Chapter 12: Design a Chat System

2. Receiver Side:

   • Polling:

     • Client periodically asks the server if there are messages available.

     • Inefficient due to frequent, redundant requests.

       

   • Long Polling:

     • Keeps the connection open until messages arrive.

     • Inefficient for inactive users.

       

   • WebSocket:

     • A bi-directional, persistent connection for real-time communication, chosen for both sending and receiving messages.

     • Uses WebSockets (ws) protocol for sending and recieving messages.

       

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Components

1. Stateless Services:
   • Handle signup, login, and user profile management.
   • Integrated with service discovery to recommend the best chat server.
2. Stateful Services:
   • Chat servers maintain persistent WebSocket connections.
   • Responsible for message delivery and synchronization.
3. Third-Party Integration:
   • Push notification services notify users about new messages.
   • Refer Notification System chapter for notifications implementation.

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Design

The client maintains a persistent WebSocket connection to a chat server for real-time messaging.

• Chat servers facilitate message sending/receiving.
• Presence servers manage online/offline status.
• API servers handle everything including user login, signup, change profile, etc.
• Notification servers send push notifications.
• Finally, the key-value store is used to store chat history.Key-value stores for the database of the chat history data for following reasons:
  • It allows easy horizontal scaling.
  • KV stores provide very low latency to access data.
  • Relational databases do not handle long tail of data well. When the indexes grow large, random access is expensive.
  • KV stores are adopted by other proven reliable chat applications. For example, both Facebook messenger and Discord.

Following are the data models for one-to-one chat and group chat.

• The primary key is message id, which helps to decide message sequence.
• For the group chat the composite primary key is (channel_id, message_id).
  • IDs can be generated using a global 64-bit sequence number generator like Snowflake.
  • A better approach is to use local sequence number generator. Local means IDs are only unique within a group.
  • The reason why local IDs work is that maintaining message sequence within one-on-one channel or a group channel is sufficient.
    

Step 3: Design Deep Dive

Service Discovery

• The primary role of service discovery is to recommend the best chat server for a client based on the criteria like geographical location, server capacity.
• Uses Apache Zookeeper to allocate chat servers based on criteria like geographic location and server capacity.
• Ensures efficient load distribution and minimizes latency.

Messaging Flows

One-on-One Chat

1. User A sends a message to Chat Server 1.
2. Chat Server 1 assigns a unique message ID and stores the message in a key-value store.
3. If User B is online, the message is forwarded to Chat Server 2, maintaining a persistent WebSocket connection.
4. If User B is offline, a push notification is sent.

Group Chat

• Messages are copied to individual inboxes for each recipient in the group.
• Simplifies synchronization but becomes expensive for larger groups.
• On the recipient side, a recipient can receive messages from multiple users. Each recipient has an inbox (message sync queue) which contains messages from different senders.

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Message Synchronization

Many users have multiple devices. We need to synchronize the message across the devices. Each device maintains a variable called cur_max_message_id, which keeps track of the latest message ID on the device. Messages that satisfy the following two conditions are considered as news messages:

• The recipient ID is equal to the currently logged-in user ID.
• Message ID in the key-value store is larger than cur_max_message_id

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Online Presence

1. Heartbeat Mechanism:

   
   - Clients send periodic heartbeats to presence servers to indicate they are online. - If no heartbeat is received within a threshold (for eg x = 30), the user is marked offline.

2. Fanout Model:

   
   - Presence updates are pushed to friends using a publish-subscribe model in which each friend pair maintains a channel. - When User A’s online status changes, it publishes the event to three channels, channel A-B, A-C, and A-D. - Those three channels are subscribed by User B, C, and D, respectively which get the online status updates. - The above design is effective for a small user groups.

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Additional Considerations

Scalability

• Horizontal Scaling: Add servers as user count increases.
• Load Balancing: Distribute traffic evenly across servers.
• Caching: Reduce database load and improve latency.

Error Handling

• Retry Mechanisms: Handle message delivery failures with retries and queuing.
• Server Failures: Use service discovery to allocate new servers in case of failures.

Future Extensions

1. Media Support: Add handling for photos and videos, including compression and cloud storage.
2. End-to-End Encryption: Ensure message privacy.
3. Client-Side Caching: Reduce data transfer for better performance.
4. Improved Load Times: Use geographically distributed caching networks.