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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

Group and total

This next section provides an example of the most commonly used pattern for grouping and summarizing data from a collection.

Scenario

You need to generate a report to show what each shop customer purchased in 2020. You will group the individual order records by customer, capturing each customer's first purchase date, the number of orders they made, the total value of all their orders, and a list of their order items sorted by date.

Populating the sample data

To start with, drop any old version of the database (if it exists) and then populate a new orders collection with nine order documents spanning 2019-2021, for three different unique customers. Each order record will contain a customer ID, the date of the order, and the dollar total for the order:

db = db.getSiblingDB("book-group-and-total");db.dropDatabase();
// Create index for an orders collection
db.orders.createIndex({"orderdate": -1});
// Insert records into the orders...

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