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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

Chapter 1: MongoDB Aggregations Explained

Part 1: Guiding Tips and Principles

Chapter 2: Optimizing Pipelines for Productivity

Chapter 3: Optimizing Pipelines for Performance

Chapter 4: Harnessing the Power of Expressions

Chapter 5: Optimizing Pipelines for Sharded Clusters

Part 2: Aggregations by Example

Chapter 6: Foundational Examples: Filtering, Grouping, and Unwinding

Chapter 7: Joining Data Examples

Chapter 8: Fixing and Generating Data Examples

Chapter 9: Trend Analysis Examples

Chapter 10: Securing Data Examples

Chapter 11: Time-Series Examples

Chapter 12: Array Manipulation Examples

Chapter 13: Full-Text Search Examples

Afterword

Index

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Appendix

Summary

In this chapter, you learned techniques for solving the two common scenarios for joining data (one-to-one and one-to-many joins). You also looked at how to deal with multiple fields on each side of the join.

In the next chapter, you will explore how to address situations where the data quality in a collection is suboptimal, such as containing incorrect data types or incomplete fields, and provide solutions for rectifying these issues.

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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