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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

Sharding administration and monitoring

Sharded MongoDB environments have some unique challenges and limitations compared to single-server or replica-set deployments. In this section, we will explore how MongoDB balances our data across shards using chunks and how we can tweak them if we need to. Together, we will explore some of sharding’s design limitations.

Balancing data – how to track and keep our data balanced

One of the advantages of sharding in MongoDB is that it is mostly transparent to the application and requires minimal administration and operational effort.

One of the core tasks that MongoDB needs to perform continuously is balancing data between shards. No matter whether we implement range-based or hash-based sharding, MongoDB will need to calculate bounds for the hashed field to be able to figure out which shard to direct every new document insert or update toward. As our data grows, these bounds may need to get readjusted to avoid having a hot...

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