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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

Better alternatives for a projection stage

The typical method for specifying fields to include or exclude in the MongoDB aggregation framework has been the $project stage. This was the only way to define which fields to keep or omit for many earlier versions of MongoDB. However, $project comes with a few usability challenges:

  • $project can be confusing and non-intuitive. You can only choose to include fields or exclude fields in a single stage, but not both. However, there is one exception, where you can exclude the _id field and still define other fields to include. This only applies to the _id field and this ambiguity makes $project unintuitive to apply.
  • $project can be verbose and inflexible. If you want to define one new field or revise one field, you will have to name all other fields in the projection to include. If each input record has 100 fields and the pipeline needs to employ a $project stage for the first time, defining these files can become time consuming....

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