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Node.js Backend Development Bootcamp · レッスン

ワークキュー、プリフェッチ、競合コンシューマー

プリフェッチ上限と競合コンシューマーパターンを使い、コンシューマー間で負荷を公平に分散します。

「ワークキュー、プリフェッチ、競合コンシューマー」はCoddyKit上の無料Node.js Backend Development Bootcampレッスンです。 これはレッスン4/4です。 下記で完全なレッスンを無料で読むことができます。その後、ブラウザ内の組み込みコードエディタと24時間対応のAIチューターでハンズオン演習できます。 これはNode.js Backend Development Bootcamp学習パスの一部であり、ウェブとCoddyKitアプリ全体で進捗が同期されます。 Node.js Backend Development Bootcampコースには全4レッスンが含まれています。

このレッスンの一部はまだ翻訳されておらず、英語で表示されています。

Why Work Queues?

A work queue (sometimes called a task queue) lets your Node.js backend push time-consuming jobs to a queue instead of running them inside the HTTP request. Think image resizing, sending emails, or generating PDFs.

  • The producer publishes a small message describing the job.
  • One or more consumers (worker processes) pull jobs and execute them in the background.
  • The HTTP response returns immediately, keeping your API fast.

RabbitMQ stores the messages durably until a worker is free to process them.

A Minimal Producer

The producer connects to RabbitMQ, declares a durable queue, and sends a task message. Each message is just a buffer of bytes — here we send a plain string describing the job.

Notice { durable: true } on the queue and { persistent: true } on the message. Together they let tasks survive a broker restart.

const amqp = require('amqplib');

async function send(task) {
  const conn = await amqp.connect('amqp://localhost');
  const ch = await conn.createChannel();
  const queue = 'tasks';

  await ch.assertQueue(queue, { durable: true });
  ch.sendToQueue(queue, Buffer.from(task), { persistent: true });
  console.log('Sent: %s', task);

  await ch.close();
  await conn.close();
}

send('resize-image:42');

A Minimal Consumer

The consumer asserts the same durable queue and registers a callback with ch.consume. Whenever a message arrives, RabbitMQ delivers it to the handler.

Here we simulate work by counting the dots in the message body, then sleeping that many seconds. The queue name is the contract that links producer and consumer.

const amqp = require('amqplib');

async function worker() {
  const conn = await amqp.connect('amqp://localhost');
  const ch = await conn.createChannel();
  const queue = 'tasks';

  await ch.assertQueue(queue, { durable: true });
  console.log('Waiting for tasks...');

  ch.consume(queue, (msg) => {
    const body = msg.content.toString();
    console.log('Received: %s', body);
  });
}

worker();

Acknowledgements Prevent Lost Work

By default, manual acknowledgements protect you from losing jobs if a worker crashes. With { noAck: false }, RabbitMQ keeps a message in an unacknowledged state until the worker calls ch.ack(msg).

  • If the worker dies before acking, RabbitMQ requeues the message and another worker picks it up.
  • Always ack after the work succeeds, never before.
  • Use ch.nack(msg, false, requeue) to reject a poisoned message.
ch.consume(queue, async (msg) => {
  try {
    await doWork(msg.content.toString());
    ch.ack(msg);            // success: remove from queue
  } catch (err) {
    ch.nack(msg, false, false); // failure: drop (or send to DLX)
  }
}, { noAck: false });

Competing Consumers Pattern

The competing consumers pattern simply means: run multiple worker processes that all consume from the same queue. RabbitMQ delivers each message to exactly one of them.

  • Want more throughput? Start more workers — no code change needed.
  • The queue acts as a load buffer during traffic spikes.
  • This is how you scale background processing horizontally in Node.js.

But how RabbitMQ chooses which worker gets the next message matters a lot.

The Problem: Round-Robin Dispatch

Out of the box, RabbitMQ dispatches messages to consumers in a strict round-robin order — it counts messages, not workload.

Imagine two workers. The queue has tasks where odd-numbered ones are heavy and even-numbered ones are light. Round-robin sends every other task to each worker, so one worker may end up with all the heavy jobs while the other sits idle.

RabbitMQ does not look at how busy a consumer already is — unless you tell it to with prefetch.

Prefetch: Limit Unacked Messages

Prefetch (QoS) caps how many unacknowledged messages a single consumer may hold at once. You set it per channel with ch.prefetch(count).

  • ch.prefetch(1) means: don't give a worker a new task until it has acked the previous one.
  • This turns dispatch from "round-robin by count" into "give the next task to whoever is free" — fair dispatch.
  • Higher values (e.g. 10) increase throughput by pipelining, at the cost of fairness.
const amqp = require('amqplib');

async function worker() {
  const conn = await amqp.connect('amqp://localhost');
  const ch = await conn.createChannel();
  const queue = 'tasks';

  await ch.assertQueue(queue, { durable: true });
  await ch.prefetch(1); // fair dispatch: one in-flight task per worker

  ch.consume(queue, async (msg) => {
    await doWork(msg.content.toString());
    ch.ack(msg);
  }, { noAck: false });
}

worker();

Tuning the Prefetch Value

The right prefetch depends on your workload:

  • prefetch(1) — best for long, uneven, CPU-heavy tasks. Maximum fairness, slight latency between ack and next delivery.
  • prefetch(10–50) — best for short, uniform tasks (e.g. tiny webhook fan-out) where round-trip latency would otherwise dominate.

Rule of thumb: short tasks + low latency network → larger prefetch. Long tasks or unpredictable durations → small prefetch. Measure, then tune.

Simulating Fair Dispatch Locally

You don't need RabbitMQ to understand fair dispatch. This standalone program models a single shared queue and two workers under a prefetch=1 policy: each worker only takes a new job when it is free.

Heavy jobs take longer, so the free worker keeps grabbing the next task — the load self-balances instead of being split blindly by count.

const tasks = [5, 1, 5, 1, 5, 1]; // seconds of "work"
let clock = 0;
const workers = [
  { name: 'W1', freeAt: 0 },
  { name: 'W2', freeAt: 0 },
];

for (const cost of tasks) {
  // prefetch=1: assign to whichever worker is free soonest
  const w = workers.reduce((a, b) => (a.freeAt <= b.freeAt ? a : b));
  const start = Math.max(clock, w.freeAt);
  w.freeAt = start + cost;
  console.log(`${w.name} runs ${cost}s at t=${start}`);
}

const finish = Math.max(...workers.map((w) => w.freeAt));
console.log('All done at t=' + finish);

Prefetch Is Per-Channel, Per-Consumer

A common gotcha: ch.prefetch(count) applies to each consumer on that channel by default. If you run one worker process per queue, this is exactly what you want.

  • The limit counts only unacked messages, so forgetting to ack will stall the worker once it hits the cap.
  • A second optional argument, ch.prefetch(count, true), makes the limit apply across the whole channel (global), which is rarely needed.
  • One channel per worker process is the simplest, safest setup.

Putting It Together

A production-ready consumer combines all the pieces: a durable queue, fair-dispatch prefetch, manual acks on success, and nack on failure.

Run several copies of this exact file as separate processes and you have competing consumers that share load fairly. Scale up by launching more workers; scale down by stopping some — the queue absorbs the difference.

const amqp = require('amqplib');

async function start() {
  const conn = await amqp.connect('amqp://localhost');
  const ch = await conn.createChannel();
  const queue = 'tasks';

  await ch.assertQueue(queue, { durable: true });
  await ch.prefetch(1);

  ch.consume(queue, async (msg) => {
    try {
      await handle(JSON.parse(msg.content.toString()));
      ch.ack(msg);
    } catch (err) {
      ch.nack(msg, false, false); // drop / route to dead-letter exchange
    }
  }, { noAck: false });
}

start().catch(console.error);

Quick Check

You run 3 worker processes consuming the same queue. Task durations vary wildly — some take 200ms, some take 30s. You notice one worker is always busy while others go idle, so jobs pile up. What is the most direct fix?

Recap

You learned how to distribute background work fairly across Node.js workers with RabbitMQ:

  • Work queues offload slow jobs from the request path into a durable queue.
  • Competing consumers means multiple workers consume the same queue; each message goes to exactly one worker, and you scale by adding processes.
  • Default dispatch is round-robin by count, which can overload one worker with heavy tasks.
  • Prefetch (ch.prefetch(n)) caps unacked messages per consumer; prefetch(1) gives fair dispatch, higher values pipeline short tasks.
  • Always use manual acks (ch.ack on success, ch.nack on failure) so crashed workers don't lose jobs.

よくある質問

「ワークキュー、プリフェッチ、競合コンシューマー」レッスンは無料ですか？

はい。「ワークキュー、プリフェッチ、競合コンシューマー」の完全なテキストはこのウェブで無料で読めます。インタラクティブに演習し（組み込みコードエディタと24時間対応のAIチューター）、Node.js Backend Development Bootcampコースの残りをアンロックするには、CoddyKit PROにアップグレードしてください。 Node.js Backend Development Bootcampコースには全4レッスンが含まれています。

「ワークキュー、プリフェッチ、競合コンシューマー」で何を学びますか？

プリフェッチ上限と競合コンシューマーパターンを使い、コンシューマー間で負荷を公平に分散します。 ブラウザで直接実行するハンズオンコードでNode.js Backend Development Bootcampを演習し、24時間対応のAIチューターがレッスンを進める中での質問に答えます。

Node.js Backend Development Bootcampを始めるのに経験は必要ですか？

事前経験は必要ありません。CoddyKitのNode.js Backend Development Bootcampは初級者から上級者向けに構成されているため、ここから始めるか最初から始めて、自分のペースで進むことができます。 これはレッスン4/4です。

「ワークキュー、プリフェッチ、競合コンシューマー」レッスンにはどのくらい時間がかかりますか？

ほとんどのCoddyKitレッスンは約5～10分かかります。各レッスンはコンパクトでインタラクティブなので、着実に進歩し、ウェブとアプリ全体で正確に前回の場所から再開できます。

このNode.js Backend Development Bootcampレッスンでコードを書いて実行できますか？

はい。すべてのNode.js Backend Development Bootcampレッスンに組み込みコードエディタが含まれているため、ブラウザでリアルコードを書いて実行し、即座のAIフィードバックを取得できます。ローカル設定は不要です。

このコースのすべてのレッスン

  1. プロデューサー、コンシューマー、AMQPモデル
  2. エクスチェンジの種類：Direct、Topic、Fanout、Headers
  3. Acknowledgement、デッドレターキュー、リトライ
  4. ワークキュー、プリフェッチ、競合コンシューマー
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