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)
Section 1: Essentials
Section 2: Building a Database-Driven Web Application
Section 3: Digging Deeper
Section 4: Replication, Sharding, and Security in a Financial Environment
Working with Complex Documents Across Collections

Mongo shell stats() methods

The most readily available monitoring command is the stats() shell method, available at both the database and collection levels. At the database level, this shell method gives important information such as the number of collections and indexes, as well as information on the average document size, average file size, and information on the amount of filesystem storage used.

Here is an example of output from db.stats() using the sweetscomplete database:

Information given by db.<COLLECTION>.stats() (substitute the name of the collection in place of <COLLECTION>), a wrapper for the collStats database command, easily produces 10 times the amount of information as db.stats(). The output from db.<COLLECTION>.stats() gives the following general information:

Output key Data type Notes
ns string Shows the namespace of the collection. The namespace is a string that includes the database and collection, separated...