Reactive Streams Specification Explained: Traffic Rules for Data Flow (Publishers, Core Signals) скачать в хорошем качестве

Reactive Streams Specification Explained: Traffic Rules for Data Flow (Publishers, Core Signals)

Reactive Streams Specification Explained: Traffic Rules for Data Flow (Publishers, Backpressure, and Core Signals) Imagine a city without traffic rules—chaos, accidents, and system collapses. The Reactive Streams Specification introduces clear traffic rules for reactive systems, ensuring data flows smoothly and safely. In this video, we use a smart city metaphor to explain the core components and contracts of Reactive Streams: • Publishers are the vehicles producing traffic. • Subscribers are the roads receiving traffic. • The Subscription is the crucial traffic signal and speed control. • The Processor acts as a flyover or junction, serving as both a consumer and a producer. The most important element is the Subscription, which enforces backpressure by controlling the flow. Just like a traffic signal prevents congestion, the Subscriber uses the Subscription to request N items, and the Publisher sends only N items—no more, no less. Without these rules, uncontrolled data flow leads to consumers being flooded, memory overflows, and systems crashing. Reactive Streams defines three core traffic signals (methods): 1. 🟢 onNext(): A data item is delivered safely. 2. 🔴 onError(): An accident happens, traffic stops immediately, and no more data is sent. 3. 🏁 onComplete(): The destination is reached, and traffic ends cleanly. Once onError or onComplete is called, no further events are allowed. This strict adherence to standards is why frameworks like Spring WebFlux, Project Reactor, RxJava, and Akka Streams can integrate and work together smoothly. By implementing Reactive Streams, systems gain guaranteed backpressure, stability, and the ability to handle high throughput safely, powering applications like streaming services, banking platforms, and real-time dashboards.