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You're reading from  Practical MongoDB Aggregations

Product typeBook
Published inMar 2024
PublisherPackt
ISBN-139781835884362
Edition1st Edition
Tools
MongoDB
Concepts
Database Programming
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Author (1)
Paul Done
Paul Done
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Paul Done

Paul Done is a Field CTO at MongoDB Inc., having been a Solutions Architect for the past decade at MongoDB. He has previously held roles in various software disciplines, including engineering, consulting, and pre-sales, at companies like Oracle, Novell, and BEA Systems. Paul specializes in databases and middleware, focusing on resiliency, scalability, transactions, event processing, and applying evolvable data model approaches. He spent most of the early 2000s building Java EE (J2EE) transactional systems on WebLogic, integrated with relational databases like Oracle RAC and messaging systems like MQ Series.
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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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Practical MongoDB Aggregations
Published in: Mar 2024Publisher: PacktISBN-13: 9781835884362
© 2024 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Paul Done

Paul Done is a Field CTO at MongoDB Inc., having been a Solutions Architect for the past decade at MongoDB. He has previously held roles in various software disciplines, including engineering, consulting, and pre-sales, at companies like Oracle, Novell, and BEA Systems. Paul specializes in databases and middleware, focusing on resiliency, scalability, transactions, event processing, and applying evolvable data model approaches. He spent most of the early 2000s building Java EE (J2EE) transactional systems on WebLogic, integrated with relational databases like Oracle RAC and messaging systems like MQ Series.
Read more about Paul Done

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