Mastering Mono & Flux in Reactive Java
A deep dive into reactive programming with Project Reactor. From Publisher-Subscriber patterns to building real-world reactive pipelines with Mono and Flux.
📑 What You'll Learn
Reactive Programming is a programming paradigm focused on asynchronous data streams and the propagation of change. Instead of pulling data (imperative), you react to data as it arrives.
Think of it like a spreadsheet: when cell A1 changes, all cells that reference A1 automatically update. That's reactive — data flows downstream and consumers react to changes.
🔑 Key Principles:
- • Asynchronous — Non-blocking operations, no thread waiting
- • Event-driven — React to events as they happen
- • Backpressure — Consumer controls the flow of data
- • Lazy execution — Nothing happens until you subscribe
Imperative vs Reactive
// ❌ Imperative (Blocking) — Thread waits for each call
List<User> users = userRepository.findAll(); // Thread BLOCKED
List<Order> orders = orderService.getOrders(users); // Thread BLOCKED again
return processOrders(orders); // Finally returns
// ✅ Reactive (Non-blocking) — Thread is free immediately
Flux<User> users = userRepository.findAll(); // Returns immediately
return users
.flatMap(user -> orderService.getOrders(user)) // Lazy pipeline
.map(order -> processOrder(order)); // Executes when subscribedWhy does this matter? In a traditional servlet-based app, each HTTP request occupies one thread. With 200 threads, you can handle at most 200 concurrent requests. In reactive, a single thread can handle thousands of concurrent connections because it never blocks.
🚀 Go Reactive!
Mono and Flux are the foundation of reactive Java development. Master these concepts and you'll unlock the full power of Spring WebFlux, R2DBC, and reactive microservices.