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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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Part 1: Guiding Tips and Principles
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Chapter 2: Optimizing Pipelines for Productivity
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Part 2: Aggregations by Example
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Chapter 6: Foundational Examples: Filtering, Grouping, and Unwinding
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Chapter 7: Joining Data Examples
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Chapter 8: Fixing and Generating Data Examples
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Chapter 9: Trend Analysis Examples
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Chapter 10: Securing Data Examples
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Chapter 11: Time-Series Examples
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Chapter 13: Full-Text Search Examples
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Afterword
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Index
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Other books you may enjoy
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Appendix
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A brief summary of MongoDB sharded clusters

In a sharded cluster, you partition a collection of data across multiple shards, where each shard runs on a separate set of host machines. You control how the system distributes the data by defining a shard key rule. Based on the shard key of each document, the system groups subsets of documents together into chunks, where a range of shard key values identifies each chunk. The cluster balances these chunks across its shards.

In addition to holding sharded collections in a database, you may also be storing unsharded collections in the same database. All a database's unsharded collections live on one specific shard in the cluster, designated as the primary shard for the database (not to be confused with a replica set's primary replica). Figure 5.1 shows the relationship between a database's collections and the shards in the cluster.

Figure 5.1: Correlation between a database's collections and...

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