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Node.js Backend Development Bootcamp · レッスン

Unary、Server、Client、双方向ストリーミングRPC

4種類のgRPC呼び出しを実装し、それぞれの通信に適したパターンを選択します。

「Unary、Server、Client、双方向ストリーミングRPC」はCoddyKit上の無料Node.js Backend Development Bootcampレッスンです。 これはレッスン2/4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。

Four Ways to Call an RPC

gRPC defines four kinds of method in your .proto file, and each one maps to a different streaming shape:

  • Unary — one request, one response (like a normal function call).
  • Server streaming — one request, a stream of responses.
  • Client streaming — a stream of requests, one response.
  • Bidirectional streaming — both sides stream independently.

The stream keyword in the service definition is what decides the shape. In this lesson you'll implement all four in Node.js with @grpc/grpc-js and learn when to reach for each.

syntax = "proto3";
package chat;

service ChatService {
  // unary
  rpc GetUser (UserRequest) returns (User);
  // server streaming
  rpc ListMessages (RoomRequest) returns (stream Message);
  // client streaming
  rpc UploadLogs (stream LogLine) returns (UploadSummary);
  // bidirectional streaming
  rpc Chat (stream Message) returns (stream Message);
}

Loading the Proto in Node.js

Before you implement any handler, you load the .proto definition at runtime with @grpc/proto-loader and turn it into a gRPC service object with @grpc/grpc-js.

The loaded packageDefinition mirrors your proto packages and services. You attach handlers to the service with server.addService() — the names you provide must match the rpc names exactly.

const grpc = require('@grpc/grpc-js');
const protoLoader = require('@grpc/proto-loader');

const pkgDef = protoLoader.loadSync('chat.proto', {
  keepCase: true,
  longs: String,
  enums: String,
  defaults: true,
  oneofs: true,
});

const proto = grpc.loadPackageDefinition(pkgDef).chat;
const server = new grpc.Server();

// handlers get attached here
server.addService(proto.ChatService.service, { /* ... */ });

Unary RPC — One In, One Out

A unary handler receives (call, callback). The request payload is on call.request, and you reply by invoking the Node-style callback(error, response).

  • Pass null as the first argument for success.
  • Pass a { code, details } error object to signal failure.

Unary is the right choice for classic request/response work: fetching a record, validating input, performing a single mutation.

function getUser(call, callback) {
  const { id } = call.request;
  if (!id) {
    return callback({
      code: grpc.status.INVALID_ARGUMENT,
      details: 'id is required',
    });
  }
  const user = { id, name: 'Ada Lovelace' };
  callback(null, user);
}

server.addService(proto.ChatService.service, { GetUser: getUser });

Server Streaming — One In, Many Out

A server-streaming handler receives only (call) — there is no callback. You push each response with call.write(message), then signal completion with call.end().

This pattern shines when the server produces a sequence the client can consume incrementally: paginated results, log tails, progress events, or large result sets you don't want to buffer in memory.

function listMessages(call) {
  const { roomId } = call.request;
  const messages = loadMessagesForRoom(roomId); // array

  for (const msg of messages) {
    call.write({ id: msg.id, text: msg.text });
  }
  call.end(); // closes the stream to the client
}

server.addService(proto.ChatService.service, {
  ListMessages: listMessages,
});

Backpressure in Server Streaming

call.write() returns a boolean. When it returns false, the internal buffer is full and you should wait for the 'drain' event before writing more. Ignoring this on large streams can balloon memory usage.

The robust pattern wraps writes in a promise that resolves on drain, so an async loop naturally pauses when the consumer is slow.

function writeAsync(call, msg) {
  return new Promise((resolve) => {
    if (call.write(msg)) resolve();
    else call.once('drain', resolve);
  });
}

async function streamBigResult(call) {
  for (let i = 0; i < 100000; i++) {
    await writeAsync(call, { id: i, text: 'row ' + i });
  }
  call.end();
}

Client Streaming — Many In, One Out

A client-streaming handler receives (call, callback). You listen for incoming items with call.on('data', ...), do final work on call.on('end', ...), and send the single response via the callback.

Use it when the client feeds many items but you only need one aggregate result: bulk uploads, batched metrics ingestion, or computing a summary/average over a stream.

function uploadLogs(call, callback) {
  let count = 0;
  let bytes = 0;

  call.on('data', (logLine) => {
    count += 1;
    bytes += Buffer.byteLength(logLine.text || '');
  });

  call.on('end', () => {
    callback(null, { received: count, totalBytes: bytes });
  });

  call.on('error', (err) => console.error('client stream error', err));
}

Bidirectional Streaming — Many In, Many Out

A bidirectional handler receives only (call) and treats it as a duplex stream: read incoming items with call.on('data', ...) and emit responses with call.write(...) at any time. Both directions are fully independent.

This is ideal for chat, multiplayer state sync, or live request/response negotiation where either side may speak first or out of lockstep.

function chat(call) {
  call.on('data', (msg) => {
    // echo every message back to the sender, augmented
    call.write({ id: msg.id, text: 'echo: ' + msg.text });
  });

  call.on('end', () => call.end());
  call.on('error', (err) => console.error('chat error', err));
}

server.addService(proto.ChatService.service, { Chat: chat });

Calling From a gRPC Client

The client API mirrors the server shapes. Unary returns via a callback; server streaming returns a readable stream you iterate with 'data'; client streaming gives you a writable stream you write() to and then end(); bidirectional gives you both at once.

The single rule: the stream keyword on each side of the proto determines whether you get a callback or a stream object.

const client = new proto.ChatService(
  'localhost:50051',
  grpc.credentials.createInsecure(),
);

// unary
client.GetUser({ id: '1' }, (err, user) => console.log(user));

// server streaming
const stream = client.ListMessages({ roomId: 'general' });
stream.on('data', (m) => console.log(m.text));
stream.on('end', () => console.log('done'));

Mental Model: Pick by Cardinality

Choosing the right RPC type is almost always a question of cardinality on each side:

  • One request, one response → unary.
  • One request, results arrive over time → server streaming.
  • Many inputs collapsed into one result → client streaming.
  • Continuous, independent two-way flow → bidirectional.

Don't reach for streaming just because data is large — pagination over unary calls is often simpler. Reach for streaming when the data is open-ended in time or genuinely incremental.

A Runnable Cardinality Picker

Here's a tiny, framework-free helper that encodes the decision rule above. It takes whether each side streams and returns the gRPC method type — useful as a sanity check when designing a service.

This is plain JavaScript with no gRPC dependency, so an online judge can run it directly.

function rpcType(clientStreams, serverStreams) {
  if (!clientStreams && !serverStreams) return 'unary';
  if (!clientStreams && serverStreams) return 'server-streaming';
  if (clientStreams && !serverStreams) return 'client-streaming';
  return 'bidirectional';
}

console.log(rpcType(false, false)); // unary
console.log(rpcType(false, true));  // server-streaming
console.log(rpcType(true, false));  // client-streaming
console.log(rpcType(true, true));   // bidirectional

Errors, Deadlines, and Cleanup

Across all four types, a few production habits matter:

  • Always attach call.on('error', ...) on streaming handlers — an unhandled stream error can crash the process.
  • Respect deadlines: check call.cancelled in long loops and stop writing if the client gave up.
  • For client/bidi streams, do final work in 'end', not after the first 'data'.
  • Send domain errors with grpc.status codes (e.g. NOT_FOUND, INVALID_ARGUMENT) rather than throwing raw exceptions.
function listMessages(call) {
  let i = 0;
  const timer = setInterval(() => {
    if (call.cancelled) { clearInterval(timer); return; }
    if (i >= 10) { clearInterval(timer); return call.end(); }
    call.write({ id: i, text: 'tick ' + i++ });
  }, 100);

  call.on('error', () => clearInterval(timer));
}

Quick Check

Test your understanding of choosing the right RPC type.

Recap

You now know all four gRPC call shapes and how to implement them in Node.js with @grpc/grpc-js:

  • Unary — (call, callback); read call.request, reply once.
  • Server streaming — (call); call.write() repeatedly, then call.end(), minding backpressure via 'drain'.
  • Client streaming — (call, callback); aggregate on 'data', respond once on 'end'.
  • Bidirectional — (call); read and write independently for live, two-way flows.

Choose by cardinality and whether the data is open-ended in time, always handle stream errors, and respect client deadlines with call.cancelled.

よくある質問

「Unary、Server、Client、双方向ストリーミングRPC」レッスンは無料ですか？

はい。「Unary、Server、Client、双方向ストリーミングRPC」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。

「Unary、Server、Client、双方向ストリーミングRPC」で何を学びますか？

4種類のgRPC呼び出しを実装し、それぞれの通信に適したパターンを選択します。 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2/4です。

「Unary、Server、Client、双方向ストリーミングRPC」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. Protobuf IDLによるサービスとメッセージの定義
  2. Unary、Server、Client、双方向ストリーミングRPC
  3. インターセプター、デッドライン、メタデータ
  4. Protoの進化と後方互換性
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