MongoDB Overview

• Origin, design goals
• Key features
• Production use cases and sample applications
• Import sample data sets

Working with documents

• Origin, design goals
• Documents and data types
• CRUD (inserts, queries, updates and atomic modifier, and deletes)

Schema Design

• Schema comparisons: MongoDB vs. RDBMS
• Normalizing / De-normalizing
• Common schema scenarios (one-many, many-many, lists, trees, etc.)
• Import sample data sets

Performance Tuning I — Indexing and Query Optimization

• Index
• Understanding your query execution plan

GridFS for managing large binary objects

Aggregation

• Built-in functions (count, group, distinct)
• Map-reduce

Replication and Durability

• Master-slave replication
• Replica sets
• Using write concern for durability

Auto-Sharding

• When does sharding make sense?
• How does sharding work?
• Setting up a MongoDB shard cluster?
  • Choosing a shard key and indexes
  • Performance and use-case considerations
• Administering a sharded cluster

Performance Tuning II

• Getting the best performance out of MongoDB
• Hosting MongoDB in the cloud
• Using write concern for durability

Administration and Troubleshooting

Introduction to drivers: (Java/Python/Ruby/PHP/Perl)

• How the drivers and shell communicate with MongoDB
• BSON
• MongoDB Wire Protocol