Book Image

MongoDB Fundamentals

By : Amit Phaltankar, Juned Ahsan, Michael Harrison, Liviu Nedov
Book Image

MongoDB Fundamentals

By: Amit Phaltankar, Juned Ahsan, Michael Harrison, Liviu Nedov

Overview of this book

MongoDB is one of the most popular database technologies for handling large collections of data. This book will help MongoDB beginners develop the knowledge and skills to create databases and process data efficiently. Unlike other MongoDB books, MongoDB Fundamentals dives into cloud computing from the very start – showing you how to get started with Atlas in the first chapter. You will discover how to modify existing data, add new data into a database, and handle complex queries by creating aggregation pipelines. As you progress, you'll learn about the MongoDB replication architecture and configure a simple cluster. You will also get to grips with user authentication, as well as techniques for backing up and restoring data. Finally, you'll perform data visualization using MongoDB Charts. You will work on realistic projects that are presented as bitesize exercises and activities, allowing you to challenge yourself in an enjoyable and attainable way. Many of these mini-projects are based around a movie database case study, while the last chapter acts as a final project where you will use MongoDB to solve a real-world problem based on a bike-sharing app. By the end of this book, you'll have the skills and confidence to process large volumes of data and tackle your own projects using MongoDB.
Table of Contents (15 chapters)
Preface

Modify Fields

In the previous sections, we learned that we could replace any document in a MongoDB collection once it has been inserted. During the replace operation, a document in the database will be replaced with a completely new document while keeping the same primary key. The replacement operations are quite useful when it comes to rectifying errors and to incorporating data changes or updates. However, in most cases, updates will affect only one or a few fields of a document. Think about any movie record from the sample_mflix dataset, where most of its fields (such as the title, cast, directors, duration, and so on) may never change. However, over a period of time, the movie may receive new comments, new reviews, and ratings.

The find and replace operation is very useful when all or most fields of a document are modified. But, using it to update only particular fields in the documents will not be easy. To do so, the replacement document you provide will need to have all the...