0Pricing
MongoDB Academy · 강의

정렬, Skip, Limit, 프로젝션 조합하기

학습자는 필터, 프로젝션, 정렬, 페이지 매김을 포함한 전체 쿼리 체인을 구성해 실제적인 목록 엔드포인트를 구현합니다.

정렬, Skip, Limit, 프로젝션 조합하기은(는) CoddyKit의 무료 MongoDB Academy 강의입니다. 이것은 4개 중 4번째 강의입니다. 아래에서 전체 강의를 무료로 읽을 수 있으며, 내장 코드 에디터와 24/7 AI 튜터와 함께 브라우저에서 직접 실습할 수 있습니다. 이 강의는 MongoDB Academy 학습 경로의 일부이며, 진행 상황이 웹과 CoddyKit 앱에 동기화됩니다. MongoDB Academy 강의에는 총 4개의 강의가 포함되어 있습니다.

이 강의의 일부는 아직 번역되지 않았으며 영어로 표시됩니다.

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 -> limit

Building 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.

자주 묻는 질문

“정렬, Skip, Limit, 프로젝션 조합하기” 강의는 무료인가요?

네 — “정렬, Skip, Limit, 프로젝션 조합하기” 전체 내용을 이 웹사이트에서 무료로 읽을 수 있습니다. 인터랙티브하게 실습하려면(내장 코드 에디터와 24/7 AI 튜터), CoddyKit PRO로 업그레이드하면 MongoDB Academy 강의 전체를 잠금 해제할 수 있습니다. MongoDB Academy 강의에는 총 4개의 강의가 포함되어 있습니다.

“정렬, Skip, Limit, 프로젝션 조합하기”에서 뭘 배우나요?

학습자는 필터, 프로젝션, 정렬, 페이지 매김을 포함한 전체 쿼리 체인을 구성해 실제적인 목록 엔드포인트를 구현합니다. 브라우저에서 직접 실행하는 실습 코드로 MongoDB Academy을(를) 배우며, 24/7 AI 튜터가 강의를 진행하면서 질문에 답변해줍니다.

MongoDB Academy을(를) 시작하는 데 경험이 필요한가요?

사전 경험은 필요하지 않습니다. CoddyKit의 MongoDB Academy은(는) 초급자부터 고급 학습자까지를 위해 구성되어 있으므로, 여기서 시작하거나 처음부터 시작할 수 있으며 자신의 속도대로 진행할 수 있습니다. 이것은 4개 중 4번째 강의입니다.

“정렬, Skip, Limit, 프로젝션 조합하기” 강의는 얼마나 걸리나요?

대부분의 CoddyKit 강의는 약 5~10분이 소요됩니다. 각 강의는 간결하고 인터랙티브하여 꾸준한 진행이 가능하며, 웹과 앱에서 중단한 부분부터 바로 시작할 수 있습니다.

이 MongoDB Academy 강의에서 코드를 작성하고 실행할 수 있나요?

네. 모든 MongoDB Academy 강의에는 내장 코드 에디터가 포함되어 있으므로, 브라우저에서 바로 실제 코드를 작성하고 실행한 후 즉시 AI 피드백을 받을 수 있습니다 — 로컬 설정이 필요 없습니다.

이 강의의 모든 강의

  1. sort()와 여러 키로 정렬하기
  2. Skip과 Limit: 오프셋 페이지 매김
  3. 범위 쿼리를 이용한 키셋 페이지 매김
  4. 정렬, Skip, Limit, 프로젝션 조합하기
← MongoDB Academy(으)로 돌아가기