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MongoDB Developer and Administrator

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Course programme

Course Preview Course Agenda
  • MongoDB Developer and Administrator
    • Lesson 0 - Course Introduction
      • 0.1 Course Introduction
      • 0.2 Table of Contents
      • 0.3 Objectives
      • 0.4 Course Overview
      • 0.5 Value to Professionals and Organizations
      • 0.6 Course Prerequisites
      • 0.7 Lessons Covered
      • 0.8 Conclusion
    • Lesson 1 - Introduction to NoSQL databases
      • 1.1 NoSQL Database Introduction
      • 1.2 Objectives
      • 1.3 What is NoSQL?
      • 1.4 What is NoSQL?(contd.)
      • 1.5 Why NoSQL?
      • 1.6 Difference Between RDBMS and NoSQL Databases
      • 1.7 Benefits of NoSQL
      • 1.8 Benefits of NoSQL (contd.)
      • 1.9 Types of NoSQL
      • 1.10 Key-Value Database
      • 1.11 Key-Value Database (contd.)
      • 1.12 Document Database
      • 1.13 Document Database Example
      • 1.14 Column-Based Database
      • 1.15 Column-Based Database (contd.)
      • 1.16 Column-Based Database (contd.)
      • 1.17 Column-Based Database Example
      • 1.18 Graph Database
      • 1.19 Graph Database (contd.)
      • 1.20 CAP Theorem
      • 1.21 CAP Theorem (contd.)
      • 1.22 Consistency
      • 1.23 Availability
      • 1.24 Partition Tolerance
      • 1.25 Mongo DB as Per CAP
      • 1.26 Quiz
      • 1.27 Summary
      • 1.28 Conclusion
    • Lesson 2 - MongoDB A Database for the Modern Web
      • 2.1 MongoDB-A Database for the Modern Web
      • 2.2 Objectives
      • 2.3 What is MongoDB?
      • 2.4 JSON
      • 2.5 JSON Structure
      • 2.6 BSON
      • 2.7 MongoDB Structure
      • 2.8 Document Store Example
      • 2.9 MongoDB as a Document Database
      • 2.10 Transaction Management in MongoDB
      • 2.11 Easy Scaling
      • 2.12 Scaling Up vs. Scaling Out
      • 2.13 Vertical Scaling
      • 2.14 Horizontal Scaling
      • 2.15 Features of MongoDB
      • 2.16 Secondary Indexes
      • 2.17 Replication
      • 2.18 Replication (contd.)
      • 2.19 Memory Management
      • 2.20 Replica Set
      • 2.21 Auto Sharding
      • 2.22 Aggregation and MapReduce
      • 2.23 Collection and Database
      • 2.24 Schema Design and Modeling
      • 2.25 Reference Data Model
      • 2.26 Reference Data Model Example
      • 2.27 Embedded Data Model
      • 2.28 Embedded Data Model Example
      • 2.29 Data Types
      • 2.30 Data Types (contd.)
      • 2.31 Data Types (contd.)
      • 2.32 Core Servers of MongoDB
      • 2.33 MongoDB's Tools
      • 2.34 Installing MongoDB on Linux
      • 2.35 Installing MongoDB on Linux
      • 2.36 Installing MongoDB on Windows
      • 2.37 Installing MongoDB on Windows
      • 2.38 Starting MongoDB On Linux
      • 2.39 Starting MongoDB On Linux
      • 2.40 Starting MongoDB On Windows
      • 2.41 Starting MongoDB On Windows
      • 2.42 Use Cases
      • 2.43 Use Cases (contd.)
      • 2.44 Quiz
      • 2.45 Summary
      • 2.46 Conclusion
    • Lesson 3 - CRUD Operations in MongoDB
      • 3.1 CRUD Operations in MongoDB
      • 3.2 Objectives
      • 3.3 Data Modification in MongoDB
      • 3.4 Batch Insert in MongoDB
      • 3.5 Ordered Bulk Insert
      • 3.6 Performing Ordered Bulk Insert
      • 3.7 Performing Ordered Bulk Insert
      • 3.8 Unordered Bulk Insert
      • 3.9 Performing Un-ordered Bulk Insert
      • 3.10 Performing Un-ordered Bulk Insert
      • 3.11 Inserts: Internals and Implications
      • 3.12 Performing an Insert Operation
      • 3.13 Performing an Insert Operation
      • 3.14 Retrieving the documents
      • 3.15 Specify Equality Condition
      • 3.16 Retrieving Documents by Find Query
      • 3.17 Retrieving Documents by Find Query
      • 3.18 $in, $or , and “AND” Conditions
      • 3.19 $or Operator
      • 3.20 Specify AND/OR Conditions
      • 3.21 Retrieving Documents by Using FindOne, AND/OR Conditions
      • 3.22 Retrieving Documents by Using FindOne, AND/OR Conditions
      • 3.23 Regular Expression
      • 3.24 Array Exact Match
      • 3.25 Array Projection Operators
      • 3.26 Retrieving Documents for Array Fields
      • 3.27 Retrieving Documents for Array Fields
      • 3.28 $Where Query
      • 3.29 Cursor
      • 3.30 Cursor (contd.)
      • 3.31 Cursor (contd.)
      • 3.32 Retrieving Documents Using Cursor
      • 3.33 Retrieving Documents Using Cursor
      • 3.34 Pagination
      • 3.35 Pagination: Avoiding Larger Skips
      • 3.36 Advance query option
      • 3.37 Update Operation
      • 3.38 Updating Documents in MongoDB
      • 3.39 Updating Documents in MongoDB
      • 3.40 $SET
      • 3.41 Updating Embedded Documents in MongoDB
      • 3.42 Updating Embedded Documents in MongoDB
      • 3.43 Updating Multiple Documents in MongoDB
      • 3.44 Updating Multiple Documents in MongoDB
      • 3.45 $Unset and $inc Modifiers
      • 3.46 $inc modifier to increment and decrement
      • 3.47 $inc modifier to increment and decrement
      • 3.48 Replacing Existing Document with New Document
      • 3.49 Replacing Existing Document with New Document
      • 3.50 $Push and $addToSet
      • 3.51 Positional Array Modification
      • 3.52 Adding Elements into Array Fields
      • 3.53 Adding Elements into Array Fields
      • 3.54 Adding Elements to Array Fields Using AddToSet
      • 3.55 Adding Elements to Array Fields Using AddToSet
      • 3.56 Performing AddToSet
      • 3.57 Performing AddToSet
      • 3.58 Upsert
      • 3.59 Removing Documents
      • 3.60 Performing Upsert and Remove Operation
      • 3.61 Performing Upsert and Remove Operation
      • 3.62 Quiz
      • 3.63 Summary
      • 3.64 Conclusion
    • Lesson 4 - Indexing and Aggregation
      • 4.1 Indexing and Aggregation
      • 4.2 Objectives
      • 4.3 Introduction to Indexing
      • 4.4 Types of Index
      • 4.5 Properties of Index
      • 4.6 Single Field Index
      • 4.7 Single Field Index on Embedded Document
      • 4.8 Compound Indexes
      • 4.9 Index Prefixes
      • 4.10 Sort Order
      • 4.11 Ensure Indexes Fit RAM
      • 4.12 Multi-Key Indexes
      • 4.13 Compound Multi-Key Indexes
      • 4.14 Hashed Indexes
      • 4.15 TTL Indexes
      • 4.16 Unique Indexes
      • 4.17 Sparse Indexes
      • 4.18 Demo—Create Compound, Sparse, and Unique Indexes
      • 4.19 Demo-Create Compound, Sparse, and Unique Indexes
      • 4.20 Text Indexes
      • 4.21 Demo—Create Single Field and Text Index
      • 4.22 Demo—Create Single Field and Text Index
      • 4.23 Text Search
      • 4.24 Index Creation
      • 4.25 Index Creation (contd.)
      • 4.26 Index Creation on Replica Set
      • 4.27 Remove Indexes
      • 4.28 Modify Indexes
      • 4.29 Demo—Drop and Index from a Collection
      • 4.30 Demo—Drop and Index from a Collection
      • 4.31 Rebuild Indexes
      • 4.32 Listing Indexes
      • 4.33 Demo—Retrieve Indexes for a Collection and Database
      • 4.34 Demo—Retrieve Indexes for a Collection and Database
      • 4.35 Measure Index Use
      • 4.36 Demo—Use Mongo Shell Methods to Monitor Indexes
      • 4.37 Demo—Use Mongo Shell Methods to Monitor Indexes
      • 4.38 Control Index Use
      • 4.39 Demo—Use the Explain, $Hint and $Natural Operators to Create Index
      • 4.40 Demo—Use the Explain, $Hint and $Natural Operators to Create Index
      • 4.41 Index Use Reporting
      • 4.42 Geospatial Index
      • 4.43 Demo—Create Geospatial Index
      • 4.44 Demo—Create Geospatial Index
      • 4.45 MongoDB’s Geospatial Query Operators
      • 4.46 Demo—Use Geospatial Index in a Query
      • 4.47 Demo—Use Geospatial Index in a Query
      • 4.48 $GeoWith Operator
      • 4.49 Proximity Queries in MongoDB
      • 4.50 Aggregation
      • 4.51 Aggregation (contd.)
      • 4.52 Pipeline Operators and Indexes
      • 4.53 Aggregate Pipeline Stages
      • 4.54 Aggregate Pipeline Stages (contd.)
      • 4.55 Aggregation Example
      • 4.56 Demo—Use Aggregate Function
      • 4.57 Demo—Use Aggregate Function
      • 4.58 MapReduce
      • 4.59 MapReduce (contd.)
      • 4.60 MapReduce (contd.)
      • 4.61 Demo—Use MapReduce in MongoDB
      • 4.62 Demo—Use MapReduce in MongoDB
      • 4.63 Aggregation Operations
      • 4.64 Demo—Use Distinct and Count Methods
      • 4.65 Demo—Use Distinct and Count Methods
      • 4.66 Aggregation Operations (contd.)
      • 4.67 Demo—Use the Group Function
      • 4.68 Demo—Use the Group Function
      • 4.69 Quiz
      • 4.70 Summary
      • 4.71 Conclusion
    • Lesson 5 - Replication and Sharding
      • 5.1 Replication and Sharding
      • 5.2 Objectives
      • 5.3 Introduction to Replication
      • 5.4 Master-Slave Replication
      • 5.5 Replica Set in MongoDB
      • 5.6 Replica Set in MongoDB (contd.)
      • 5.7 Automatic Failover
      • 5.8 Replica Set Members
      • 5.9 Priority 0 Replica Set Members
      • 5.10 Hidden Replica Set Members
      • 5.11 Delayed Replica Set Members
      • 5.12 Delayed Replica Set Members (contd.)
      • 5.13 Demo—Start a Replica Set
      • 5.14 Demo-Start a Replica Set
      • 5.15 Write Concern
      • 5.16 Write Concern (contd.)
      • 5.17 Write Concern Levels
      • 5.18 Write Concern for a Replica Set
      • 5.19 Modify Default Write Concern
      • 5.20 Read Preference
      • 5.21 Read Preference Modes
      • 5.22 Blocking for Replication
      • 5.23 Tag Set
      • 5.24 Configure Tag Sets for Replica set
      • 5.25 Replica Set Deployment Strategies
      • 5.26 Replica Set Deployment Strategies (contd.)
      • 5.27 Replica Set Deployment Patterns
      • 5.28 Oplog File
      • 5.29 Replication State and Local Database
      • 5.30 Replication Administration
      • 5.31 Demo—Check a Replica Set Status
      • 5.32 Demo—Check a Replica Set Status
      • 5.33 Sharding
      • 5.34 When to Use Sharding?
      • 5.35 What is a Shard?
      • 5.36 What is a Shard Key
      • 5.37 Choosing a Shard Key
      • 5.38 Ideal Shard Key
      • 5.39 Range-Based Shard Key
      • 5.40 Hash-Based Sharding
      • 5.41 Impact of Shard Keys on Cluster Operation
      • 5.42 Production Cluster Architecture
      • 5.43 Config Server Availability
      • 5.44 Production Cluster Deployment
      • 5.45 Deploy a Sharded Cluster
      • 5.46 Add Shards to a Cluster
      • 5.47 Demo—Create a Sharded Cluster
      • 5.48 Demo—Create a Sharded Cluster
      • 5.49 Enable Sharding for Database
      • 5.50 Enable Sharding for Collection
      • 5.51 Enable Sharding for Collection (contd.)
      • 5.52 Maintaining a Balanced Data Distribution
      • 5.53 Splitting
      • 5.54 Chunk Size
      • 5.55 Special Chunk Type
      • 5.56 Shard Balancing
      • 5.57 Shard Balancing (contd.)
      • 5.58 Customized Data Distribution with Tag Aware Sharding
      • 5.59 Tag Aware Sharding
      • 5.60 Add Shard Tags
      • 5.61 Remove Shard Tags
      • 5.62 Quiz
      • 5.63 Summary
      • 5.64 Conclusion
    • Lesson 6 - Developing Java and Node JS Application with MongoDB
      • 6.1 Developing Java and Node JS Application with MongoDB
      • 6.2 Objectives
      • 6.3 Capped Collection
      • 6.4 Capped Collection Creation
      • 6.5 Capped Collection Creation (contd.)
      • 6.6 Demo—Create a Capped Collection in MongoDB
      • 6.7 Demo—Create a Capped Collection in MongoDB
      • 6.8 Capped Collection Restriction
      • 6.9 TTL Collection Features
      • 6.10 Demo—Create TTL Indexes
      • 6.11 Demo—Create TTL Indexes
      • 6.12 GridFS
      • 6.13 GridFS Collection
      • 6.14 Demo—Create GridFS in MongoDB Java Application
      • 6.15 Demo—Create GridFS in MongoDB Java Application
      • 6.16 MongoDB Drivers and Client Libraries
      • 6.17 Develop Java Application with MongoDB
      • 6.18 Connecting to MonogDB from Java Program
      • 6.19 Create Collection From Java Program
      • 6.20 Insert Documents From Java Program
      • 6.21 Insert Documents Using Java Code Example
      • 6.22 Demo—Insert a Document Using Java
      • 6.23 Demo—Insert a Document Using Java
      • 6.24 Retrieve Documents Using Java Code
      • 6.25 Demo—Retrieve Document Using Java
      • 6.26 Demo—Retrieve Document Using Java
      • 6.27 Update Documents Using Java Code
      • 6.28 Demo—Update Document Using Java
      • 6.29 Demo—Update Document Using Java
      • 6.30 Delete Documents Using Java Code
      • 6.31 Demo—Delete Document Using Java
      • 6.32 Demo—Delete Document Using Java
      • 6.33 Store Images Using GridFS API
      • 6.34 Retrieve Images Using GridFS API
      • 6.35 Remove Image Using GridFS API
      • 6.36 Remove Image Using GridFS API (contd..)
      • 6.37 Connection Creation Using Node JS
      • 6.38 Insert Operations Using Node JS
      • 6.39 Insert Operations Using Node JS (contd.)
      • 6.40 Demo—Perform CRUD Operation in Node JS
      • 6.41 Demo—Perform CRUD Operation in Node JS
      • 6.42 Demo—Perform Insert and Retrieve Operations Using Node JS
      • 6.43 Demo—Perform Insert and Retrieve Operations Using Node JS
      • 6.44 Update Operations Using Node JS
      • 6.45 Retrieve Documents Using Node JS
      • 6.46 Using DB Cursor to Retrieve Documents
      • 6.47 Mongoose ODM Module in Node JS
      • 6.48 Defining Schema Using Mongoose
      • 6.49 Defining Schema Using Mongoose (contd.)
      • 6.50 Demo—Use Mongoose to Define Schema
      • 6.51 Demo—Use Mongoose to Define Schema
      • 6.52 Demo—How to Run Node JS Using Mongoose
      • 6.53 Demo—How to Run Node JS Using Mongoose
      • 6.54 Quiz
      • 6.55 Summary
      • 6.56 Conclusion
    • Lesson 7 - Administration of MongoDB Cluster Operations
      • 7.1 Administration of MongoDB Cluster Operations
      • 7.2 Objectives
      • 7.3 Capped Collection
      • 7.4 Capped Collection Creation
      • 7.5 Capped Collection Creation (contd.)
      • 7.6 Demo-Create a Capped Collection in MongoDB
      • 7.7 Demo-Create a Capped Collection in MongoDB
      • 7.8 Capped Collection Restriction
      • 7.9 TTL Collection Features
      • 7.10 Demo-Create TTL Indexes
      • 7.11 Demo-Create TTL Indexes
      • 7.12 GridFS
      • 7.13 GridFS Collection
      • 7.14 Demo-Create GridFS in MongoDB Java Application
      • 7.15 Demo-Create GridFS in MongoDB Java Application
      • 7.16 Memory-Mapped Files
      • 7.17 Journaling Mechanics
      • 7.18 Storage Engines
      • 7.19 MMAPv1 Storage Engine
      • 7.20 WiredTiger Storage Engine
      • 7.21 WiredTiger Compression Support
      • 7.22 Power of 2-Sized Allocations
      • 7.23 No Padding Allocation Strategy
      • 7.24 Diagnosing Performance Issues
      • 7.25 Diagnosing Performance Issues (contd.)
      • 7.26 Diagnosing Performance Issues (contd.)
      • 7.27 Demo-Monitor Performance in MongoDB
      • 7.28 Demo-Monitor Performance in MongoDB
      • 7.29 Optimization Strategies for MongoDB
      • 7.30 Configure Tag Sets for Replica Set
      • 7.31 Optimize Query Performance
      • 7.32 Monitoring Strategies for MongoDB
      • 7.33 MongoDB Utilities
      • 7.34 MongoDB Commands
      • 7.35 MongoDB Management service (MMS)
      • 7.36 Data Backup Strategies in MongoDB
      • 7.37 Copying Underlying Data Files
      • 7.38 Backup with MongoDump
      • 7.39 Fsync and Lock
      • 7.40 MongoDB Ops Manager Backup Software
      • 7.41 Security Strategies in MongoDB
      • 7.42 Authentication Implementation in MongoDB
      • 7.43 Authentication in a Replica set
      • 7.44 Authentication on Sharded Clusters
      • 7.45 Authorization
      • 7.46 End-to-End Auditing for Compliance
      • 7.47 Quiz
      • 7.48 Summary
      • 7.49 Conclusion

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