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Practical MongoDB Aggregations

You're reading from  Practical MongoDB Aggregations

Product type Book
Published in Sep 2023
Publisher Packt
ISBN-13 9781835080641
Pages 312 pages
Edition 1st Edition
Languages
Author (1):
Paul Done Paul Done
Profile icon Paul Done
Toc

Table of Contents (20) Chapters close

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 18. Other books you may enjoy Appendix

Filtered top subset

First, you will look at an example that demonstrates how to query a sorted subset of data. As with all subsequent examples, this first example provides the commands you need to populate the dataset in your own MongoDB database and then apply the aggregation pipeline to produce the results shown.

Scenario

You need to query a collection of people to find the three youngest individuals who have a job in engineering, sorted by the youngest person first.

Note

This example is the only one in the book that you can also achieve entirely using the MongoDB Query Language and serves as a helpful comparison between the MongoDB Query Language and aggregation pipelines.

Populating the sample data

To start with, drop any old version of the database (if it exists) and then populate a new persons collection with six person documents. Each person record will contain the person's ID, first name, last name, date of birth, vocation, and address:

db = db.getSiblingDB...
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