Faceted Aggregation in MongoDB
1. Introduction
Faceted aggregation is a powerful feature in MongoDB that allows you to perform multiple aggregations on a dataset and return results in a structured format. This technique is commonly used in e-commerce applications for product filtering and categorization.
2. Key Concepts
2.1 Aggregation Pipeline
The aggregation pipeline is a framework that allows you to process data records and return computed results. It consists of stages that transform the data as it passes through the pipeline.
2.2 Facets
In the context of faceted aggregation, a facet represents a unique way of grouping and summarizing the data, often used for filtering or categorizing results.
3. Step-by-Step Process
3.1 Sample Data
Consider a collection named products
:
{
"_id": 1,
"name": "Laptop",
"category": "Electronics",
"price": 1200,
"brand": "BrandA"
}
3.2 Using the Aggregation Framework
To perform faceted aggregation:
db.products.aggregate([
{
$facet: {
"categoryCounts": [
{ $group: { _id: "$category", count: { $sum: 1 } } }
],
"brandCounts": [
{ $group: { _id: "$brand", count: { $sum: 1 } } }
]
}
}
])
3.3 Explanation of the Code
The above code performs the following:
- Uses the
$facet
stage to create multiple pipelines. - Groups the products by
category
and counts them. - Groups the products by
brand
and counts them.
4. Best Practices
- Keep your facets simple to enhance performance.
- Limit the number of documents processed in each facet using
$match
before aggregation. - Benchmark your queries to identify performance bottlenecks.
5. FAQ
What is the maximum number of facets I can use?
MongoDB does not impose a strict limit on the number of facets, but performance may degrade with excessive facets.
Can I apply sorting within facets?
Yes, you can apply sorting using the $sort
stage in each facet pipeline.