Author Archives: Stanislav_Panteleev

the Subscription plays a pivotal role in managing flow control and resource management in reactive programming. Let’s break it down 👇 🎯 What is a Subscription? In Reactive Streams (Java 9 Flow API, RxJava, Reactor, Akka Streams), a Subscription is … Continue reading →

Let’s compare RxJava, Project Reactor, Spring WebFlux, and Akka Streams, each with simple Cold vs Hot observable examples.

Java Reactive Flow, which is part of the Reactive Streams specification — the foundation of modern reactive libraries like RxJava, Project Reactor, and Akka Streams. 🌊 What is Java Reactive Flow? ✅ It’s a standard API introduced in Java 9 … Continue reading →

Understanding the difference between Hot and Cold Observables is crucial to mastering RxJava and reactive programming in general — especially when working with time-sensitive or shared data sources. Let’s break it down clearly and visually 👇 ❄️ Cold Observable 📌 … Continue reading →

🧠 Summary Backpressure = “Slow down! I can’t handle that much data right now!” Prevents overwhelming the consumer. Crucial for building robust, scalable, and memory-safe reactive systems. In a reactive stream, the consumer is the Observer / Subscriber — the … Continue reading →

🙌 Backpressure is one of the most important — and often misunderstood — concepts in reactive programming, especially when dealing with asynchronous streams. Let’s unpack it clearly 👇 🔄 What is Backpressure? Backpressure refers to a situation and a mechanism … Continue reading →

🎯 Goal of Reactive Programming: To react to a stream of data/events over time, in a non-blocking, asynchronous, and declarative way. This is achieved by two main players: 🧩 1. Observable<T> — The Data Source ✅ What it is: An … Continue reading →

The Observer Pattern is a behavioral design pattern where: One object (the Subject) maintains a list of Observers. When the Subject’s state changes, it notifies all its Observers. Think of it like a subscription model: You (Observer) subscribe to a … Continue reading →

📌 It depends on the Scheduler you use. ✅ Schedulers.io() Purpose: For I/O-bound tasks like DB calls, file access, HTTP calls. Type: Cached thread pool (like Java’s Executors.newCachedThreadPool()). Threads: Unbounded (new threads created as needed, idle ones reused). Good for: … Continue reading →

This line changes the thread where the subscriber and everything downstream of it will run. 🔧 The Reactive Pipeline Has Stages Imagine this code: Here’s what happens: just(“Stanley”) emits the data. .map(…) transforms it (runs on the same thread as … Continue reading →