What this book covers

Chapter 1, MongoDB Aggregations Explained, provides a level-set of what aggregations are and how to use them.

Chapter 2, Optimizing Pipelines for Productivity, helps you to develop composable and adaptable pipelines.

Chapter 3, Optimizing Pipelines for Performance, informs you how to reduce the latency of your aggregations.

Chapter 4, Harnessing the Power of Expressions, helps you leverage the power of expressions for transforming data, especially arrays.

Chapter 5, Optimizing Pipelines for Sharded Clusters, provides considerations for executing your pipelines against large volumes of data.

Chapter 6, Foundational Examples: Filtering, Grouping, and Unwinding, provides examples of common data manipulation patterns used in many aggregation pipelines, which are relatively straightforward to understand and adapt.

Chapter 7, Joining Data Examples, offers guidance on joining together data from different collections.

Chapter 8, Fixing and Generating Data Examples, provides tools and techniques to clean data within a dataset.

Chapter 9, Trend Analysis Examples, showcases the capabilities of the MongoDB aggregation framework in performing advanced data analytics.

Chapter 10, Securing Data Examples, helps you discover ways to use aggregation pipelines to secure the data in a MongoDB database and reduce the risk of a data breach.

Chapter 11, Time-Series Examples, shows examples of how you can use aggregation pipelines to extract insight from time-series data.

Chapter 12, Array Manipulation Examples, shows how to break down array manipulation problems into manageable pieces, streamlining your assembly of solutions.

Chapter 13, Full-Text Search Examples, demonstrates how to build aggregation pipelines that leverage full-text search capabilities in MongoDB Atlas.