Book Image

Mastering MongoDB 3.x

By : Alex Giamas
Book Image

Mastering MongoDB 3.x

By: Alex Giamas

Overview of this book

MongoDB has grown to become the de facto NoSQL database with millions of users—from small startups to Fortune 500 companies. Addressing the limitations of SQL schema-based databases, MongoDB pioneered a shift of focus for DevOps and offered sharding and replication maintainable by DevOps teams. The book is based on MongoDB 3.x and covers topics ranging from database querying using the shell, built in drivers, and popular ODM mappers to more advanced topics such as sharding, high availability, and integration with big data sources. You will get an overview of MongoDB and how to play to its strengths, with relevant use cases. After that, you will learn how to query MongoDB effectively and make use of indexes as much as possible. The next part deals with the administration of MongoDB installations on-premise or in the cloud. We deal with database internals in the next section, explaining storage systems and how they can affect performance. The last section of this book deals with replication and MongoDB scaling, along with integration with heterogeneous data sources. By the end this book, you will be equipped with all the required industry skills and knowledge to become a certified MongoDB developer and administrator.
Table of Contents (13 chapters)

Why aggregation?

Aggregation framework was introduced by MongoDB in version 2.2 (2.1 in development branch). It serves as an alternative to both the MapReduce framework and also querying the database directly.

Using the aggregation framework, we can perform group by operations in the server. Thus we can project only the fields that are needed in the result set. Using the $match and $project operators, we can reduce the amount of data passed through the pipeline, resulting in faster data processing.

Self-joins, that is, joining data within the same collection, can also be performed using the aggregation framework as we will see in our use case.

When comparing the aggregation framework to the queries available via the shell or various other drivers, there is a use case for both.

For selection and projection queries, it's almost always better to use simple queries as the complexity...