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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
Author Profile Icon Alex Giamas
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

Elevating operations

When connecting to our production MongoDB servers, we want to make sure that our operations are as lightweight as possible (and are certainly non-destructive) and do not alter the database state in any sense.

Two useful utilities that we can chain to our queries are shown here:

> db.collection.find(query).maxTimeMS(999)

Our query instance will only take up to 999 milliseconds (ms), and will then return an exceeded time limit error, as follows:

> db.collection.find(query).maxScan(1000)

Our query instance will examine 1000 documents at the most, in order to find results and then return (no error raised).

Whenever we can, we should bind our queries by time or document result size to avoid running unexpectedly long queries that may affect our production database. A common reason for accessing our production database is troubleshooting degraded cluster performance. This can be investigated via cloud monitoring tools, as we described in previous...

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