Many Answers From One Pass ($facet and $bucket)

Why this matters

$facet lets you run multiple aggregation sub-pipelines over the same input documents in a single pass, which is how faceted search ("show me counts per category AND per price range AND per rating simultaneously") works without three separate queries. $bucket groups continuous numeric values into defined ranges — the building block for histograms, price range filters, and age distribution charts. Understanding these stages matters because the naive alternative is running three queries and merging results in application code, which is 3× the database load, 3× the latency, and produces inconsistent snapshots since each query runs at a different moment.

Demo

Compute category counts and price-range buckets in a single aggregation pass using $facet.

Try it yourself

1. Add a third facet named topByRating that uses $sort and $limit to return the top 3 highest-rated products. Confirm all three facets return consistent results from the same pipeline invocation.
2. Change the $bucket boundaries so one range spans only $1 (e.g. [49, 50]). Insert a product at exactly $49.99. Confirm which bucket it falls into and verify the boundary semantics (inclusive lower, exclusive upper).
3. Use $bucketAuto with buckets: 4 instead of manual boundaries. Compare the auto-generated boundaries to your manual ones. Note which approach produces more even distribution for your dataset.

References

• $facet — MongoDB docs
• $bucket — MongoDB docs