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Practical MongoDB Aggregations

You're reading from  Practical MongoDB Aggregations

Product type Book
Published in Sep 2023
Publisher Packt
ISBN-13 9781835080641
Pages 312 pages
Edition 1st Edition
Languages
Author (1):
Paul Done Paul Done
Profile icon Paul Done

Table of Contents (20) Chapters

Preface 1. Chapter 1: MongoDB Aggregations Explained 2. Part 1: Guiding Tips and Principles
3. Chapter 2: Optimizing Pipelines for Productivity 4. Chapter 3: Optimizing Pipelines for Performance 5. Chapter 4: Harnessing the Power of Expressions 6. Chapter 5: Optimizing Pipelines for Sharded Clusters 7. Part 2: Aggregations by Example
8. Chapter 6: Foundational Examples: Filtering, Grouping, and Unwinding 9. Chapter 7: Joining Data Examples 10. Chapter 8: Fixing and Generating Data Examples 11. Chapter 9: Trend Analysis Examples 12. Chapter 10: Securing Data Examples 13. Chapter 11: Time-Series Examples 14. Chapter 12: Array Manipulation Examples 15. Chapter 13: Full-Text Search Examples 16. Afterword
17. Index 18. Other books you may enjoy Appendix

Faceted classification

A typical scenario, often seen as a navigation bar on the left-hand side of an e-commerce product search website, is the need to characterize the same data across multiple dimensions or facets. This example will show you how to perform these faceting queries from a single aggregation pipeline.

Scenario

You want to provide faceted search capability on your retail website to enable customers to refine their product search by selecting specific characteristics against the product results listed on the web page. It is beneficial to classify the products by different dimensions, where each dimension, or facet, corresponds to a particular field in a product record (e.g., product rating or product price).

Each facet should be broken down into a separate range so that a customer can select a specific sub-range (e.g., 4-5 stars) for a particular facet (e.g., rating). The aggregation pipeline will analyze the products collection by each facet's field (rating...

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