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๐Ÿ“

MongoDB Recipes: With Data Modeling and Query Building Strategies

โœ Scribed by Subhashini Chellappan, Dharanitharan Ganesan


Publisher
Apress
Year
2020
Tongue
English
Leaves
257
Edition
1st ed.
Category
Library

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No coin nor oath required. For personal study only.

โœฆ Synopsis


Get the most out of MongoDB using a problem-solution approach. This book starts with recipes on the MongoDB query language, including how to query various data structures stored within documents. These self-contained code examples allow you to solve your MongoDB problems without fuss.
MongoDB Recipes describes how to use advanced querying in MongoDB, such as indexing and the aggregation framework. It demonstrates how to use the Compass function, a GUI client interacting with MongoDB, and how to apply data modeling to your MongoDB application. Youโ€™ll see recipes on the latest features of MongoDB 4 allowing you to manage data in an efficient manner using MongoDB.
What You Will Learn

  • Work with the MongoDB document model
  • Design MongoDB schemas
  • Use the MongoDB query language
  • Harness the aggregation framework
  • Create replica sets and sharding in MongoDB

Who This Book Is ForDevelopers and professionals who work with MongoDB.


โœฆ Table of Contents


Front Matter ....Pages i-xvii
MongoDB Features and Installation (Subhashini Chellappan, Dharanitharan Ganesan)....Pages 1-24
MongoDB CRUD Operations (Subhashini Chellappan, Dharanitharan Ganesan)....Pages 25-77
Data Modeling and Aggregation (Subhashini Chellappan, Dharanitharan Ganesan)....Pages 79-104
Indexes (Subhashini Chellappan, Dharanitharan Ganesan)....Pages 105-126
Replication and Sharding (Subhashini Chellappan, Dharanitharan Ganesan)....Pages 127-155
Multidocument Transactions (Subhashini Chellappan, Dharanitharan Ganesan)....Pages 157-171
MongoDB Monitoring and Backup (Subhashini Chellappan, Dharanitharan Ganesan)....Pages 173-213
MongoDB Security (Subhashini Chellappan, Dharanitharan Ganesan)....Pages 215-241
Back Matter ....Pages 243-247

โœฆ Subjects


Computer Science; Big Data; Open Source


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