Book Image

Mastering MongoDB 7.0 - Fourth Edition

By : Marko Aleksendrić, Arek Borucki, Leandro Domingues, Malak Abu Hammad, Elie Hannouch, Rajesh Nair, Rachelle Palmer
Book Image

Mastering MongoDB 7.0 - Fourth Edition

By: Marko Aleksendrić, Arek Borucki, Leandro Domingues, Malak Abu Hammad, Elie Hannouch, Rajesh Nair, Rachelle Palmer

Overview of this book

Mastering MongoDB 7.0 explores the latest version of MongoDB, an exceptional NoSQL database solution that aligns with the needs of modern web applications. This book starts with an informative overview of MongoDB’s architecture and developer tools, guiding you through the process of connecting to databases seamlessly. This MongoDB book explores advanced queries in detail, including aggregation pipelines and multi-document ACID transactions. It delves into the capabilities of the MongoDB Atlas developer data platform and the latest features, such as Atlas Vector Search, and their role in AI applications, enabling developers to build applications with the scalability and performance that today’s organizations need. It also covers the creation of resilient search functionality using MongoDB Atlas Search. Mastering MongoDB 7.0’s deep coverage of advanced techniques encompasses everything from role-based access control (RBAC) to user management, auditing practices, and encryption across data, network, and storage layers. By the end of this book, you’ll have developed the skills necessary to create efficient, secure, and high-performing applications using MongoDB. You’ll have the confidence to undertake complex queries, integrate robust applications, and ensure data security to overcome modern data challenges.
Table of Contents (20 chapters)
4
Chapter 4: Connecting to MongoDB

Aggregation

Aggregations in MongoDB are operations consisting of several steps that process multiple documents and return computed results. Aggregations are built around the concept of pipelines, through which data flows are gradually processed. In a pipeline, the output from the current processing unit is fed as input to the next unit (similar to chaining commands in Linux or a data-wrangling script in Python). In a pipeline, at each stage, a set of documents is fed to the processing unit's input and the output is fed to the following unit. This process ultimately provides solutions to potentially complex problems by breaking them down into smaller and simpler stages.

In this chapter, you will dive deeper into some of the more interesting and useful features of the MongoDB aggregation framework.

This chapter will cover the following topics:

  • The purpose of the MongoDB aggregation framework
  • Principles of aggregation and aggregation stages
  • Basic aggregation...