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Practical MongoDB Aggregations

Practical MongoDB Aggregations

By : Paul Done
5 (17)
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Practical MongoDB Aggregations

Practical MongoDB Aggregations

5 (17)
By: Paul Done

Overview of this book

Officially endorsed by MongoDB, Inc., Practical MongoDB Aggregations helps you unlock the full potential of the MongoDB aggregation framework, including the latest features of MongoDB 7.0. This book provides practical, easy-to-digest principles and approaches for increasing your effectiveness in developing aggregation pipelines, supported by examples for building pipelines to solve complex data manipulation and analytical tasks. This book is customized for developers, architects, data analysts, data engineers, and data scientists with some familiarity with the aggregation framework. It begins by explaining the framework's architecture and then shows you how to build pipelines optimized for productivity and scale. Given the critical role arrays play in MongoDB's document model, the book delves into best practices for optimally manipulating arrays. The latter part of the book equips you with examples to solve common data processing challenges so you can apply the lessons you've learned to practical situations. By the end of this MongoDB book, you’ll have learned how to utilize the MongoDB aggregation framework to streamline your data analysis and manipulation processes effectively.
Table of Contents (20 chapters)
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2
Part 1: Guiding Tips and Principles
7
Part 2: Aggregations by Example
16
Afterword

What do expressions produce?

An expression can be an operator (e.g., {$concat: ...}), a variable (e.g., "$$ROOT"), or a field path (e.g., "$address"). In all these cases, an expression is just something that dynamically populates and returns a new element, which can be one of the following types:

  • Number (including integer, long, float, double, and decimal128)
  • String (UTF-8)
  • Boolean
  • DateTime (UTC)
  • Array
  • Object

However, a specific expression can restrict you to returning just one or a few of these types. For example, the {$concat: ...} operator, which combines multiple strings, can only produce a string data type (or null). The "$$ROOT" variable can only return an object that refers to the root document currently being processed in the pipeline stage.

A field path (e.g., "$address") is different and can return an element of any data type, depending on what the field refers to in the current input document....

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