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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

Time series collections

A time series collection is a special type of collection that is used to collect data measurements over a period of time.

For example, time series collection use cases can include storing Internet of Things (IoT) sensor readings, weather readings, and stock price data.

A time series collection needs to be created as such, and we cannot change a collection type into a time series one. Migrating data from a generic purpose collection to a time series one can be done using a custom script or MongoDB’s own Kafka connector for performance and stability.

To create a time series collection, we need to specify the following fields. In this context, a data point might refer to a sensor reading or the stock price at a specific point in time:

  • timeField: This field is mandatory and is the field that stores the timestamp of the data point. It must be a Date() object.
  • metaField: This field is optional and is used to store metadata for the data...
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