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  • Book Overview & Buying Mastering MongoDB 6.x
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Mastering MongoDB 6.x

Mastering MongoDB 6.x - Third Edition

By : Alex Giamas
4.7 (17)
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Mastering MongoDB 6.x

Mastering MongoDB 6.x

4.7 (17)
By: Alex Giamas

Overview of this book

MongoDB is a leading non-relational database. This book covers all the major features of MongoDB including the latest version 6. MongoDB 6.x adds many new features and expands on existing ones such as aggregation, indexing, replication, sharding and MongoDB Atlas tools. Some of the MongoDB Atlas tools that you will master include Atlas dedicated clusters and Serverless, Atlas Search, Charts, Realm Application Services/Sync, Compass, Cloud Manager and Data Lake. By getting hands-on working with code using realistic use cases, you will master the art of modeling, shaping and querying your data and become the MongoDB oracle for the business. You will focus on broadly used and niche areas such as optimizing queries, configuring large-scale clusters, configuring your cluster for high performance and availability and many more. Later, you will become proficient in auditing, monitoring, and securing your clusters using a structured and organized approach. By the end of this book, you will have grasped all the practical understanding needed to design, develop, administer and scale MongoDB-based database applications both on premises and on the cloud.
Table of Contents (22 chapters)
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1
Part 1 – Basic MongoDB – Design Goals and Architecture
4
Part 2 – Querying Effectively
11
Part 3 – Administration and Data Management
16
Part 4 – Scaling and High Availability

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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Mastering MongoDB 6.x
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