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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

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 18. Other books you may enjoy Appendix

Strongly typed conversion

It's not uncommon for someone to import data into a MongoDB collection and neglect to apply strong typing for the date, number, and boolean fields and store them as strings. This situation is likely to cause friction for subsequent users of the data. This example will show you how to restore these fields to their proper types.

Scenario

A third party has imported a set of retail orders into a MongoDB collection but with all data typing lost (they have stored all field values as strings). You want to reestablish correct typing for all the documents and copy them into a new cleaned collection. You can incorporate such transformation logic in the aggregation pipeline because you know each field's type in the original record structure.

Note

Unlike most examples in this book, in this example, the aggregation pipeline writes its output to a collection rather than streaming the results back to the calling application.

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