$unwind: descomposición de campos de array
Aplanará un campo de array en documentos individuales con $unwind y lo combinará con $group para realizar análisis por elemento.
$unwind: descomposición de campos de array es una lección gratuita de MongoDB Academy en CoddyKit. Esta es la lección 2 de 4. Puedes leer la lección completa abajo gratuitamente — luego la practicas en el navegador con un editor de código integrado y un tutor de IA 24/7. Forma parte de la ruta de aprendizaje de MongoDB Academy, y tu progreso se sincroniza en la web y la app de CoddyKit. El curso de MongoDB Academy incluye 4 lecciones en total.
Partes de esta lección aún no han sido traducidas y se muestran en inglés.
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: nullincludeArrayIndex 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 goodReviewsQuick 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 $mergeObjects.
Preguntas frecuentes
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¿Qué aprenderé en «$unwind: descomposición de campos de array»?
Aplanará un campo de array en documentos individuales con $unwind y lo combinará con $group para realizar análisis por elemento. Practicas MongoDB Academy con código real que ejecutas directamente en el navegador, y un tutor de IA 24/7 responde tus preguntas mientras trabajas en la lección.
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Todas las lecciones de este curso
- $lookup: combinación de colecciones en el pipeline
- $unwind: descomposición de campos de array
- $addFields, $replaceRoot y $mergeObjects
- $out y $merge: escritura de resultados del pipeline