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

MongoDB persistence strategy

MongoDB saves data in memory-mapped files so that data access is faster than direct disk I/O. When some document is saved, it is written quickly to the memory and persisted to the disk lazily, usually after every 60 seconds. This ensures that we have read-and-write access to databases that is almost as fast as memory.

Let's first study the format in which data is saved in MongoDB.

Binary JSON (BSON)

MongoDB uses the JSON format for storing information. As we have seen before, a typical MongoDB document has the following structure:

  "_id" : ObjectId("5143678345db7ca255000001"),
  "address" : {
    "_id" : ObjectId("514367f445db7ca255000003"),
    "city" : "London",
    "country" : "UK",
    "street" : "Picadilly Circus",
    "zip" : 123,
    "zipcode" : "123"
  "language" : "Hindi",
  "last_name" : "Nutter",
  "name" : "Charles"

However, that's not how it's stored on the disk. This is because it would be very inefficient to store information in the raw JSON...