Book Image

Learn MongoDB 4.x

By : Doug Bierer
Book Image

Learn MongoDB 4.x

By: Doug Bierer

Overview of this book

When it comes to managing a high volume of unstructured and non-relational datasets, MongoDB is the defacto database management system (DBMS) for DBAs and data architects. This updated book includes the latest release and covers every feature in MongoDB 4.x, while helping you get hands-on with building a MongoDB database app. You’ll get to grips with MongoDB 4.x concepts such as indexes, database design, data modeling, authentication, and aggregation. As you progress, you’ll cover tasks such as performing routine operations when developing a dynamic database-driven website. Using examples, you’ll learn how to work with queries and regular database operations. The book will not only guide you through design and implementation, but also help you monitor operations to achieve optimal performance and secure your MongoDB database systems. You’ll also be introduced to advanced techniques such as aggregation, map-reduce, complex queries, and generating ad hoc financial reports on the fly. Later, the book shows you how to work with multiple collections as well as embedded arrays and documents, before finally exploring key topics such as replication, sharding, and security using practical examples. By the end of this book, you’ll be well-versed with MongoDB 4.x and be able to perform development and administrative tasks associated with this NoSQL database.
Table of Contents (22 chapters)
1
Section 1: Essentials
5
Section 2: Building a Database-Driven Web Application
9
Section 3: Digging Deeper
13
Section 4: Replication, Sharding, and Security in a Financial Environment
14
Working with Complex Documents Across Collections

Understanding the mapReduce() method syntax

The primary method that allows you to perform aggregation operations using a JavaScript function is mapReduce(). The generic syntax for the collection method is this:

db.<collection>.mapReduce(<map func>,<reduce func>, \
{query:{},out:"<new collection>"})

The first argument is a JavaScript function representing the map phase. In this phase, you define a JavaScript function that calls emit(), which defines the fields included in the operation. The second argument is a JavaScript function that represents the reduce phase. A typical use for this is to produce some sort of accumulation (for example, sum) on the mapped fields.

The third argument is a JSON object with two properties: query and outquery, as you might have guessed, is a filter that limits documents included in the operation. out is the name of a collection into which the results of the operation...