Book Image

MongoDB Cookbook - Second Edition - Second Edition

By : Amol Nayak
Book Image

MongoDB Cookbook - Second Edition - Second Edition

By: Amol Nayak

Overview of this book

MongoDB is a high-performance and feature-rich NoSQL database that forms the backbone of the systems that power many different organizations – it’s easy to see why it’s the most popular NoSQL database on the market. Packed with many features that have become essential for many different types of software professionals and incredibly easy to use, this cookbook contains many solutions to the everyday challenges of MongoDB, as well as guidance on effective techniques to extend your skills and capabilities. This book starts with how to initialize the server in three different modes with various configurations. You will then be introduced to programming language drivers in both Java and Python. A new feature in MongoDB 3 is that you can connect to a single node using Python, set to make MongoDB even more popular with anyone working with Python. You will then learn a range of further topics including advanced query operations, monitoring and backup using MMS, as well as some very useful administration recipes including SCRAM-SHA-1 Authentication. Beyond that, you will also find recipes on cloud deployment, including guidance on how to work with Docker containers alongside MongoDB, integrating the database with Hadoop, and tips for improving developer productivity. Created as both an accessible tutorial and an easy to use resource, on hand whenever you need to solve a problem, MongoDB Cookbook will help you handle everything from administration to automation with MongoDB more effectively than ever before.
Table of Contents (17 chapters)
MongoDB Cookbook Second Edition
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Developing using spring-data-mongodb


From a developer's perspective, when a program needs to interact with a MongoDB instance, they need to use the respective client APIs for their specific platforms. The trouble with doing this is that we need to write a lot of boilerplate code and it is not necessarily object-oriented. For instance, we have a class called Person with various attributes such as name, age, address, and so on. The corresponding JSON document shares a similar structure to this person class as follows:

{
  name:"…",
  age:..,
  address:{lineOne:"…", …}
}

However, to store this document, we need to convert the Person class to DBObject, which is a map with key and value pairs. What is really needed is to let us persist this Person class itself as an object in the database without having to convert it to DBObject.

Additionally, some of the operations such as searching by a particular field of a document, saving an entity, deleting an entity, searching by the ID, and so on are pretty...