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Practical MongoDB Aggregations

You're reading from Practical MongoDB Aggregations

Product type Book

Published in Mar 2024

Publisher Packt

ISBN-13 9781835884362

Pages 278 pages

Edition 1st Edition

Languages

Concepts

Database Programming

Author (1):

Paul Done

Table of Contents (20) Chapters

Preface

1. Chapter 1: MongoDB Aggregations Explained

2. Part 1: Guiding Tips and Principles

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

Joining Data Examples

This chapter offers guidance on joining together data from two collections. Contrary to what you may have heard, MongoDB is quite capable of performing these joins. The method of data manipulation will differ depending on whether you're executing a one-to-one or one-to-many join. You will explore solutions for both scenarios.

This chapter will cover the following:

Implementing one-to-one joins
Implementing one-to-many joins
Dealing with multiple fields on each side of the join

The rest of the chapter is locked

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Authors (1)

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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