MongoDB Academy · Pelajaran

Proyeksi Inklusi vs Eksklusi

Pilih atau sembunyikan bidang tertentu dalam hasil kueri dan pahami alasan inklusi serta eksklusi tidak dapat dicampur dalam satu proyeksi.

Proyeksi Inklusi vs Eksklusi adalah pelajaran MongoDB Academy gratis di CoddyKit. Ini adalah pelajaran 1 dari 4. Kamu bisa membaca pelajaran lengkapnya di bawah secara gratis — lalu praktikkan langsung di browser dengan editor kode bawaan dan tutor AI 24/7. Ini adalah bagian dari jalur belajar MongoDB Academy, dan progresmu tersinkronisasi di web dan aplikasi CoddyKit. Kursus MongoDB Academy mencakup 4 pelajaran total.

Bagian dari pelajaran ini belum diterjemahkan dan ditampilkan dalam bahasa Inggris.

What Is a Projection?

A projection is the second argument to find() or findOne() that tells MongoDB which fields to include or exclude from the result. Instead of returning the entire document, you specify exactly the fields you need. This reduces bandwidth, decreases memory usage in your application, and keeps API responses lean. Projections are one of the simplest and most impactful query optimisations available.

Inclusion Mode: Specify What to Return

In inclusion mode, you list the fields you want to receive and set their value to 1. MongoDB returns only those fields plus _id (which is included by default). This is the most common form of projection because it explicitly declares the fields your query depends on, making the intent clear to anyone reading the code.

// Return only name and email — everything else is excluded
const user = await db.collection('users').findOne(
  { email: 'alice@example.com' },
  { projection: { name: 1, email: 1 } }
);
// Result: { _id: ObjectId('...'), name: 'Alice', email: 'alice@example.com' }

Excluding _id From Results

The _id field is always included in inclusion projections unless you explicitly exclude it. Set _id: 0 alongside inclusion fields to suppress it. This is useful when building API responses that use a different identifier field, or when you want to avoid leaking internal MongoDB IDs to clients.

// Include name and email but suppress _id
const user = await db.collection('users').findOne(
  { email: 'alice@example.com' },
  { projection: { _id: 0, name: 1, email: 1 } }
);
// Result: { name: 'Alice', email: 'alice@example.com' }
// _id is not present

Exclusion Mode: Specify What to Omit

In exclusion mode, you set fields to 0 to remove them from the result. Every other field is returned. This is useful when you want almost all fields but need to suppress a few sensitive or large ones—for example, hiding a passwordHash field from query results in a general-purpose user query.

// Return all user fields EXCEPT passwordHash and internalNotes
const user = await db.collection('users').findOne(
  { email: 'alice@example.com' },
  { projection: { passwordHash: 0, internalNotes: 0 } }
);
// Result: everything except passwordHash and internalNotes

Cannot Mix Inclusion and Exclusion

MongoDB does not allow mixing inclusion (1) and exclusion (0) fields in a single projection, except for the _id field. Attempting to do so results in a Projection cannot have a mix of inclusion and exclusion fields error. Choose one mode per query. The only legal combination is inclusion fields (1) with _id: 0.

// VALID: inclusion mode with _id suppressed
{ projection: { name: 1, email: 1, _id: 0 } }

// VALID: exclusion mode
{ projection: { passwordHash: 0, secret: 0 } }

// INVALID: mixing 1 and 0 (throws an error)
// { projection: { name: 1, passwordHash: 0 } }  <- ERROR

Projections in find() vs Aggregation

In find(), projection is the second argument. In the aggregation pipeline, you use the $project stage, which supports the same inclusion/exclusion syntax plus computed fields and expressions. Both behave the same way with respect to the cannot-mix rule, but $project is more powerful because it can rename fields and add calculated values.

// find() projection
db.users.find({}, { name: 1, email: 1, _id: 0 });

// Equivalent in aggregation with $project
db.users.aggregate([
  { $project: { name: 1, email: 1, _id: 0 } }
]);

Projections and Covered Queries

A covered query is a query where both the filter fields and the projection fields are entirely within a single index. MongoDB can answer a covered query from the index alone without reading the actual document from disk. Projections are essential for covered queries: if you project a field not in the index, MongoDB must fetch the document, breaking the coverage benefit.

// Index on { email: 1, name: 1 }
db.users.createIndex({ email: 1, name: 1 });

// Covered query — filter + projection both satisfied by the index
db.users.find(
  { email: 'alice@example.com' },
  { name: 1, email: 1, _id: 0 }  // _id must be excluded for full coverage
).explain('executionStats');
// Look for 'totalDocsExamined: 0' in the output

Projections With Mongoose

In Mongoose, you can pass a projection string or object to .select(). A space-separated string with + for inclusion and - for exclusion is common. Fields marked with select: false in the schema (like passwordHash) are excluded from results by default and must be explicitly included with +passwordHash.

// Mongoose: string projection (+ include, - exclude)
const users = await User.find({}).select('name email -_id');

// Object projection
const user = await User.findOne({ email: 'a@b.com' }).select({ name: 1, email: 1, _id: 0 });

// Schema-level default exclusion
const userSchema = new mongoose.Schema({
  email: String,
  passwordHash: { type: String, select: false }  // excluded by default
});

Projection Performance Benefits

Projections improve performance in three ways: (1) they reduce the amount of data read from disk when the projection aligns with an index; (2) they reduce network bandwidth between the MongoDB server and your application; (3) they reduce the amount of memory your application must allocate to hold query results. For large documents or high-throughput APIs, projections can reduce response size by 80% or more.

Projecting Computed Values in Aggregation

The $project stage in aggregation goes beyond simple inclusion/exclusion. You can compute new fields using expressions—for example, concatenating strings, performing arithmetic, or extracting parts of a date. This lets you transform the shape of documents server-side before sending results to the application, reducing client-side processing.

db.orders.aggregate([
  {
    $project: {
      orderId: '$_id',
      _id: 0,
      totalWithTax: { $multiply: ['$subtotal', 1.1] },  // computed field
      year: { $year: '$createdAt' }                       // date extraction
    }
  }
]);

Always Project Sensitive Fields Out

Never return sensitive fields like passwordHash, apiKey, ssn, or creditCardNumber in general-purpose queries. Use exclusion projections or schema-level select: false to ensure these fields never accidentally appear in API responses. Defence in depth means applying projections at the data layer as a backstop, even if the application already strips these fields from responses.

Quick Check

Test your understanding of MongoDB & NoSQL Databases concepts from this lesson.

Lesson Recap

In this lesson you learned: inclusion projections (value 1) return only listed fields, exclusion projections (value 0) return all fields except the listed ones, and you cannot mix inclusion and exclusion except for _id: 0 with inclusion fields. Next up we explore projecting nested fields and arrays using dot notation and $slice.

Pertanyaan yang Sering Diajukan

Apakah pelajaran “Proyeksi Inklusi vs Eksklusi” gratis?

Ya — teks lengkap “Proyeksi Inklusi vs Eksklusi” gratis dibaca di sini di web. Untuk praktiknya secara interaktif (editor kode bawaan dan tutor AI 24/7) dan buka sisa kursus MongoDB Academy, upgrade ke CoddyKit PRO. Kursus MongoDB Academy mencakup 4 pelajaran total.

Apa yang akan aku pelajari di “Proyeksi Inklusi vs Eksklusi”?

Pilih atau sembunyikan bidang tertentu dalam hasil kueri dan pahami alasan inklusi serta eksklusi tidak dapat dicampur dalam satu proyeksi. Kamu berlatih MongoDB Academy dengan kode praktik yang langsung kamu jalankan di browser, dan tutor AI 24/7 menjawab pertanyaanmu saat kamu mengerjakan pelajaran ini.

Apakah aku perlu pengalaman untuk memulai MongoDB Academy?

Tidak diperlukan pengalaman sebelumnya. MongoDB Academy di CoddyKit dirancang untuk pemula hingga pelajar tingkat lanjut, jadi kamu bisa memulai di sini atau dari awal dan belajar sesuai kecepatan kamu sendiri. Ini adalah pelajaran 1 dari 4.

Berapa lama pelajaran “Proyeksi Inklusi vs Eksklusi” memakan waktu?

Sebagian besar pelajaran CoddyKit memakan waktu sekitar 5–10 menit. Setiap pelajaran ringkas dan interaktif, jadi kamu membuat kemajuan stabil dan melanjutkan dari tempat kamu tinggalkan di web dan aplikasi.

Bisakah aku menulis dan menjalankan kode dalam pelajaran MongoDB Academy ini?

Ya. Setiap pelajaran MongoDB Academy menyertakan editor kode bawaan, jadi kamu menulis dan menjalankan kode nyata langsung di browser dan mendapatkan umpan balik AI instan — tidak diperlukan penyiapan lokal.

Semua pelajaran dalam kursus ini

Proyeksi Inklusi vs Eksklusi
Memproyeksikan Bidang Bertingkat dan Array
Proyeksi Array $ dan $elemMatch
Praktik Terbaik Proyeksi untuk Respons API

← Kembali ke MongoDB Academy