MongoDB Academy · レッスン

skipとlimit：オフセットページネーション

skip()とlimit()を使って従来のページ番号方式のページネーションを実装し、大規模なコレクションでの性能コストを測定します。

「skipとlimit：オフセットページネーション」はCoddyKit上の無料MongoDB Academyレッスンです。これはレッスン2/4です。下記で完全なレッスンを無料で読むことができます。その後、ブラウザ内の組み込みコードエディタと24時間対応のAIチューターでハンズオン演習できます。これはMongoDB Academy学習パスの一部であり、ウェブとCoddyKitアプリ全体で進捗が同期されます。 MongoDB Academyコースには全4レッスンが含まれています。

このレッスンの一部はまだ翻訳されておらず、英語で表示されています。

What Is Offset Pagination?

Offset pagination—also called page-number pagination—divides results into fixed-size pages and uses a page number to determine how far into the result set to start. Page 1 shows items 1-20, page 2 shows items 21-40, and so on. In MongoDB this is implemented with skip() to jump over earlier results and limit() to restrict how many documents are returned per page.

Using skip() and limit()

limit(N) tells the cursor to return at most N documents. skip(N) tells MongoDB to skip the first N documents before returning any results. Together they implement page-number pagination: to get page P with size S items per page, use skip((P-1)*S) and limit(S).

const PAGE = 3;
const PAGE_SIZE = 20;

// Page 3 of 20 results per page
const products = await db.collection('products')
  .find({ isActive: true })
  .sort({ createdAt: -1 })
  .skip((PAGE - 1) * PAGE_SIZE)  // skip 40 docs (pages 1 and 2)
  .limit(PAGE_SIZE)               // return next 20
  .toArray();

console.log('Page 3 results:', products.length);

Counting Total Pages

Offset pagination usually requires a total document count to display page numbers in the UI. Use countDocuments(filter) to count matching documents before applying pagination. Run the count and the paged query in parallel to avoid adding latency. The total count divided by the page size (rounded up) gives the total number of pages.

const filter = { isActive: true };

const [total, results] = await Promise.all([
  db.collection('products').countDocuments(filter),
  db.collection('products')
    .find(filter)
    .sort({ createdAt: -1 })
    .skip((PAGE - 1) * PAGE_SIZE)
    .limit(PAGE_SIZE)
    .toArray()
]);

const totalPages = Math.ceil(total / PAGE_SIZE);
console.log('Total:', total, 'Pages:', totalPages);

The Hidden Cost of skip()

MongoDB implements skip() by scanning and discarding the first N documents. Even with an index, MongoDB must walk through and count N index entries before returning results. On page 1, skip is 0—fast. On page 500 with 20 items per page, skip is 9980—MongoDB must traverse nearly 10,000 entries just to find where page 500 starts. This is the core performance problem with offset pagination.

O(skip + limit) Query Complexity

The time to execute a skip/limit query grows linearly with the skip amount. The query cost is O(skip + limit)—the server must examine skip documents before returning limit documents. For page 1 this is O(20); for page 1000 with 20 items per page it is O(20020). As users navigate to higher page numbers, queries get progressively slower, often going from milliseconds to seconds on large collections.

When Offset Pagination Is Acceptable

Despite its performance limitations, offset pagination is acceptable in these scenarios: (1) the collection has fewer than a few thousand documents; (2) users rarely navigate beyond the first few pages; (3) the feature requires jumping directly to a page number (e.g., 'go to page 47'). Many admin dashboards and search results with low page depth fit this profile. Use keyset pagination for infinite scroll or large data sets.

Implementing an API Endpoint With Offset Pagination

A typical REST list endpoint accepts page and limit query parameters, validates them, and applies skip/limit accordingly. Always cap the maximum limit to prevent clients from requesting thousands of documents in a single call, which would exhaust server memory.

// Express route: GET /api/products?page=2&limit=20
async function listProducts(req, res) {
  const page  = Math.max(1, parseInt(req.query.page)  || 1);
  const limit = Math.min(100, parseInt(req.query.limit) || 20); // cap at 100
  const skip  = (page - 1) * limit;

  const [total, items] = await Promise.all([
    Product.countDocuments({ isActive: true }),
    Product.find({ isActive: true }).sort('-createdAt').skip(skip).limit(limit).lean()
  ]);

  res.json({ page, limit, total, totalPages: Math.ceil(total / limit), items });
}

Data Consistency Issues With Offset Pagination

Offset pagination has a subtle correctness problem: if documents are inserted or deleted between page requests, items can shift positions in the sorted result set. A document inserted between page 1 and page 2 pushes every subsequent document forward, causing one item to appear on both pages (duplicate) or be skipped entirely. This is called the page drift problem and is inherent to offset pagination.

Estimating vs Exact Count

For very large collections, countDocuments(filter) can be slow because it scans the index. An alternative is estimatedDocumentCount(), which is O(1) but counts all documents in the collection without applying a filter. For simple cases where you want the total without filtering, the estimated count is much faster. For filtered counts on large collections, consider caching the count or using Atlas's faceted search.

// O(1) but no filter support
const approxTotal = await db.collection('products').estimatedDocumentCount();

// Exact count with filter (slower on large collections)
const exactTotal = await db.collection('products').countDocuments({ isActive: true });

Combining skip/limit With Projections

Always combine pagination with a tight projection for list endpoints. Fetching all fields while paginating defeats the purpose: you're still paying to transfer full document payloads for every page. A projection that returns only summary fields (name, price, thumbnail) reduces bandwidth by 80-95% compared to fetching full documents, making pagination viable at larger page offsets.

const SUMMARY = { _id: 1, name: 1, price: 1, thumbnailUrl: 1, rating: 1 };

const items = await db.collection('products')
  .find({ isActive: true })
  .projection(SUMMARY)
  .sort({ rating: -1 })
  .skip((PAGE - 1) * PAGE_SIZE)
  .limit(PAGE_SIZE)
  .toArray();

When to Switch to Keyset Pagination

Switch from offset to keyset (cursor) pagination when: users scroll infinitely through results (no page numbers needed), the collection has more than 100,000 documents, page load times increase noticeably for higher page numbers, or data changes frequently between page requests. Keyset pagination is always O(log n) regardless of position in the result set, because it uses a range query on an indexed field instead of skip.

Quick Check

Test your understanding of MongoDB & NoSQL Databases concepts from this lesson.

Lesson Recap

In this lesson you learned: offset pagination uses skip((page-1)*size) and limit(size) to fetch a page, skip() scans and discards documents so deep pages become progressively slower, and offset pagination is acceptable for small collections or shallow page depths but keyset pagination is better at scale. Next up we implement keyset pagination with range queries for consistent O(log n) performance.

よくある質問

「skipとlimit：オフセットページネーション」レッスンは無料ですか？

はい。「skipとlimit：オフセットページネーション」の完全なテキストはこのウェブで無料で読めます。インタラクティブに演習し（組み込みコードエディタと24時間対応のAIチューター）、MongoDB Academyコースの残りをアンロックするには、CoddyKit PROにアップグレードしてください。 MongoDB Academyコースには全4レッスンが含まれています。

「skipとlimit：オフセットページネーション」で何を学びますか？

skip()とlimit()を使って従来のページ番号方式のページネーションを実装し、大規模なコレクションでの性能コストを測定します。ブラウザで直接実行するハンズオンコードでMongoDB Academyを演習し、24時間対応のAIチューターがレッスンを進める中での質問に答えます。

MongoDB Academyを始めるのに経験は必要ですか？

事前経験は必要ありません。CoddyKitのMongoDB Academyは初級者から上級者向けに構成されているため、ここから始めるか最初から始めて、自分のペースで進むことができます。これはレッスン2/4です。

「skipとlimit：オフセットページネーション」レッスンにはどのくらい時間がかかりますか？

ほとんどのCoddyKitレッスンは約5～10分かかります。各レッスンはコンパクトでインタラクティブなので、着実に進歩し、ウェブとアプリ全体で正確に前回の場所から再開できます。

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