the app
• Confusing cluster module usage

2. Which of the following is the correct way to get the number of CPU cores in Node.js for forking workers?

easy

A. const cores = require('os').cpus().length;

B. const cores = require('cluster').cpuCount;

C. const cores = require('os').cpuCount();

D. const cores = require('os').cpus.length;

Solution

1. Step 1: Check Node.js os module usage

   The os module has a method cpus() that returns an array of CPU core info.

2. Step 2: Correct syntax to get core count

   Using cpus().length gives the number of CPU cores available.

3. Final Answer:

   const cores = require('os').cpus().length; -> Option A

4. Quick Check:

   os.cpus() returns array, length gives core count [OK]

Hint: Use os.cpus().length to count CPU cores [OK]

Common Mistakes:

• Forgetting parentheses after cpus
• Using non-existent cpuCount method
• Trying to get cores from cluster module

3. Given this code snippet, what will be logged when run on a machine with 4 CPU cores?

const cluster = require('cluster');
const os = require('os');

if (cluster.isPrimary) {
  const numCPUs = os.cpus().length;
  console.log(`Primary process is running`);
  for (let i = 0; i < numCPUs; i++) {
    cluster.fork();
  }
} else {
  console.log(`Worker ${process.pid} started`);
}

medium

A. Primary process is running
Worker 1234 started
Worker 1235 started
Worker 1236 started
Worker 1237 started

B. Primary process is running
Worker started
Worker started
Worker started
Worker started

C. Primary process is running
Worker 1234 started

D. SyntaxError due to missing cluster setup

Solution

1. Step 1: Identify primary and worker behavior

   The primary logs once and forks 4 workers (one per CPU core).

2. Step 2: Each worker logs its own process id

   Each worker logs "Worker [pid] started" with its unique process id.

3. Final Answer:

   Primary process is running Worker 1234 started Worker 1235 started Worker 1236 started Worker 1237 started -> Option A

4. Quick Check:

   Primary logs once, 4 workers log with pids [OK]

Hint: Primary logs once; each worker logs with unique pid [OK]

Common Mistakes:

• Assuming workers log without pid
• Thinking only one worker starts
• Confusing primary and worker logs

4. What is wrong with this code snippet that tries to fork workers per CPU core?

const cluster = require('cluster');
const os = require('os');

if (cluster.isPrimary) {
  const numCPUs = os.cpus.length;
  for (let i = 0; i < numCPUs; i++) {
    cluster.fork();
  }
} else {
  console.log('Worker started');
}

medium

A. cluster.fork() is not a function

B. No error; code works fine

C. Missing else block for worker process

D. os.cpus.length is undefined; should be os.cpus().length

Solution

1. Step 1: Check os module usage

   os.cpus is a function, so os.cpus.length is undefined and causes error.

2. Step 2: Correct usage

   Use os.cpus().length to get the number of CPU cores correctly.

3. Final Answer:

   os.cpus.length is undefined; should be os.cpus().length -> Option D

4. Quick Check:

   os.cpus() is function, need parentheses [OK]

Hint: Remember os.cpus() is a function, not a property [OK]

Common Mistakes:

• Forgetting parentheses on os.cpus()
• Assuming cluster.fork() is missing
• Thinking else block is required for syntax

5. You want to create a Node.js server that forks one worker per CPU core and restarts any worker if it crashes. Which code snippet correctly implements this behavior?

hard

A. const cluster = require('cluster');
const http = require('http');
const os = require('os');

if (cluster.isPrimary) {
const numCPUs = os.cpus().length;
for (let i = 0; i < numCPUs; i++) {
cluster.fork();
}
} else {
http.createServer((req, res) => {
res.writeHead(200);
res.end('Hello from worker ' + process.pid);
}).listen(8000);
cluster.on('exit', (worker) => {
console.log(`Worker ${worker.process.pid} died`);
});
}

B. const cluster = require('cluster');
const http = require('http');
const os = require('os');

if (cluster.isWorker) {
const numCPUs = os.cpus().length;
for (let i = 0; i < numCPUs; i++) {
cluster.fork();
}
} else {
http.createServer((req, res) => {
res.writeHead(200);
res.end('Hello from worker ' + process.pid);
}).listen(8000);
}

C. const cluster = require('cluster');
const http = require('http');
const os = require('os');

if (cluster.isPrimary) {
const numCPUs = os.cpus().length;
for (let i = 0; i < numCPUs; i++) {
cluster.fork();
}
cluster.on('exit', (worker) => {
console.log(`Worker ${worker.process.pid} died, restarting...`);
cluster.fork();
});
} else {
http.createServer((req, res) => {
res.writeHead(200);
res.end('Hello from worker ' + process.pid);
}).listen(8000);
}

D. const cluster = require('cluster');
const http = require('http');
const os = require('os');

if (cluster.isPrimary) {
cluster.fork();
} else {
http.createServer((req, res) => {
res.writeHead(200);
res.end('Hello from worker ' + process.pid);
}).listen(8000);
}

Solution

1. Step 1: Fork one worker per CPU core in primary process

   In if (cluster.isPrimary), use const numCPUs = os.cpus().length; for (let i = 0; i < numCPUs; i++) cluster.fork();

2. Step 2: Restart workers on exit event

   In primary process, cluster.on('exit', (worker) => { console.log(`Worker ${worker.process.pid} died, restarting...`); cluster.fork(); });

3. Step 3: Worker creates HTTP server

   Workers create the HTTP server listening on port 8000, responding with their pid.

4. Final Answer:

   forks one worker per CPU core and restarts any worker if it crashes -> Option C

5. Quick Check:

   Primary forks os.cpus().length + cluster.on('exit', fork()) + workers create HTTP server [OK]

Hint: Use cluster.on('exit') in primary to restart workers [OK]

Common Mistakes:

• Using cluster.isWorker instead of cluster.isPrimary
• Not restarting workers on exit
• Forking workers inside worker process