Mastering MongoDB 6.x: Expert techniques to run high-volume and fault-tolerant database solutions using MongoDB 6.x, 3rd Edition [3 ed.] 1803243864, 9781803243863

Table of contents :
Cover
Title Page
Copyright and Credits
Dedication
Contributors
Table of Contents
Preface
Part 1 – Basic MongoDB – Design Goals and Architecture
Chapter 1: MongoDB – A Database for the Modern Web
Technical requirements
The evolution of SQL and NoSQL
The evolution of MongoDB
MongoDB for SQL developers
MongoDB for NoSQL developers
MongoDB’s key characteristics and use cases
Key characteristics
Use cases for MongoDB
MongoDB criticism
MongoDB configuration and best practices
Operational best practices
Schema design best practices
Best practices for write durability
Best practices for replication
Best practices for sharding
Best practices for security
Best practices for AWS
Reference documentation and further reading
Summary
Chapter 2: Schema Design and Data Modeling
Technical requirements
Relational schema design
MongoDB schema design
Data modeling
Data types
Modeling data for atomic operations
Read isolation and consistency
Modeling relationships
One-to-one
One-to-many and many-to-many
Modeling data for keyword searches
Modeling data for Internet of Things
Connecting to MongoDB
Connecting using Ruby
Connecting using Python
Connecting using PHP
Summary
Part 2 – Querying Effectively
Chapter 3: MongoDB CRUD Operations
Technical requirements
CRUD using the shell
Scripting for the mongo shell
Administration
MapReduce in the mongo shell
Aggregation framework
Securing the shell
Authentication with MongoDB
The new mongosh shell
MongoDB Stable API
Summary
Chapter 4: Auditing
Technical requirements
Auditing and logging differences
Audit setup in MongoDB Enterprise Edition
Audit events and format
Audit filters
Audit guarantee
Audit setup in MongoDB Atlas
JSON audit filter
Audit logging access
Audit case study
MongoDB CLI
Mongo shell and audit logs
Summary
Chapter 5: Advanced Querying
Technical requirements
MongoDB CRUD operations
CRUD using the Ruby driver
CRUD in Mongoid
CRUD using the Python driver
CRUD using PyMODM
CRUD using the PHP driver
CRUD using Doctrine
Update operators
Smart querying
Change streams
Introduction
Queryable encryption
Summary
Chapter 6: Multi-Document ACID Transactions
Technical requirements
Transactions background
Exploring ACID properties
Atomicity
Consistency
Isolation
Durability
When do we need ACID in MongoDB?
Building a digital bank using MongoDB
E-commerce using MongoDB
The best practices and limitations of multi-document ACID transactions
Summary
Chapter 7: Aggregation
Technical requirements
Why aggregation?
Aggregation options
Single-purpose aggregation methods
Aggregation operators
Aggregation pipeline stages
Aggregation pipeline expression operators
Literal expression operator
Miscellaneous operators
Object expression operators
Expression string operators
Text expression operators
Timestamp expression operators
Trigonometry expression operators
Type expression operators
Time series collections
MongoDB views
Limitations
Optimizing aggregation pipelines
Aggregation use case
Summary
Chapter 8: Indexing
Index internals
Index types
Building and managing indexes
Using indexes efficiently
Further reading
Summary
Part 3 – Administration and Data Management
Chapter 9: Monitoring, Backup, and Security
Technical requirements
Monitoring clusters
What should we monitor?
Monitoring memory usage in WiredTiger
Tracking page faults
Working set calculations
Monitoring tools
Cluster backups
Backup options
EC2 backup and restore
Incremental backups
Securing our clusters
Authentication
Role-based access control-based authorization
Network-level security
Auditing security
Special cases
Overview
Summary
Chapter 10: Managing Storage Engines
Pluggable storage engines
WiredTiger
Encrypted at rest
Client-side field-level encryption
In-memory
Other storage engines
Locking in MongoDB
Lock reporting
Lock yield
Commonly used commands and locks
Commands requiring a database lock
Further reading
Summary
Chapter 11: MongoDB Tooling
Technical requirements
Introduction to MongoDB tools
MongoDB Atlas
Setting up a cluster
MongoDB Atlas Search
MongoDB Kubernetes Operator
An introduction to Kubernetes
Enterprise Kubernetes Operator
MongoDB Atlas Serverless
MongoDB Realm
Realm Sync
Realm Sync data model
Realm Sync mode
Realm Application Services
MongoDB Charts
MongoDB Compass
MongoDB Connector for Business Intelligence
MongoDB Cloud Manager
MongoDB Ops Manager
Summary
Chapter 12: Harnessing Big Data with MongoDB
Technical requirements
What is big data?
The big data landscape
Message queuing systems
Data warehousing
MongoDB as a data warehouse
Big data use case with servers on-premises
Setting up Kafka 
Setting up Hadoop
Using a Hadoop-to-MongoDB pipeline
Setting up a Spark connection to MongoDB
MongoDB Atlas Data Lake
Summary
Further reading
Part 4 – Scaling and High Availability
Chapter 13: Mastering Replication
Technical requirements
Replication
Logical or physical replication
Different high availability types
An architectural overview
How do elections work?
What is the use case for a replica set?
Setting up a replica set
Converting a standalone server into a replica set
Creating a replica set
Read preference
Write concern
Priority settings for replica set members
Production considerations
Connecting to a replica set
Replica set administration
How to perform maintenance on replica sets
Initial sync
Resyncing a member of a replica set
Changing the oplog’s size
Reconfiguring a replica set when we have lost the majority of our servers
Chained replication
Streaming replication
Flow control
Cloud options for a replica set
Amazon DocumentDB
Microsoft Azure Cosmos DB
MongoDB Atlas
Replica set limitations
Summary
Chapter 14: Mastering Sharding
Technical requirements
Why do we need sharding?
Architectural overview
Development, continuous deployment, and staging environments
Planning ahead with sharding
Setting up sharding
Choosing the shard key
Choosing the correct shard key
Sharding administration and monitoring
Balancing data – how to track and keep our data balanced
Chunk administration
Sharding limitations
Querying sharded data
The query router
Hedged reads
Querying using Ruby
Performance comparison with replica sets
Sharding recovery
mongos
mongod
Config server
A shard goes down
The entire cluster goes down
Further reading
Summary
Chapter 15: Fault Tolerance and High Availability
Application design
Schema-less doesn’t mean schema design-less
Design patterns
Design anti-patterns
Read performance optimization
Defensive coding
Elevating operations
Boosting security
Enabling security by default
Isolating our servers
Checklists
Summary
Further reading
Index
About Packt
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