Let’s go reactive with JAVA
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The document presents a detailed overview of reactive programming in Java, emphasizing its principles, including asynchronous and non-blocking data flows. It discusses the Reactive Streams specification, Project Reactor, and Spring WebFlux, highlighting their roles in creating responsive applications. Additionally, it includes interfaces for publishers, subscribers, and processors that facilitate event-driven streaming and back pressure management.
Let’s go reactive with JAVA
- 1. Let’s go reactive with JAVA Presented By : Vinisha Sharma Software consultant - Knoldus Inc
- 2. © 2018 Minimal – Presentation template 2 Agenda ● Reactive Programming ● Reactive Streams Specification ● Project Reactor ● Mono/ Flux ● Spring Boot Webflux ● Demo
- 3. 3 05
- 4. 4 ❑ Programming paradigm oriented around - data flows and propagation of change. ❑ Asynchronous and Non Blocking. ❑ Data flow as an Event/Message Driven stream Reactive Programming
- 7. 7 Reactive streams Reactive Streams is an initiative to provide a standard for asynchronous stream processing with non-blocking back pressure Functional Style Code ● Java 8 Streams API ● Lambdas Event Driven Streams ● Event or Message for every result item from Data Source ● Event or Message for Completion or error ● Asynchronous and non-blocking Deferred Push/Pull Model Back Pressure F BE D
- 10. 10 Reactive Stream Specification Specification or Rules for a Reactive Stream (Created by Pivotal, Netflix, LightBend, Twitter etc...)
- 11. 11 public interface Publisher<T> { public void subscribe(Subscriber<? super T> s); } ❑ Represents the Data source ❑ Database ❑ External Service, etc….. Publisher
- 12. 12 public interface Subscriber<T> { public void onSubscribe(Subscription s); public void onNext(T t); public void onError(Throwable t); public void onComplete(); } ❑ Represents the consumer of the stream data Subscriber
- 13. 13 public interface Subscription { public void request(long n); public void cancel(); } Subscription
- 14. 14 public interface Processor<T, R> extends Subscriber<T>, Publisher<R> { } ❑ A Processor represents a processing stage—which is both a Subscriber and a Publisher. Processor
- 17. 17 Data Flow as an Event Driven Stream
- 18. 18 Data Flow as an Event Driven Stream ❏ On Error
- 19. 19 Data Flow as an Event Driven Stream ❏ No data
- 20. 20 Back pressure
- 22. 22 ❑ Reactor is a fully non-blocking reactive programming foundation for the JVM, with efficient demand management (in the form of managing "backpressure"). ❑ Integrates directly with the Java 8 functional APIs, notably CompletableFuture, Stream, and Duration. ❑ Reactive Types - Offers asynchronous sequence (MONO/FLUX) for reactive streams Project Reactor <dependency> <groupId>io.projectreactor</groupId> <artifactId>reactor-core</artifactId> </dependency>
- 23. 23 ❑ Publisher<T> that emits at most one item ❑ Optionally terminates with an onComplete signal or an onError signal. Mono
- 24. 24 ❑ Publisher<T> that emits 0 to n items ❑ Optionally terminates with an onComplete signal or an onError signal. Flux
- 25. 25 Mono Vs Flux Mono<Student> Flux<Student>
- 26. 26 ❑ Reactive-stack web framework ❑ Non Blocking and Supports Reactive Streams back pressure ❑ Runs on such servers as Netty, Undertow, and Servlet 3.1+ containers. Spring Webflux
- 27. 27 DEMO
- 28. 28 ❑ https://projectreactor.io/ ❑ https://github.com/reactive-streams/reactive-streams-jvm ❑ https://stackify.com/reactive-spring-5/ References
- 29. 29 Thank You
- 30. 30 Stay in touch Contact Details: vinsha.sharma@knoldus.com or linkedin.com/in/vinisha-sharma-26538a135