Mongo DB Training

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DURATION: 4 Days

1. Introduction to MongoDB – Architecture and Installation:

Goal: In this module, you will get an understanding of NoSQL databases, design goals, requirement of NoSQL database/ MongoDB, MongoDB® architecture and introduction to JSON and BSON among

others. This module will also cover the installation of MongoDB® and associated tools.

Skills:

• Understand NoSQL databases and their advantages.
• Learn JSON and BSON.
• Install MongoDB.

Objectives: 

After completing this module, you should be able to:

• Differentiate database categories.
• Learn MongoDB design goals.
• List MongoDB tools.
• Describe JSON and BSON.
• Install MongoDB on Windows, Linux, MAC OS etc.
• Setup MongoDB environment.

Topics:

• Understanding the basic concepts of a Database.
• Database categories: What is NoSQL? Why NoSQL? Benefit over RDBMS.
• Types of NoSQL Database, and NoSQL vs. SQL Comparison, ACID & Base Property.
• CAP Theorem, implementing NoSQL and what is MongoDB?.
• Overview of MongoDB, Design Goals for MongoDB Server and Database, MongoDB tools.
• Understanding the following: Collection, Documents and Key/ Values, etc.
• Introduction to JSON and BSON documents.
• Environment setup (live Hands-on) and using various MongoDB tools available in the MongoDB.
• Package.
• Case study discussion.

Hands-on/Demo/Use-case:

• MongoDB Installation

2.Schema Design and Data Modelling:

Goal: In this module, you will learn Schema Design and Data Modelling in MongoDB®, various data

structure and tools available to manage Data Model in MongoDB.

Skills:

• Understand Data Modelling Schemas
• Design Data Model relationships and tree structures
• Apply Data Modelling in various real-time contexts

Objectives: 

After completing this module, you should be able to:

• Understand different concepts of data modelling in MongoDB®.
• Understand different types of data model.
• Understand the challenges of designing a data model in MongoDB®.
• Apply the knowledge of a real-world use case.

Topics:

• Data Modelling Concepts.
• Why Data Modelling? Data Modelling Approach.
• Analogy between RDBMS & MongoDB Data Model, MongoDB Data Model (Embedding & Linking).
• Challenges for Data Modelling in MongoDB.
• Data Model Examples and Patterns.
• Model Relationships between Documents.
• Model Tree Structures.
• Model Specific Application Contexts.
• Use Case discussion of Data modelling.

Hands-on/Demo/Use-case:

• HR Data Modelling in RDBMS

3.CRUD Operations:

Goal: In this module, you will get an understanding of CRUD Operations and their functional usage. You will learn how to perform read/write operations with CRUD.

Skills:

• Insert, query, update, and delete documents.
• Perform distributed read/write operations.
• Perform query optimization.

Objectives: 

After completing this module, you should be able to:

• Understand MongoDB’s development and production architecture.
• Understand read and write concepts of MongoDB.
• Understand how Journaling works.
• Use Mongo shell for CRUD operations.
• Understand different MongoDB® data types.

Topics:

• MongoDB Development Architecture.
• MongoDB Production Architecture.
• MongoDB CRUD Introduction, MongoDB CRUD Concepts.
• MongoDB CRUD Concerns (Read & Write Operations) –.
• Concern Levels, Journaling, etc.
• Cursor Query Optimizations, Query Behavior in MongoDB.
• Distributed Read & Write Queries.
• MongoDB Datatypes.
• MongoDB CRUD Syntax & Queries (Live Hands on).

Hands-on/Demo/Use-case:

• MongoDB CRUD Operation

4. Indexing and Aggregation Framework:

Goal: In this module, you will learn the Indexing and Aggregation Framework in MongoDB®.

Skills:

• Create multiple types of Indexes.
• Manage indexes and indexing strategies.
• Work with Geospatial indexes.
• Use MapReduce framework.

Objectives:

After completing this module, you should be able to:

• Use various type of indexes in MongoDB®.
• Use hint, explain plan of a query.
• Work with Geospatial indexes.
• Work with Aggregation Pipeline in MongoDB®.
• Use MapReduce framework.

Topics:

• Index Introduction, Index Concepts, Index Types, Index Properties.
• Index Creation and Indexing Reference.
• Introduction to Aggregation.
• Approach to Aggregation.
• Types of Aggregation (Pipeline, MapReduce & Single Purpose).
• Performance Tuning.

Hands-on/Demo/Use-case:

• Work with Aggregations.

5. MongoDB Administration:

Goal: In this module you will learn MongoDB® administrative activities such as Health Check, Backup, Recovery, Data Import/Export, Performance tuning, etc.

Skills:

• Administer database health, query volume, recovery goals.
• Determine performance characteristics.

Objectives:

After completing this module, you should be able to:

• Take database backup and restore MongoDB®.
• Export and import data from/ to a MongoDB® instance.
• Check server status and DB status.
• Monitor various resource utilization of a mongod instance.
• Understand various optimization strategies.
• Create capped collection.
• Use TTL in MongoDB®.

Topics:

• Administration concepts in MongoDB.
• Monitoring issues related to Database.
• Monitoring at Server, Database, Collection level, and various Monitoring tools related to MongoDB.
• Database Profiling, Locks, Memory Usage, No of connections, page fault etc.
• Backup and Recovery Methods for MongoDB.
• Export and Import of Data to and from MongoDB.
• Run time configuration of MongoDB.
• Production notes/ best practices.
• Data Managements in MongoDB (Capped Collections/ Expired data from TTL), Hands on.
• Administrative Tasks.

Hands-on/Demo/Use-case:

• Import and Export MongoDB® Data.