System requirements

Functional:

• User Authentication: This is essential for ensuring only registered users can post comments.
• Comment Creation & Replies: This allows users to participate in discussions.
• Nested Comments: This is the core functionality, enabling threaded conversations.
• Real-time Updates: This keeps users engaged and informed about new activity.
• Edit & Delete: Users need control over their own comments.
• Moderation: Ensures a safe and healthy discussion environment.
• User Notifications: Keeps users informed about relevant replies.
• Search: Helps users find specific information within a conversation.

Non-Functional:

• Scalability: The system should be able to grow with the user base and activity.
• Reliability: Minimizes disruptions and ensures data availability.
• Security: Protects user data and prevents unauthorized access.
• Usability: The interface should be intuitive and user-friendly.
• Responsive Design: Provides a good experience on all devices.
• Data Integrity: Ensures the accuracy and consistency of comment data.
• Performance: Fast loading times and efficient data retrieval are crucial.

API design

User Management:

• POST /users (Create User): Creates a new user account. (Requires minimal data like username, password)
• POST /login (Login): Authenticates a user and returns a token for subsequent requests. (Requires username/email and password)
• GET /users/me (Get User Info): Retrieves information about the currently logged-in user. (Requires valid access token)

Comment Management:

• POST /posts/{postId}/comments (Create Comment): Creates a new comment on a specific post. (Requires valid access token, post ID, and comment content)
• POST /comments/{commentId}/replies (Reply to Comment): Creates a reply to an existing comment. (Requires valid access token, comment ID, and reply content)
• GET /posts/{postId}/comments (Get Post Comments): Retrieves all comments for a specific post, including nested replies. (Optional parameters for pagination and filtering)
• GET /comments/{commentId} (Get Comment): Retrieves a specific comment with its replies. (Optional parameter to include nested replies)
• PUT /comments/{commentId} (Edit Comment): Allows users to edit their own comments. (Requires valid access token and comment content)
• DELETE /comments/{commentId} (Delete Comment): Allows users and admins to delete comments. (Requires valid access token and authorization for deletion)

Moderation:

• DELETE /admin/comments/{commentId} (Admin Delete Comment): Allows admins to delete inappropriate comments. (Requires admin access token)

Notifications:

• GET /users/me/notifications (Get User Notifications): Retrieves unread notifications for the logged-in user. (Requires valid access token)
• PUT /notifications/{notificationId} (Mark Notification as Read): Allows users to mark notifications as read. (Requires valid access token and notification ID)

Search:

• GET /posts/{postId}/comments/search (Search Comments): Allows users to search for comments within a specific post based on keywords. (Requires valid access token and search query)

Database Design for Nested Comments System

Here's a breakdown of potential database choices for your nested comments system, considering the CAP theorem:

1. Relational Database (SQL):

• Database Type: SQL (e.g., MySQL, PostgreSQL)
• Reasoning: Structured data like users, posts, and their relationships are well-suited for relational databases with efficient querying capabilities.
• CAP Theorem: Leans towards Consistency. SQL databases prioritize data consistency, ensuring all reads reflect the latest updates across all replicas.

2. Document Database (NoSQL):

• Database Type: NoSQL (e.g., MongoDB)
• Reasoning: Document databases offer flexibility for storing hierarchical comment data with varying structures and embedded replies.
• CAP Theorem: Can be Balanced or Availability Focused. Some NoSQL databases prioritize consistency like SQL, while others favor high availability for handling read requests even during updates. Choose a database based on your specific needs for consistency vs. availability.

Data Partitioning:

• Best Strategy: Partition by Post ID.
• Reasoning: This distributes comments for each post across different database partitions, improving performance when retrieving comments for a specific post.
• Partitioning Algorithm: Range Partitioning can be used. It divides the data based on the continuous range of Post IDs.

Sharding Strategy:

• Best Strategy: Horizontal Sharding by Post ID.
• Reasoning: Sharding distributes data across multiple database servers, improving scalability as the number of posts and comments grows. Sharding by Post ID ensures comments for each post are likely to be co-located on the same shard, minimizing data movement for post-specific queries.

High-level design

Here's a breakdown of the high-level components needed for the nested comments system:

1. API Gateway:

• Serves as the single entry point for all API requests.
• Routes requests to appropriate backend services based on functionality (e.g., user management, comments).
• Handles authentication and authorization checks for incoming requests.

2. User Service:

• Manages user accounts (registration, login, profile information).
• Validates user credentials and issues access tokens for authorized requests.

3. Post Service:

• Handles CRUD operations for posts (create, read, update, delete).
• Enforces authorization for post creation and modification.

4. Comment Service:

• Handles CRUD operations for comments (create, read, update, delete).
• Validates comment creation requests and enforces authorization.
• Implements logic for nesting comments under a parent comment.

5. Notification Service (Optional):

• Generates notifications for users when they receive replies or mentions in comments.
• Manages notification delivery and user interaction (marking as read, deleting).

6. Database:

• Stores user data, posts, comments (including nested replies), and notification information (if applicable).
• Uses chosen database technology (e.g., relational, NoSQL) with appropriate partitioning and sharding strategies for scalability.

7. Cache (Optional):

• Can be implemented using a key-value store (e.g., Redis) to cache frequently accessed data (e.g., top-level comments for a post).
• Improves performance by reducing database load for frequently retrieved information.

Request flows

Explain how the request flows from end to end in your high level design. Also you could draw a sequence diagram using the diagramming tool to enhance your explanation...

Detailed component design

Dig deeper into 2-3 components and explain in detail how they work. For example, how well does each component scale? Any relevant algorithm or data structure you like to use for a component? Also you could draw a diagram using the diagramming tool to enhance your design...

Trade offs/Tech choices

Explain any trade offs you have made and why you made certain tech choices...

Failure scenarios/bottlenecks

Try to discuss as many failure scenarios/bottlenecks as possible.

Future improvements

What are some future improvements you would make? How would you mitigate the failure scenario(s) you described above?