Reactive Programming In Java Using: Project Reactor

Aug 8, 2019Download as pptx, pdf

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The document outlines reactive programming in Java using Project Reactor, highlighting its asynchronous and non-blocking nature as well as the Reactive Streams specification. It details the roles of publishers, subscribers, and processors in the event-driven data flow model. Additionally, it describes the reactive types Mono and Flux, which represent single and multiple asynchronous data emissions respectively.

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Presented By:
Vinisha Sharma
Software Consultant
Reactive Programming in Java
using : Project Reactor

Our Agenda
01 Reactive Programming
02 Reactive Stream Specification
03 Project Reactor
04 Mono and Flux
05 Demo

Reactive Programming In Java Using: Project Reactor

Reactive Programming
● Programming paradigm oriented around - data flows and propagation of change.
● Asynchronous and Non Blocking.
● Data flow as an Event/Message Driven stream

Reactive Streams
Reactive Streams is an initiative to provide a standard for asynchronous stream
processing with non-blocking back pressure.
Back Pressure
Deferred Push/Pull
Model
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
E
F
B
D

Imperative Programming
Synchronous and blocking communication model

Reactive Stream Specification
Specification or Rules for a Reactive Stream
(Created by Pivotal, Netflix, LightBend, Twitter etc...)
Publisher Subscriber Subscription Processor

Subscriber
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

Subscription
public interface Subscription {
public void request(long n);
public void cancel();
}

Processor
public interface Processor<T, R> extends Subscriber<T>, Publisher<R> {
}
● A Processor represents a processing stage—which is both a Subscriber and a Publisher.

Data Flow as an Event Driven Stream
● On Error

Data Flow as an Event Driven Stream
● No data

Project Reactor
● 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
<dependency>
<groupId>io.projectreactor</groupId>
<artifactId>reactor-core</artifactId>
</dependency>

Mono
● Publisher<T> that emits at most one item
● Optionally terminates with an onComplete signal or an onError signal.

Flux
● Publisher<T> that emits 0 to n items
● Optionally terminates with an onComplete signal or an onError signal.

Mono VS Flux
Mono<Student> Flux<Student>

References
● https://projectreactor.io/
● https://github.com/reactive-streams/reactive-streams-jvm
● https://stackify.com/reactive-spring-5/

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1. Presented By: Vinisha Sharma Software Consultant Reactive Programming in Java using : Project Reactor

2. Our Agenda 01 Reactive Programming 02 Reactive Stream Specification 03 Project Reactor 04 Mono and Flux 05 Demo

4. Reactive Programming ● Programming paradigm oriented around - data flows and propagation of change. ● Asynchronous and Non Blocking. ● Data flow as an Event/Message Driven stream

5. Reactive Manifesto

6. Reactive Streams Reactive Streams is an initiative to provide a standard for asynchronous stream processing with non-blocking back pressure. Back Pressure Deferred Push/Pull Model 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 E F B D

7. Imperative Programming Synchronous and blocking communication model

8. Reactive Stream Specification Specification or Rules for a Reactive Stream (Created by Pivotal, Netflix, LightBend, Twitter etc...) Publisher Subscriber Subscription Processor

9. Publisher public interface Publisher<T> { public void subscribe(Subscriber<? super T> s); } ● Represents the Data source ○ Database ○ External Service, etc…..

10. Subscriber 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

11. Subscription public interface Subscription { public void request(long n); public void cancel(); }

12. Processor public interface Processor<T, R> extends Subscriber<T>, Publisher<R> { } ● A Processor represents a processing stage—which is both a Subscriber and a Publisher.

13. Publisher/Subscriber Event Flow

14. Publisher/Subscriber Event Flow

15. Data Flow as an Event Driven Stream

16. Data Flow as an Event Driven Stream ● On Error

17. Data Flow as an Event Driven Stream ● No data

18. Back Pressure

19. Project Reactor ● 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 <dependency> <groupId>io.projectreactor</groupId> <artifactId>reactor-core</artifactId> </dependency>

20. Mono ● Publisher<T> that emits at most one item ● Optionally terminates with an onComplete signal or an onError signal.

21. Flux ● Publisher<T> that emits 0 to n items ● Optionally terminates with an onComplete signal or an onError signal.

22. Mono VS Flux Mono<Student> Flux<Student>

23. References ● https://projectreactor.io/ ● https://github.com/reactive-streams/reactive-streams-jvm ● https://stackify.com/reactive-spring-5/

24. Thank You !

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