MongoDB Recipes: With Data Modeling and Query Building Strategies
Subhashini / Ganesan Chellappan
Résumé
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. You'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 For Developers and professionals who work with MongoDB.
Chapter 1: MongoDB Features and Installation
Chapter Goal: In this chapter, you will learn NoSQL databases, CAP theorem, MongoDB Features and MongoDB tools. This chapter will also cover installation of MongoDB and its associated tools.
Sub Topics:
NoSQL Databases and Categories
CAP Theorem
MongoDB Features
MongoDB Tools
Describe JSON and BSON
Installing MongoDB on Windows, Linux
MongoDB Terms
MongoDB Data Types
Chapter 2: CRUD Operations
Chapter Goal: In this chapter, you will learn how to perform CRUD operations with MongoDB. This chapter also help you to understand how to query embedded documents and arrays.
Sub Topics:
Basic CRUD operations
Query Embedded Documents
Query Arrays
Bulk Write Operations
Chapter 3: Data Modelling
Chapter Goal: In this chapter, you will learn schema design and various data modelling patterns in MongoDB.
Sub Topics:
Data Modelling Concepts
Data Model Patterns
Model Relationship between documents
Model Tree Structures
Chapter 4: Indexing and Aggregation Framework
Chapter Goal: In this chapter, you will learn indexes types and Aggregation Framework in MongoDB.
Sub Topics:
Introduction to indexes
Index Types
Creating Indexes
Introduction to Aggregation Framework
Aggregation Framework Types
Chapter 5: MongoDB Replication and Sharding
Chapter Goal: In this chapter, you will learn the replication set up and sharding set up.
Sub Topics:
Replication Concepts
Master Slave Replication
Replication Setup
Introduction to Sharding and concepts
Shard Setup
Types of Sharding
Chapter 6: MongoDB Transaction
Chapter Goal: In this chapter, you will learn transactions in MongoDB.
Sub Topics:
Atomicity
Multi-Document Transaction
Concurrency Control
Chapter 7: MongoDB Administration
Chapter Goal: In this chapter, you will learn Database Profiler, MongoDB Backup Methods and Monitoring MongoDB.
Sub Topics:
Database Profiler
MongoDB Backup Methods
Monitoring MongoDB
Chapter 8: MongoDB Security
Chapter Goal: In this chapter, you will learn security aspects of MongoDB.
Sub Topics:
Creating Users
Creating and Assigning custom roles
Authenticating Server
Dharanitharan Ganesan is an MBA in Technology management with high level of exposure and experience in big data - Apache Hadoop, Apache Spark and various Hadoop ecosystem components. He has a proven track record of improving efficiency and productivity through the automation of various routine and administrative functions in business intelligence and big data technologies. His areas of interest and expertise are centered on machine learning algorithms, Blockchain in Bigdata, statistical modelling and predictive analytics.
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Apress |
| Auteur(s) | Subhashini / Ganesan Chellappan |
| Parution | 01/01/2020 |
| Nb. de pages | 247 |
| EAN13 | 9781484248904 |
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