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)

Limitations

The aggregation pipeline can output results in three distinct ways:

  • Inline as a document containing the result set
  • In a collection
  • Returning a cursor to the result set

Inline results are subject to the BSON maximum document size of 16 MB, meaning that we should use this only if our final result is of fixed size. An example of this would be outputting the ObjectIds of the top five most ordered items from an e-commerce site.

A contrary example to that would be outputting the top 1,000 ordered items, along with the product information, including the description and other fields of variable size.

Outputting results into a collection is the preferred solution if we want to perform further processing of data. We can either output into a new collection or replace the contents of an existing collection. The aggregation output results will only be visible once the aggregation...