MongoDB Data Modeling
Table of Contents
MongoDB Data Modeling
Credits
About the Author
Acknowledgments
About the Reviewers
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Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Errata
Piracy
Questions
1. Introducing Data Modeling
The relationship between MongoDB and NoSQL
Introducing NoSQL (Not Only SQL)
NoSQL databases types
Dynamic schema, scalability, and redundancy
Database design and data modeling
The ANSI-SPARC architecture
The external level
The conceptual level
The internal level
Data modeling
The conceptual model
The logical model
The physical model
Summary
2. Data Modeling with MongoDB
Introducing documents and collections
JSON
BSON
Characteristics of documents
The document size
Names and values for a field in a document
The document primary key
Support collections
The optimistic loop
Designing a document
Working with embedded documents
Working with references
Atomicity
Common document patterns
One-to-one
One-to-many
Many-to-many
Summary
3. Querying Documents
Understanding the read operations
Selecting all documents
Selecting documents using criteria
Comparison operators
Logical operators
Element operators
Evaluation operators
Array operators
Projections
Introducing the write operations
Inserts
Updates
Write concerns
Unacknowledged
Acknowledged
Journaled
Replica acknowledged
Bulk writing documents
Summary
4. Indexing
Indexing documents
Indexing a single field
Indexing more than one field
Indexing multikey fields
Indexing for text search
Creating special indexes
Time to live indexes
Unique indexes
Sparse indexes
Summary
5. Optimizing Queries
Understanding the query plan
Evaluating queries
Covering a query
The query optimizer
Reading from many MongoDB instances
Summary
6. Managing the Data
Operational segregation
Giving priority to read operations
Capped collections
Data self-expiration
Summary
7. Scaling
Scaling out MongoDB with sharding
Choosing the shard key
Basic concerns when choosing a shard key
Scaling a social inbox schema design
Fan out on read
Fan out on write
Fan out on write with buckets
Summary
8. Logging and Real-time Analytics with MongoDB
Log data analysis
Error logs
Access logs
What we are looking for
Measuring the traffic on the web server
Designing the schema
Capturing an event request
A one-document solution
TTL indexes
Sharding
Querying for reports
Summary
Index
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