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Mastering MongoDB 6.x

You're reading from   Mastering MongoDB 6.x Expert techniques to run high-volume and fault-tolerant database solutions using MongoDB 6.x

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Product type Paperback
Published in Aug 2022
Publisher Packt
ISBN-13 9781803243863
Length 460 pages
Edition 3rd Edition
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Author (1):
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Alex Giamas Alex Giamas
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Alex Giamas
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Table of Contents (22) Chapters Close

Preface 1. Part 1 – Basic MongoDB – Design Goals and Architecture
2. Chapter 1: MongoDB – A Database for the Modern Web FREE CHAPTER 3. Chapter 2: Schema Design and Data Modeling 4. Part 2 – Querying Effectively
5. Chapter 3: MongoDB CRUD Operations 6. Chapter 4: Auditing 7. Chapter 5: Advanced Querying 8. Chapter 6: Multi-Document ACID Transactions 9. Chapter 7: Aggregation 10. Chapter 8: Indexing 11. Part 3 – Administration and Data Management
12. Chapter 9: Monitoring, Backup, and Security 13. Chapter 10: Managing Storage Engines 14. Chapter 11: MongoDB Tooling 15. Chapter 12: Harnessing Big Data with MongoDB 16. Part 4 – Scaling and High Availability
17. Chapter 13: Mastering Replication 18. Chapter 14: Mastering Sharding 19. Chapter 15: Fault Tolerance and High Availability 20. Index 21. Other Books You May Enjoy

Why aggregation?

The aggregation framework was introduced by MongoDB in version 2.2 (version 2.1 in the development branch). It serves as an alternative to both the MapReduce framework, which is deprecated as of version 5.0, and querying the database directly.

Using the aggregation framework, we can perform GROUP BY operations in the server. Therefore, we can project only the fields that are needed in the result set. Using the $match and $project operators, we can reduce the amount of data passed through the pipeline, resulting in faster data processing.

Self-joins—that is, joining data within the same collection—can also be performed using the aggregation framework, as we will see in our use case.

When comparing the aggregation framework to simply using the queries available via the shell or various other drivers, it is important to remember that there is a use case for both.

For selection and projection queries, it’s almost always better to use...

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