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$unwind: Menguraikan Bidang Array

Peserta didik akan meratakan bidang array menjadi dokumen individual dengan $unwind dan menggabungkannya dengan $group untuk analitik per elemen.

$unwind: Menguraikan Bidang Array 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 Does $unwind Do?

The $unwind stage deconstructs an array field in a document into multiple output documents—one per array element. Each output document is a copy of the original document with the array field replaced by a single element from the array. This is essential for per-element analytics, like counting how many times each tag appears across all articles in a collection.

// Input document:
// { title: 'MongoDB Guide', tags: ['nosql', 'database', 'mongodb'] }

db.articles.aggregate([
  { $unwind: '$tags' }
]);
// Output: THREE documents:
// { title: 'MongoDB Guide', tags: 'nosql' }
// { title: 'MongoDB Guide', tags: 'database' }
// { title: 'MongoDB Guide', tags: 'mongodb' }

Basic $unwind Syntax

The simplest form of $unwind is a string with the dollar-prefixed field path: { $unwind: '$arrayField' }. The extended object syntax allows additional options like preserving empty arrays and including the array index. For most cases, the simple string form is sufficient.

// Simple string form
db.products.aggregate([
  { $unwind: '$reviews' }
]);

// Extended object form with options
db.products.aggregate([
  { $unwind: {
    path: '$reviews',
    includeArrayIndex: 'reviewIndex',   // add index field
    preserveNullAndEmptyArrays: true    // keep docs with no reviews
  }}
]);

The Missing Array Problem

By default, $unwind removes documents where the specified field is missing, null, or an empty array. This behavior is like an inner join: only documents with non-empty arrays pass through. To preserve documents with missing or empty arrays, set preserveNullAndEmptyArrays: true. This is important when the array field is optional and you don't want to lose the parent document.

// Default: documents without 'tags' are DROPPED
db.articles.aggregate([{ $unwind: '$tags' }]);
// Article with no tags: { title: 'Untitled' } -> EXCLUDED

// preserveNullAndEmptyArrays: documents are KEPT
db.articles.aggregate([{
  $unwind: {
    path: '$tags',
    preserveNullAndEmptyArrays: true  // keep docs with no tags
  }
}]);
// { title: 'Untitled' } -> INCLUDED with tags: null

includeArrayIndex for Element Position

The includeArrayIndex option adds a new field to each output document containing the 0-based index of the element in the original array. This is useful when the position in the array carries meaning—for example, the order of steps in a process, the rank of a search result, or the sequence of events in a log.

// Track which position each tag appeared at in the original array
db.articles.aggregate([{
  $unwind: {
    path: '$tags',
    includeArrayIndex: 'tagPosition'
  }
}]);
// { title: 'Guide', tags: 'nosql', tagPosition: 0 }
// { title: 'Guide', tags: 'database', tagPosition: 1 }
// { title: 'Guide', tags: 'mongodb', tagPosition: 2 }

$unwind Followed by $group

The most common pattern in MongoDB aggregation is $unwind + $group: first flatten the array to get one document per element, then group to compute per-element statistics. For example, unwinding the tags array and then grouping by tag name gives you the count of articles per tag.

// Count how many articles use each tag
db.articles.aggregate([
  { $unwind: '$tags' },      // one doc per tag
  { $group: {
    _id: '$tags',            // group by tag value
    count: { $sum: 1 }       // count articles per tag
  }},
  { $sort: { count: -1 } }, // most popular first
  { $limit: 20 }            // top 20 tags
]);

$unwind With $lookup Results

After a $lookup, the joined field is always an array. When the join is one-to-one (joining by a unique _id), you typically $unwind immediately to flatten the single-element array into an embedded object. This is such a common pattern that you'll see it in almost every pipeline that uses $lookup.

db.orders.aggregate([
  { $lookup: {
    from: 'customers',
    localField: 'customerId',
    foreignField: '_id',
    as: 'customer'
  }},
  // Flatten the single-element array
  { $unwind: '$customer' },
  // Now access customer fields as objects
  { $project: {
    orderId: '$_id',
    amount: 1,
    'customer.name': 1,
    'customer.email': 1
  }}
]);

Flattening Nested Arrays

For documents with nested arrays (arrays inside arrays), you can use multiple consecutive $unwind stages. The first $unwind deconstructs the outer array, and the second deconstructs the inner array. Each stage multiplies the number of output documents, so be cautious with deep nesting to avoid explosive document expansion.

// Document: { course: 'Math', modules: [{ name: 'Algebra', lessons: ['L1', 'L2'] }] }

db.courses.aggregate([
  { $unwind: '$modules' },      // deconstruct modules array
  { $unwind: '$modules.lessons' }  // deconstruct nested lessons array
]);
// Output:
// { course: 'Math', modules: { name: 'Algebra', lessons: 'L1' } }
// { course: 'Math', modules: { name: 'Algebra', lessons: 'L2' } }

Calculating Array Element Statistics

A powerful use case for $unwind is computing statistics on individual array elements. For example, in an e-commerce database with orders containing line items (an array of sub-documents), unwinding line items lets you compute total revenue, average quantity, or top-selling items across all line items in all orders—not just per order.

// Total revenue and quantity per product across all orders
db.orders.aggregate([
  { $unwind: '$lineItems' },  // deconstruct line items
  { $group: {
    _id: '$lineItems.productId',
    totalRevenue: { $sum: { $multiply: ['$lineItems.price', '$lineItems.qty'] } },
    totalQty: { $sum: '$lineItems.qty' },
    orderCount: { $sum: 1 }  // how many orders contained this product
  }},
  { $sort: { totalRevenue: -1 } }
]);

Avoiding $unwind When Possible

$unwind can dramatically multiply the number of documents in the pipeline (a document with a 100-element array becomes 100 documents after unwind). This increases memory usage and processing time for all subsequent stages. Always ask: 'Can I achieve this with an array expression operator like $size, $filter, or $map in a $project stage instead of unwinding?' Array expression operators are often faster because they don't expand the document count.

// Better: use $size in $project instead of $unwind + $count
// Avoid:
db.articles.aggregate([
  { $unwind: '$tags' },
  { $group: { _id: '$_id', tagCount: { $sum: 1 } } }  // slow
]);

// Better:
db.articles.aggregate([{
  $project: {
    title: 1,
    tagCount: { $size: { $ifNull: ['$tags', []] } }  // fast
  }
}]);

$unwind Performance Impact

Because $unwind multiplies documents, it is usually the most expensive stage in a pipeline when applied to large arrays. Performance tips: apply $match and $project before $unwind to reduce the input document size and count; add a $match immediately after $unwind if you only care about specific elements; and limit the number of documents entering the unwind with an early $limit when applicable.

// Optimized order for $unwind pipelines:
db.orders.aggregate([
  { $match: { status: 'completed', createdAt: { $gte: thisMonth } } },  // 1. filter first
  { $project: { lineItems: 1, _id: 0 } },  // 2. project only needed fields
  { $unwind: '$lineItems' },               // 3. expand (smaller docs now)
  { $match: { 'lineItems.qty': { $gt: 5 } } },  // 4. filter expanded results
  { $group: { _id: '$lineItems.productId', count: { $sum: 1 } } }
]);

Reconstructing Arrays After $unwind

After a $unwind + $group pipeline, you can use $push in the $group stage to rebuild an array from the processed elements. This pattern is useful for filtering or transforming array elements: unwind to get individual elements, apply per-element transformations or filters, then push back into a new array. This is more flexible than using $filter or $map for complex per-element logic.

// Filter out low-rated reviews per product, keep only rating >= 4
db.products.aggregate([
  { $unwind: '$reviews' },
  { $match: { 'reviews.rating': { $gte: 4 } } },  // per-element filter
  { $group: {
    _id: '$_id',
    name: { $first: '$name' },
    goodReviews: { $push: '$reviews' }  // rebuild filtered array
  }}
]);
// Each product now has only its 4+ star reviews in goodReviews

Quick Check

Test your understanding of $unwind in the aggregation pipeline.

Lesson Recap

In this lesson you learned: $unwind creates one output document per array element, preserveNullAndEmptyArrays: true keeps documents with missing or empty arrays, and the classic $unwind + $group pattern enables per-element analytics like tag frequency counts. Next up we explore $addFields, $replaceRoot, and $mergeObjects.

Pertanyaan yang Sering Diajukan

Apakah pelajaran “$unwind: Menguraikan Bidang Array” gratis?

Ya — teks lengkap “$unwind: Menguraikan Bidang Array” 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 “$unwind: Menguraikan Bidang Array”?

Peserta didik akan meratakan bidang array menjadi dokumen individual dengan $unwind dan menggabungkannya dengan $group untuk analitik per elemen. 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 “$unwind: Menguraikan Bidang Array” 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

  1. $lookup: Menggabungkan Koleksi dalam Alur
  2. $unwind: Menguraikan Bidang Array
  3. $addFields, $replaceRoot, dan $mergeObjects
  4. $out dan $merge: Menulis Hasil Alur
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