MongoDB
The most popular database for modern apps
About MongoDB
MongoDB allows your teams to easily organize, use and enrich data – in real time, anywhere.
MongoDB is a cross-platform document-oriented database program. Classified as a NoSQL database program, MongoDB uses JSON-like documents with schemata. MongoDB is developed by MongoDB Inc. and licensed under the Server Side Public License.
- Best way to work with data
- Put data where you need it
- Run anywhere
MongoDB Topics
The following are the things covered under MongoDB.
MongoDB - Data Modelling
Data in MongoDB has a flexible schema.documents in the same collection. They do not need to have the same set of fields or structure, and common fields in a collection’s documents may hold different types of data.
MongoDB - Create Collection
In MongoDB, you don't need to create collection. MongoDB creates collection automatically, when you insert some document.
MongoDB - Deployment
When you are preparing a MongoDB deployment, you should try to understand how your application is going to hold up in production. It’s a good idea to develop a consistent, repeatable approach to managing your deployment environment so that you can minimize any surprises once you’re in production.
MongoDB - Relationships
Relationships in MongoDB represent how various documents are logically related to each other. Relationships can be modeled via Embedded and Referenced approaches. Such relationships can be either 1:1, 1:N, N:1 or N:N.
MongoDB - Atomic Operations
MongoDB does not support multi-document atomic transactions. However, it does provide atomic operations on a single document.
MongoDB - Map Reduce
As per the MongoDB documentation, Map-reduce is a data processing paradigm for condensing large volumes of data into useful aggregated results. MongoDB uses mapReduce command for map-reduce operations.
Course Contents
The following are the course contents offered for mongoDB
- Datastore design considerations
- Relational v/s NoSQL stores
- Entities
- When to use Relational/NoSQL?
- Categories of NoSQL stores
- Examples of NoSQL stores
- MongoDB Administration
- MongoDB Development
- MongoDB Querying
- MongoDB evolution
- Major feature set for versions 1.0 and 1.2
- Version 2
- Version 3
- Version 3+
- MongoDB for SQL developers
- MongoDB for NoSQL developers
- MongoDB key characteristics and use cases
- Key characteristics
- What is the use case for MongoDB?
- MongoDB criticism
- MongoDB configuration and best practices
- Operational best practices
- Schema design best practices
- Best practices for write durability
- Best practices for replication
- Best practices for sharding
- Best practices for security
- Best practices for AWS
- Reference documentation
- MongoDB documentation
- Schema Design and Data Modeling
- Relational schema design
- MongoDB schema design
- Read-write ratio
- Connecting to MongoDB
- Data Formats
- What are Data Formats?
- Difference between Data Formats and Data Structures
- Serializing and de-serializing data
- The JSON Data Format
- BSON Data Format
- Advantages of BSON
- Servers
- Connections
- Databases
- Collections
- Documents
- CRUD
- Indexes
- Query Expression Objects
- Query Options
- Cursors
- Mongo Query Language
- Dot Notation
- Full Text Search
- Basic Data Types
- Dates
- Arrays
- _id and ObjectIds
- Tips for Using the Shell
- Running Scripts with the Shell
- Creating a .mongorc.js
- Customizing Your Prompt
- Editing Complex Variables
- Inconvenient Collection Names
- Inserting Documents
- Removing Documents
- Updating Documents
- Document Replacement
- Using Update Operators
- Upserts
- Updating Multiple Documents
- Returning Updated Documents
- Introduction to find
- Query Criteria
- null
- Regular Expressions
- Querying Arrays
- Querying on Embedded Documents
- $where Queries
- Limits
- Avoiding Large Skips
- Advanced Query Options
- Database Commands
- Introduction to Indexes
- Creating an Index
- Introduction to Compound Indexes
- How MongoDB Selects an Index
- Using Compound Indexes
- How $-Operators Use Indexes
- Indexing Objects and Arrays
- Index Cardinality
- When Not to Index
- Types of Indexes
- Index Administration
- Joins
- Server-side v/s Client-side querying
- Retrieving a subset of fields
- Conditional operators
- Aggregation
- Grouping
- Projections
- Cursor Methods
- MapReduce introduction
- Installing single node MongoDB
- Starting a single node instance using command-line options
- Single node installation of MongoDB with options from the config file
- Connecting to a single node in the Mongo shell with JavaScript
- Connecting to a single node using a Java client
- Starting multiple instances as part of a replica set
- Connecting to the replica set in the shell to query and insert data
- Connecting to the replica set to query and insert data from a Java client
- Connecting to the replica set to query and insert data using a Python client
- Starting a simple sharded environment of two shards
- Connecting to a shard in the shell and performing operations
- Introduction
- Creating test data
- Performing simple querying
- Updating and deleting data from the shell
- Analyzing the plan
- Improving the query execution time
- Improvement using indexes
- Improvement using covered indexes
- Some caveats of index creations
- Creating and understanding sparse indexes
- Expiring documents after a fixed interval using the TTL index
- Expiring documents at a given time using the TTL index
- Basic configuration options
- Replication
- Master-Slave Replication
- Adding and Removing Sources
- Replica Sets
- Nodes in a Replica Set
- Using Slaves for Data Processing
- How It Works
- The Oplog
- Syncing
- Replication State and the Local Database
- Blocking for Replication
- Administration
- Diagnostics
- Changing the Oplog Size
- Replication with Authentication
- Renaming a collection
- Viewing collection stats
- Viewing database stats
- Manually padding a document
- The mongostat and mongotop utilities
- Getting current executing operations and killing them
- Using profiler to profile operations
- Setting up users in Mongo
- Interprocess security in Mongo
- Modifying collection behavior using the collMod command
- Setting up MongoDB as a windows service
- Replica set configurations
- shard cluster configurations
- Setting up a Production ready Multi node cluster with 15 nodes
- Using the Admin Interface
- serverStatus
- mongostat
- Third-Party Plug-Ins
- Authentication Basics
- How Authentication Works
- Other Security Considerations
- Data File Backup
- mongodump and mongorestore
- fsync and Lock
- Slave Backups
- Repair
- Document-oriented data
- Principles of schema design
- Designing an e-commerce data model
- Nuts and bolts: on databases
- E-commerce queries
- MongoDB’s query language
- Aggregating orders
- Aggregation in detail
- A brief tour of document updates
- E-commerce updates
- Atomic document processing
- Nuts and bolts: MongoDB updates and deletes
- Introduction
- Atomic find and modify operations
- Implementing atomic counters in Mongo
- Implementing server-side scripts
- Creating and tailing a capped collection cursors in MongoDB
- Converting a normal collection to a capped collection
- Storing binary data in Mongo
- Storing large data in Mongo using GridFS
- Storing data to GridFS from Java client
- Implementing triggers in Mongo using oplog
- Implementing full text search in Mongo
- MongoDB Hadoop Integration
- Hive Integration
- Pig Integration
- HandsOn UseCase Demo
- Replica set configurations
- shard cluster configurations
- Setting up a Production ready Multi node cluster with 15 nodes
- Monitoring
- Shard cluster Administrations & perfromance monitoring
- Troubleshoot
- Security
- Audit
- x509
- TLS/SSL
- Alerts & monitoring
- backup
- Performance tuning and Optimization on MultiNode Mongodb Cluster
- Deciding the number of mongos
- Deciding the no of replica sets
- Deciding the no of shards
- Making Shards as replicasets
- Scaling vs High Availability
- Consistency vs Partitioning vs Performance (revisiting CAP theorem)
- Capacity planning
- HandsOn UseCase Demo
Download
Download MongoDB course plan