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Practical MongoDB Aggregations

Practical MongoDB Aggregations

By : Paul Done
5 (17)
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Practical MongoDB Aggregations

Practical MongoDB Aggregations

5 (17)
By: Paul Done

Overview of this book

Officially endorsed by MongoDB, Inc., Practical MongoDB Aggregations helps you unlock the full potential of the MongoDB aggregation framework, including the latest features of MongoDB 7.0. This book provides practical, easy-to-digest principles and approaches for increasing your effectiveness in developing aggregation pipelines, supported by examples for building pipelines to solve complex data manipulation and analytical tasks. This book is customized for developers, architects, data analysts, data engineers, and data scientists with some familiarity with the aggregation framework. It begins by explaining the framework's architecture and then shows you how to build pipelines optimized for productivity and scale. Given the critical role arrays play in MongoDB's document model, the book delves into best practices for optimally manipulating arrays. The latter part of the book equips you with examples to solve common data processing challenges so you can apply the lessons you've learned to practical situations. By the end of this MongoDB book, you’ll have learned how to utilize the MongoDB aggregation framework to streamline your data analysis and manipulation processes effectively.
Table of Contents (20 chapters)
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2
Part 1: Guiding Tips and Principles
7
Part 2: Aggregations by Example
16
Afterword

Unpack arrays and group differently

You applied filters and groups to whole documents in the previous two examples. In this example, you will work with an array field contained in each document, unraveling each array's contents to enable you to subsequently group the resulting raw data in a way that helps you produce a critical business summary report.

Scenario

You want to generate a retail report to list the total value and quantity of expensive products sold (valued over 15 dollars). The source data is a list of shop orders, where each order contains the set of products purchased as part of the order.

Populating the sample data

Drop any old version of the database (if it exists) and then populate a new orders collection where each document contains an array of products purchased. Each order document contains an order ID plus a list of products purchased as part of the order, including each product's ID, name, and price:

db = db.getSiblingDB("book-unpack...

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