MongoDB 4 Quick Start Guide: Learn the Skills You Need to Work With the World's Most Popular NoSQL Database by Doug Bierer

Author:Doug Bierer [Doug Bierer]
Language: eng
Format: epub
Tags: COM021000 - COMPUTERS / Databases / General, COM018000 - COMPUTERS / Data Processing, COM021030 - COMPUTERS / Databases / Data Mining
ISBN: 9781789343533
Google: DxzXvAEACAAJ
Publisher: Packt Publishing
Published: 2018-09-28T23:27:39.993110+00:00

An overview of aggregation

Before diving into the specifics, it's important to lay some groundwork. The first question which comes to mind is, What is aggregation? That question would be logically followed by, Why use it?

What is aggregation?

The main purpose of aggregation operations is to refine query results by grouping together field values from multiple documents, and then performing one or more transformations. Aggregation in MongoDB can be as simple as presenting the results of a query into a set of one or more fields, or as complex as performing a multistage query, breaking the output into buckets, and performing operations on each result set. A more advanced usage would be to manipulate complex fields within a document. For example, if a document contains an array as one of its fields, an aggregation pipeline could be used to filter the output from this array.

The closest SQL equivalent to MongoDB aggregation would be the LIMIT, GROUP BY, and ORDER BY clauses, and the SQL functions AVG(), SUM() , COUNT(), and so on. Even JOIN and subselects could be construed as a form of aggregation in SQL. MongoDB aggregation can accomplish all of these operations and much more!

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