Setting the file. One moment.
Chapter 06 · MongoDB Schema Design
Subchapter 6.11
references/pattern-bucket.mdMarkdown4 KBView on GitHub
Group a series of related items into bounded arrays within a single document. The bucket pattern separates long series of data into distinct objects, reducing document count and aligning storage with how data is actually consumed. This is especially useful when an application accesses data in fixed-size groups (e.g. pages).
For time-series data, prefer Time Series Collections (opens in a new tab), which apply bucketing automatically with built-in compression and indexing optimizations.
Incorrect (one document per event):
Storing one document per stock trade (e.g. { ticker, customerId, type, quantity, date }) means the application pages through trades using skip/limit, which degrades as offset grows. Each trade is a separate document and index entry.
Correct (bucket pattern - group by customer, bounded per page):
Each document holds up to N trades for one customer (e.g. 10 trades = one page). The _id encodes customer ID and the first trade’s epoch seconds (e.g. "123_1698349623"), with a count field and a history array of trade objects. One bucket equals one page of data — a regex on _id uses the default _id index with no extra index needed, and document count drops by up to the bucket-size factor.
Insert with atomic upsert:
// Insert a new trade into the correct bucket
db.trades.findOneAndUpdate(
{
"_id": /^123_/, // Match buckets for this customer
"count": { $lt: 10 } // Only if bucket isn't full
},
{
$push: {
history: {
type: "buy",
ticker: "MSFT",
qty: 42,
date: ISODate("2023-11-02T11:43:10Z")
}
},
$inc: { count: 1 },
$setOnInsert: {
_id: "123_1698939791", // New bucket ID if upsert fires
customerId: 123
}
},
{ upsert: true, sort: { _id: -1 } }
)
// If a bucket with room exists, the trade is pushed into it
// Otherwise a new bucket document is created
// Array is bounded — never exceeds 10 elementsQuery patterns:
// Page 1 of trades for customer 123
db.trades.find({ _id: /^123_/ }).sort({ _id: 1 }).limit(1)
// Page N (e.g. page 10)
db.trades.find({ _id: /^123_/ }).sort({ _id: 1 }).skip(9).limit(1)
// Each returned document IS a page — no per-trade skip/limit neededChoosing bucket boundaries:
| Bucketing Strategy | Good For | Example |
|---|---|---|
| Fixed count (N items) | Pagination, evenly-sized pages | 10 trades per bucket |
| Time window | Log/event grouping (when not using Time Series Collections) | 1 hour of events per bucket |
| Logical grouping | Domain-driven partitioning | All line items in one order |
When NOT to use this pattern:
// Check that bucket size matches expectations
db.trades.aggregate([
{ $group: {
_id: null,
avgCount: { $avg: "$count" },
maxCount: { $max: "$count" },
totalBuckets: { $sum: 1 }
}}
])
// avgCount should approach your target bucket size
// maxCount should not exceed it
// Check average document size
db.trades.aggregate([
{ $project: { size: { $bsonSize: "$$ROOT" } } },
{ $group: { _id: null, avgSize: { $avg: "$size" } } }
])