Classification hierarchy of Intro To Reactor Core | Baeldung

Introduction:

• This article serves as an introduction to Reactor Core, a Java library that enables reactive programming. It provides a high-level overview, setting the stage for further exploration in subsequent articles.

Reactive Streams Specification:

• The article starts by discussing the Reactive Streams Specification, which forms the foundation for Reactor. It highlights how Reactor implements this specification and provides a groundwork for understanding its capabilities.

Maven Dependencies:

• Proper configuration of Maven dependencies is demonstrated by adding Reactor-core and Logback-classic. This ensures that logging is in place to track the flow of data and help with debugging.

Producing a Stream of Data:

• The article explores how to generate a stream of data, using Flux and Mono as primary tools. It provides examples of creating static and dynamic streams, respectively.

Subscribing and Collecting Elements:

• This section focuses on subscribing to a stream and collecting the elements it emits. It uses logging to visualize the flow of data and demonstrates how to use the subscribe() method to gather elements.

The Flow of Elements:

• The article provides a detailed explanation of the flow of elements within a stream, including the onSubscribe(), request(), onNext(), and onComplete() methods. It also introduces a custom Subscriber implementation to illustrate these stages.

Comparison to Java 8 Streams:

• A comparison is drawn between Reactor and Java 8 Streams in terms of their model and functionality. It emphasizes the push model of Reactor, where events are pushed to subscribers, versus the pull model of Streams, where subscribers request data.

Backpressure:

• The concept of backpressure is introduced, where subscribers can control the amount of data received from an upstream. This helps prevent overwhelming resources and allows for efficient data handling.

Operating on a Stream:

• This section covers mapping data within a stream and combining multiple streams using the zip() function. It provides examples and explains how these operations enable reactive behavior, allowing for dynamic responses to incoming events.

Hot Streams:

• The article discusses hot streams, which are infinite and always running, in contrast to cold streams that have a finite length. It introduces ConnectableFlux, which enables creating hot streams by converting cold ones.

Throttling:

• Throttling is presented as a strategy to control the rate at which data is pushed to subscribers. This helps manage resources and prevent overwhelming systems with excessive data.

Concurrency:

• Concurrency plays a crucial role in reactive programming. The article demonstrates how to run code on different threads using the Schedule interface, showcasing how Reactor can be used in parallel processing scenarios.

Conclusion:

• In conclusion, the article provides a comprehensive overview of Reactor Core and its key concepts. It directs readers to further resources for more advanced topics and applications, setting the stage for further exploration in subsequent articles.