Combining Sort, Skip, Limit, and Projections
Learners will compose a full query chain with filter, projection, sort, and pagination to power a realistic list endpoint.
Combining Sort, Skip, Limit, and Projections is a free MongoDB Academy lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the MongoDB Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
The Complete Query Chain
A production-quality MongoDB list query combines four components: a filter to select matching documents, a projection to select which fields to return, a sort to order the results, and pagination (skip/limit or keyset) to return one page at a time. Understanding how these compose and in what order MongoDB executes them is essential for writing correct and performant queries.
MongoDB's Internal Execution Order
Regardless of the order you chain methods in the driver, MongoDB always executes query components in this fixed sequence: 1) Filter → 2) Sort → 3) Skip → 4) Limit. Projection is applied as documents are read from the storage engine. This order matters: skip operates on the sorted result set, and limit caps the final output after skipping. You cannot change this execution order.
// These two are identical — order of chaining doesn't matter
db.products.find({}).sort({ price: -1 }).skip(20).limit(10);
db.products.find({}).limit(10).skip(20).sort({ price: -1 });
// MongoDB executes: filter -> sort -> skip -> limitBuilding a List API Endpoint
Put it all together in a realistic list endpoint. The example below fetches page 2 of active products in the 'electronics' category, sorted by rating descending, returning only the fields needed for a product card UI. Each piece of the chain serves a specific purpose.
const filter = { category: 'electronics', isActive: true };
const projection = { _id: 1, name: 1, price: 1, thumbnailUrl: 1, rating: 1 };
const PAGE = 2;
const PAGE_SIZE = 20;
const products = await db.collection('products')
.find(filter) // 1. filter
.project(projection) // projection
.sort({ rating: -1, _id: -1 }) // 2. sort
.skip((PAGE - 1) * PAGE_SIZE) // 3. skip
.limit(PAGE_SIZE) // 4. limit
.toArray();The Supporting Index
For the complete query chain to be efficient, you need an index that covers the filter and sort. The filter uses category and isActive (equality), and the sort uses rating and _id. The ideal compound index places equality fields first, then sort fields: { category: 1, isActive: 1, rating: -1, _id: -1 }.
// Index supporting the list API query
db.products.createIndex({ category: 1, isActive: 1, rating: -1, _id: -1 });
// Verify: explain should show IXSCAN and no SORT stage
db.products.find({ category: 'electronics', isActive: true })
.sort({ rating: -1, _id: -1 })
.skip(20)
.limit(20)
.explain('executionStats');The Complete Mongoose Query Chain
Mongoose's fluent API makes the same query chain readable and type-safe. Chain .find(), .select(), .sort(), .skip(), and .limit(), then call .lean() for a plain POJO result (much faster than full Mongoose documents when you don't need lifecycle hooks or virtuals).
const products = await Product
.find({ category: 'electronics', isActive: true })
.select({ name: 1, price: 1, thumbnailUrl: 1, rating: 1, _id: 1 })
.sort({ rating: -1, _id: -1 })
.skip((PAGE - 1) * PAGE_SIZE)
.limit(PAGE_SIZE)
.lean(); // returns plain objects, not Mongoose Documents
console.log('Products on page:', products.length);Returning Pagination Metadata
A well-designed list API response includes pagination metadata alongside the data array: the current page, page size, total document count, total page count, and whether there is a next/previous page. This lets clients render pagination controls without making a separate count request. Always return metadata and data together in one response object.
const [total, items] = await Promise.all([
Product.countDocuments({ category: 'electronics', isActive: true }),
Product.find({ category: 'electronics', isActive: true })
.select({ name: 1, price: 1, thumbnailUrl: 1, rating: 1 })
.sort({ rating: -1 })
.skip((PAGE - 1) * PAGE_SIZE)
.limit(PAGE_SIZE)
.lean()
]);
res.json({
data: items,
page: PAGE,
pageSize: PAGE_SIZE,
total: total,
totalPages: Math.ceil(total / PAGE_SIZE),
hasNext: PAGE * PAGE_SIZE < total,
hasPrev: PAGE > 1
});Applying Default Values and Input Validation
Always validate and sanitise the page, limit, and sort query parameters before using them in a MongoDB query. Unchecked values can cause skip(-5) errors, enormous limit(999999) calls that exhaust memory, or sort injections if you pass user-provided sort keys directly. Whitelist allowed sort fields and enforce sane min/max bounds on page and limit.
const ALLOWED_SORT_FIELDS = new Set(['rating', 'price', 'createdAt']);
function parseListParams(query) {
const page = Math.max(1, parseInt(query.page) || 1);
const limit = Math.min(100, Math.max(1, parseInt(query.limit) || 20));
const sortField = ALLOWED_SORT_FIELDS.has(query.sort) ? query.sort : 'createdAt';
const sortDir = query.order === 'asc' ? 1 : -1;
return { page, limit, sort: { [sortField]: sortDir, _id: sortDir } };
}Switching Between Offset and Keyset Pagination
You can offer both pagination modes from the same endpoint by checking for a cursor parameter (keyset) vs a page parameter (offset). When cursor is provided, apply the range filter and omit skip(). When only page is provided, use skip(). This lets you migrate clients gradually from offset to keyset pagination without breaking backward compatibility.
async function listItems(req, res) {
const limit = 20;
let query = Product.find({ isActive: true }).sort({ createdAt: -1, _id: -1 }).limit(limit);
if (req.query.cursor) {
const { createdAt, _id } = decodeCursor(req.query.cursor);
query = query.where('$or').equals([
{ createdAt: { $lt: new Date(createdAt) } },
{ createdAt: new Date(createdAt), _id: { $lt: _id } }
]);
} else if (req.query.page) {
const page = Math.max(1, parseInt(req.query.page) || 1);
query = query.skip((page - 1) * limit);
}
const items = await query.lean();
res.json({ items, nextCursor: items.length === limit ? encodeCursor(items.at(-1)) : null });
}Testing the Query Chain
Test your complete query chain with both unit tests (mock the driver) and integration tests (real MongoDB via an in-memory mongod or testcontainers). Seed the test collection with enough documents to verify that pagination boundaries are correct: that page 1 and page 2 together return exactly 2×pageSize distinct documents with no duplicates or gaps.
Caching Paginated Results
For read-heavy paginated APIs, consider caching responses at the HTTP level (Redis or a CDN) keyed by the full query string including page, sort, and filters. Cache TTLs of 10-60 seconds reduce database load dramatically for popular queries. Be aware that cached responses may return slightly stale data—acceptable for most use cases but not for financial or real-time dashboards.
Verifying the Full Chain With explain()
Run your complete find chain with explain('executionStats') to validate the full query plan. The ideal plan shows: IXSCAN for the filter, the same index scan serving the sort (no separate SORT stage), and nReturned equal to your limit value. Any unexpected COLLSCAN or SORT stage indicates a missing or ineffective index.
const stats = await db.collection('products')
.find({ category: 'electronics', isActive: true })
.sort({ rating: -1, _id: -1 })
.skip(20)
.limit(20)
.explain('executionStats');
const stage = stats.executionStats.executionStages;
console.log('Stage:', stage.stage); // should be LIMIT
console.log('Docs examined:', stats.executionStats.totalDocsExamined);
console.log('Docs returned:', stats.executionStats.nReturned);Quick Check
Test your understanding of MongoDB & NoSQL Databases concepts from this lesson.
Lesson Recap
In this lesson you learned: MongoDB always executes filter → sort → skip → limit regardless of method chaining order, the supporting index should place equality fields first then sort fields, and pagination metadata (total, hasNext, hasPrev) should be returned alongside the data array. Next up we explore importing and exporting data with mongoimport, mongoexport, and seed scripts.
Frequently asked questions
Is the “Combining Sort, Skip, Limit, and Projections” lesson free?
Yes — the full text of “Combining Sort, Skip, Limit, and Projections” is free to read here on the web, and the MongoDB Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the MongoDB Academy course, upgrade to CoddyKit PRO.
What will I learn in “Combining Sort, Skip, Limit, and Projections”?
Learners will compose a full query chain with filter, projection, sort, and pagination to power a realistic list endpoint. You practise MongoDB Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start MongoDB Academy?
No prior experience is required. MongoDB Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Combining Sort, Skip, Limit, and Projections” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this MongoDB Academy lesson?
Yes. Every MongoDB Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Sorting With sort() and Multiple Keys
- Skip and Limit: Offset Pagination
- Keyset Pagination With Range Queries
- Combining Sort, Skip, Limit, and Projections