This article walks through the full design of a billion‑user group chat system, covering functional and non‑functional requirements, core components such as WebSocket and Redis, face‑to‑face group creation, message flow, database schema, and performance‑oriented scaling techniques.
This article walks through the design of a billion‑user group chat platform, covering functional and non‑functional requirements, core components, database schema, face‑to‑face group creation, message flow, storage strategies, and performance‑optimizing techniques such as clustering, message queues, multithreading, and Redis caching.
This guide explains how to design group and private chat messages, define a unified JSON protocol, validate payloads with a custom validator, and implement WebSocket callbacks (onWorkerStart, onWebSocketConnect, onMessage, onClose) using PHP and JavaScript client examples for both one‑to‑one and group conversations.
This article dissects WeChat's group chat system, covering its functional and non‑functional requirements, high‑level architecture, face‑to‑face group creation, message transmission, storage design, and the real‑time red‑packet allocation algorithm implemented in Go.
This article dissects the design of WeChat's group chat system, covering functional and non‑functional requirements, high‑level component architecture, database schemas, face‑to‑face group creation, real‑time messaging, red‑packet algorithms, and Go code implementation, revealing how massive concurrency, performance, and storage challenges are solved.
The article analyzes the memory inefficiency of storing per‑user read/unread lists for group chat messages, proposes a bitmap‑based solution with user‑to‑map ID mapping, discusses handling of member exits, and evaluates the storage savings and scalability of the new design.
This tutorial walks you through creating a real‑time group chat using Spring Boot and Java WebSocket, covering Maven dependencies, core server classes, annotation explanations, configuration, and testing with an online client, all backed by complete source code on GitHub.
The article analyzes the memory overhead of naïvely storing per‑user read/unread lists for group chat messages and proposes a bitmap‑based scheme with user‑to‑map ID mapping, quit flags, and compact storage that can reduce per‑message space by over 95 percent.
The article examines how to efficiently store read/unread status for group chat messages by replacing per‑user lists with compact bitmap structures, discusses handling member exits, presents C++‑style struct definitions, and quantifies storage savings compared to the naïve 8‑byte per‑user approach.
This article examines how to model read/unread status for group chat messages using bitmap techniques, evaluates memory costs of naive approaches, and presents a compact storage schema that handles member joins, exits, and scalability while drastically reducing per‑message overhead.
The article analyzes the memory inefficiency of storing per‑message read/unread user lists in large group chats and proposes a bitmap‑based solution that maps users to sequential IDs, uses compact bitmaps for read status and handles member exits, achieving over 95% storage reduction.
This article presents a comprehensive design and implementation of a high‑availability, horizontally scalable instant‑messaging group‑chat system, detailing its architecture, component interactions, scaling strategies, reliability mechanisms, and extensions for offline and single‑chat messaging.
This article analyzes the challenges of scaling group chat in an instant messaging system and presents architectural optimizations—including shared message storage, periodic conversation list updates, offline count handling, and version‑based incremental sync—to reduce write and read amplification while improving overall performance.
This article examines how to design a reliable group messaging system with read‑receipt support, comparing push and pull delivery, detailing data structures, acknowledgment flows, and optimization techniques to reduce traffic and storage while maintaining real‑time user experience.
