Book Image

Learning Mongoid

By : Gautam Rege
Book Image

Learning Mongoid

By: Gautam Rege

Overview of this book

Mongoid helps you to leverage the power of schema-less and efficient document-based design, dynamic queries, and atomic modifier operations. Mongoid eases the work of Ruby developers while they are working on complex frameworks. Starting with why and how you should use Mongoid, this book covers the various components of Mongoid. It then delves deeper into the detail of queries and relations, and you will learn some tips and tricks on improving performance. With this book, you will be able to build robust and large-scale web applications with Mongoid and Rails. Starting with the basics, this book introduces you to components such as moped and origin, and how information is managed, learn about the various datatypes, embedded documents, arrays, and hashes. You will learn how a document is stored and manipulated with callbacks, validations, and even atomic updates. This book will then show you the querying mechanism in detail, right from simple to complex queries, and even explains eager loading, lazy evaluation, and chaining of queries. Finally, this book will explain the importance of performance tuning and how to use the right indexes. It also explains MapReduce and the Aggregation Framework.
Table of Contents (14 chapters)
Learning Mongoid
About the Author
About the Reviewers

The aggregation framework

The aggregation framework of MongoDB was introduced from MongoDB v2.0. It gives us similar functionality, such as the GROUP BY in SQL. This could be achieved easily by using MapReduce, but the aggregation is simpler!

Mongoid currently provides only the following basic aggregations: :count, :min, :max, :sum, and :avg.

So, to get a count of all the books use the following code:

irb> Book.count
=> 12

irb> Book.avg(:reviews_count)
 => 1.3333333333333333

The aggregation framework will be discussed in detail in the next chapter. In short, it uses an pipeline that streams output from one operation as the input of the next operation in the pipeline (similar to the | operator on the Unix shell). Though Mongoid supports the basic aggregations, we can also define our own complex aggregation pipelines. However, the aggregate method is not directly available on the models (as yet). Instead, we need to invoke it on the collection. Let's see an example that shows how...