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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 is Atlas Search?

Atlas Search makes adding fast relevance-based full-text search to your applications easy. Atlas Search deploys an Apache Lucene index alongside your database, automatically handling data and schema synchronization between the source collection and this new search index. Atlas Search provides the following features, all backed by support for multiple language analyzers:

  • Fuzzy matching
  • Autocomplete
  • Fast facets and counts
  • Highlighting
  • Relevance scoring
  • Geospatial queries
  • Synonyms

You reduce your cognitive load by invoking searches via the regular MongoDB drivers and aggregations API rather than a third-party Lucene API.

With the Atlas platform's integration of a database, search engine, and synchronization pipeline into a single, unified, and fully managed service, you can quickly build search features into your applications. Consequently these ease of use and functionality advantages mean you should use Atlas Search...

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