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Practical MongoDB Aggregations

You're reading from Practical MongoDB Aggregations The official guide to developing optimal aggregation pipelines with MongoDB 7.0

Product type Paperback

Published in Sep 2023

Publisher Packt

ISBN-13 9781835080641

Length 312 pages

Edition 1st Edition

Languages

JavaScript

Tools

MongoDB

Concepts

Database Programming

Author (1):

Paul Done

View More author details

Table of Contents (20) Chapters

Preface

1. Chapter 1: MongoDB Aggregations Explained

2. Part 1: Guiding Tips and Principles FREE CHAPTER

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

Why subscribe?

18. Other books you may enjoy

Appendix

Summary

In this chapter, you explored examples of using time-series windowing aggregations to compute summaries and trends for industrial IoT devices.

In the next chapter, you will learn how to process and manipulate array fields contained in documents without having to unwind and regroup the content of each array.

The rest of the chapter is locked

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Authors (1)

Paul Done

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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