How Redis Handles Millions of Requests: Event‑Driven, Non‑Blocking IO & Epoll
This article explains how Redis achieves million‑level concurrent connections by using an event‑driven Reactor model, non‑blocking I/O, efficient I/O multiplexing such as epoll, and in‑memory data storage to deliver ultra‑low latency and high throughput.
Event‑Driven Design
Redis uses an event‑driven model based on the Reactor pattern, allowing a single thread to handle many connections efficiently.
Non‑Blocking I/O
Redis’s non‑blocking architecture avoids the bottlenecks of blocking I/O, enabling the server to continue processing other tasks while I/O operations are in progress.
I/O Multiplexing
Redis typically employs Linux’s epoll, an event‑driven I/O multiplexing mechanism that scales far better than select or poll.
struct epoll_event events[10];
int num = epoll_wait(epfd, events, 10, -1);In‑Memory Operations
All data is kept in memory, providing extremely fast read/write speeds and eliminating disk latency, which is essential for handling massive concurrent requests.
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Mike Chen's Internet Architecture
Over ten years of BAT architecture experience, shared generously!
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