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5 Project Reactor Techniques That Turned My Blocking Java Code Into High-Performance Pipelines

DEV Community·Nithin Bharadwaj·about 1 month ago
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As a best-selling author, I invite you to explore my books on Amazon . Don't forget to follow me on Medium and show your support. Thank you! Your support means the world! I’ve spent years writing Java applications that just couldn’t keep up under load. A single slow database query would freeze the whole request, threads would pile up, memory would spike, and my users would stare at loading spinners. Then I discovered Reactive Programming with Project Reactor. It changed how I think about data flows, concurrency, and failure handling. Let me walk you through five techniques that turned my blocking, thread‑per‑request nightmares into non‑blocking, efficient pipelines. First, you need to get comfortable with the two core types: Flux and Mono . Think of Mono as a container that either holds one value or nothing at all. Flux holds zero to many values, like a stream of events. Almost every business operation maps to one of these. When I fetch a single user from a database, I return Mono<User> .…

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