Node.js साक्षात्कार प्रश्न 2026: इवेंट लूप, स्ट्रीम और स्केलिंग

Node.js Event Loop Phases (in order):
1. timers       — setTimeout, setInterval callbacks
2. pending I/O  — I/O errors from previous iteration
3. idle/prepare — internal use
4. poll         — retrieve new I/O events (MAIN PHASE)
5. check        — setImmediate callbacks
6. close        — close event callbacks (socket.destroy, etc.)

Microtask queue (runs BETWEEN each phase):
  - process.nextTick() — higher priority than Promises
  - Promise callbacks (.then/.catch)

Order of execution:
  1. Synchronous code
  2. process.nextTick() queue
  3. Promise callbacks
  4. setImmediate (check phase)
  5. setTimeout (timers phase, even setTimeout(fn, 0))

// Demonstrate event loop order
console.log('1 - sync');

setTimeout(() => console.log('2 - setTimeout'), 0);

setImmediate(() => console.log('3 - setImmediate'));

Promise.resolve().then(() => console.log('4 - Promise'));

process.nextTick(() => console.log('5 - nextTick'));

console.log('6 - sync');

// Output: 1, 6, 5, 4, 3, 2
// sync → nextTick → Promise → setImmediate → setTimeout

const fs = require('fs');
const zlib = require('zlib');
const { pipeline } = require('stream/promises');

// Streams: process data piece by piece, not all at once
// Memory efficient for large files

// Four types:
// Readable: fs.createReadStream, http.IncomingMessage
// Writable: fs.createWriteStream, http.ServerResponse
// Duplex:   net.Socket (both read and write)
// Transform: zlib.gzip (modifies data as it passes through)

// Good: streams don't load entire file into memory
async function compressFile(input, output) {
  await pipeline(
    fs.createReadStream(input),
    zlib.createGzip(),
    fs.createWriteStream(output)
  );
}

// BAD: loads entire file into memory
// const data = fs.readFileSync('huge-file.csv');  // could be 10GB!

// Streams for HTTP
const http = require('http');
http.createServer((req, res) => {
  const stream = fs.createReadStream('large-file.mp4');
  stream.pipe(res);  // efficient streaming to browser
}).listen(3000);

// 1. async/await with try/catch (most common in 2026)
async function getUser(id) {
  try {
    const user = await db.findUser(id);
    if (!user) throw new Error('User not found');
    return user;
  } catch (error) {
    logger.error({ error, id }, 'Failed to get user');
    throw error; // re-throw or return error response
  }
}

// 2. Express error handling middleware
app.get('/users/:id', async (req, res, next) => {
  try {
    const user = await getUser(req.params.id);
    res.json(user);
  } catch (error) {
    next(error); // pass to error handler
  }
});

app.use((error, req, res, next) => {
  logger.error(error);
  res.status(error.status || 500).json({ error: error.message });
});

// 3. Uncaught exceptions (last resort)
process.on('uncaughtException', (error) => {
  logger.error('Uncaught exception:', error);
  process.exit(1); // restart via PM2/supervisor
});

process.on('unhandledRejection', (reason, promise) => {
  logger.error('Unhandled rejection:', reason);
  // In Node.js 16+, this terminates the process
});

const { Worker, isMainThread, parentPort, workerData } = require('worker_threads');

// Main thread
if (isMainThread) {
  // CPU-intensive work → offload to worker thread
  const worker = new Worker(__filename, {
    workerData: { data: largeDataArray }
  });

  worker.on('message', (result) => {
    console.log('Result:', result);
  });

  worker.on('error', (error) => {
    console.error('Worker error:', error);
  });
} else {
  // Worker thread
  const { data } = workerData;
  const result = expensiveComputation(data);  // doesn't block main thread!
  parentPort.postMessage(result);
}

// Use worker threads for:
// - CPU-intensive computation (image processing, crypto, compression)
// - Parallel data processing
// NOT needed for I/O operations (event loop handles those efficiently)

// 1. Cluster module (use all CPU cores)
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();
  }
  cluster.on('exit', (worker) => {
    console.log(`Worker ${worker.id} died. Restarting...`);
    cluster.fork(); // auto-restart
  });
} else {
  require('./server'); // each worker runs the server
}

// 2. PM2 (recommended for production)
// pm2 start app.js -i max  # cluster mode, max workers
// pm2 start app.js -i 4    # 4 workers
// pm2 monit                # monitoring

// 3. Horizontal scaling
// Run multiple Node.js instances
// Load balance with nginx or AWS ALB