Referensi: Satu-ke-Banyak dan Banyak-ke-Banyak
Simpan referensi ObjectId di berbagai koleksi dan gunakan $lookup untuk menggabungkannya saat kueri dijalankan.
Referensi: Satu-ke-Banyak dan Banyak-ke-Banyak adalah pelajaran MongoDB Academy gratis di CoddyKit. Ini adalah pelajaran 2 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 Referencing?
Referencing means storing an ObjectId (or another unique identifier) inside one document that points to a document in a different collection, similar to a foreign key in relational databases. Instead of nesting data, you link it. This approach is essential when the child count is large, when children are shared among multiple parents, or when children need to be queried independently.
One-to-Many With References
In a one-to-many relationship a single parent has many children. A user can have hundreds of orders—far too many to safely embed. Instead, each order document stores a userId reference pointing back to the parent user. This keeps the user document small while allowing unbounded order growth.
// users collection
db.users.insertOne({ _id: ObjectId('u1'), name: 'Alice', email: 'alice@example.com' });
// orders collection — each order references the user
db.orders.insertMany([
{ _id: ObjectId('o1'), userId: ObjectId('u1'), total: 49.99, status: 'shipped' },
{ _id: ObjectId('o2'), userId: ObjectId('u1'), total: 120.00, status: 'pending' }
]);Many-to-Many With References
A many-to-many relationship—like students enrolled in multiple courses, and courses containing multiple students—cannot be embedded without duplication. The cleanest approach is to store an array of references on one side. For example, each student document holds an array of courseId values it is enrolled in.
db.students.insertOne({
_id: ObjectId('s1'),
name: 'Bob',
enrolledCourses: [ ObjectId('c1'), ObjectId('c2'), ObjectId('c3') ]
});
db.courses.insertOne({
_id: ObjectId('c1'),
title: 'MongoDB Fundamentals',
instructorId: ObjectId('i1')
});Joining References With $lookup
To retrieve a document along with its referenced data, use the $lookup aggregation stage. It performs a left outer join between two collections. The from field names the collection to join, localField is the reference field in the current collection, and foreignField is the field to match in the joined collection.
// Fetch orders and join the user for each order
db.orders.aggregate([
{ $match: { status: 'shipped' } },
{
$lookup: {
from: 'users',
localField: 'userId',
foreignField: '_id',
as: 'user'
}
},
{ $unwind: '$user' },
{ $project: { total: 1, status: 1, 'user.name': 1 } }
]);Child-Side vs Parent-Side References
You can store the reference on either side of the relationship. Child-side reference: the child stores the parent's ID (e.g., order.userId)—queries like 'all orders for a user' are simple range queries. Parent-side reference: the parent stores an array of child IDs (e.g., user.orderIds)—useful when you frequently retrieve all child IDs without querying child documents.
Many-to-Many $lookup Example
To resolve a many-to-many relationship—finding all courses a student is enrolled in—use $lookup with the array of IDs stored in the student document. The $in syntax inside $lookup's pipeline form lets you match multiple IDs efficiently.
db.students.aggregate([
{ $match: { name: 'Bob' } },
{
$lookup: {
from: 'courses',
localField: 'enrolledCourses',
foreignField: '_id',
as: 'courses'
}
},
{ $project: { name: 1, 'courses.title': 1 } }
]);Referencing in Mongoose With populate()
Mongoose provides the populate() method as an abstraction over $lookup. You declare a field as a reference using type: mongoose.Schema.Types.ObjectId, ref: 'ModelName', and then call .populate('fieldName') on a query to automatically resolve the reference to the full document.
const orderSchema = new mongoose.Schema({
userId: { type: mongoose.Schema.Types.ObjectId, ref: 'User' },
total: Number,
status: String
});
// Usage: populate resolves userId to the full User document
const orders = await Order.find({ status: 'shipped' }).populate('userId', 'name email');Indexing the Reference Field
When querying child documents by their parent reference—such as all orders for a given user—MongoDB must scan the entire collection unless the userId field is indexed. Always create an index on reference fields used in frequent queries. An index on userId turns a full collection scan into a fast index scan.
// Create an index on the reference field for fast lookups
db.orders.createIndex({ userId: 1 });
// Now this query hits the index instead of scanning all orders
db.orders.find({ userId: ObjectId('u1') });Shared Data: The Case for References
When multiple documents share the same child—like many blog posts sharing the same author profile—embedding would duplicate the author data in every post. With referencing, only the authorId is stored in each post. If the author's name changes, one update to the authors collection propagates everywhere, whereas with embedding you'd have to update every post.
Performance Trade-offs of References
Referencing requires at least two round trips to the database (or one aggregation with $lookup) to fetch the parent and its children. This is slower than a single embedded read, but the trade-off is often worth it when children are large in number, updated independently, or shared across parents. Design choices always depend on your dominant query patterns.
Combining Embedding and Referencing
Real schemas often mix both strategies. An order document might embed the shipping address (immutable at order time) while referencing the productId for each line item (shared catalogue data). This hybrid approach co-locates data that changes together and references data that is shared or grows independently. There is no rule against mixing the two patterns in a single document.
db.orders.insertOne({
_id: ObjectId(),
userId: ObjectId('u1'), // reference to user
shippingAddress: { // embedded snapshot
street: '123 Maple St',
city: 'Austin',
zip: '78701'
},
items: [
{ productId: ObjectId('p1'), qty: 2, price: 19.99 } // reference to product
]
});Quick Check
Test your understanding of MongoDB & NoSQL Databases concepts from this lesson.
Lesson Recap
In this lesson you learned: referencing stores ObjectId links across collections, $lookup and populate() resolve references at query time, and referencing is preferred when child count is large, data is shared, or children need independent updates. Next up we explore the unbounded array anti-pattern—when embedding goes wrong.
Pertanyaan yang Sering Diajukan
Apakah pelajaran “Referensi: Satu-ke-Banyak dan Banyak-ke-Banyak” gratis?
Ya — teks lengkap “Referensi: Satu-ke-Banyak dan Banyak-ke-Banyak” 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 “Referensi: Satu-ke-Banyak dan Banyak-ke-Banyak”?
Simpan referensi ObjectId di berbagai koleksi dan gunakan $lookup untuk menggabungkannya saat kueri dijalankan. 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 2 dari 4.
Berapa lama pelajaran “Referensi: Satu-ke-Banyak dan Banyak-ke-Banyak” 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
- Penyematan: Relasi Satu-ke-Sedikit
- Referensi: Satu-ke-Banyak dan Banyak-ke-Banyak
- Antipola Array Tak Terbatas
- Kerangka Keputusan Desain Skema