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Reactive Card Magic: Understanding Spring WebFlux and Project Reactor
The document presents an overview of reactive programming and Spring WebFlux, focusing on its non-blocking architecture designed to handle high client demand. It covers concepts such as reactive systems, project reactor, and key features of Spring WebFlux, alongside code examples for implementing a reactive card magic application. Resources for further reading and related projects are also provided.
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Reactive Card Magic: Understanding Spring WebFlux and Project Reactor
- 1. Reactive Card Magic @JavaFXpert Webon Reactive Stack with Spring
- 2. About Presenter JamesWeaver @JavaFXpert Developer Advocate and International Speaker for Pivotal
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- 5. Reactive Card Magic Whatwill we cover? • Spring WebFlux (what, why, etc.) • Reactive systems and Reactive programming • Reactive programming in Java • Project Reactor • WebClient reactive client • Code and concepts walkthrough of Reactive Card Magic application @JavaFXpert
- 6. Spring WebFlux What isit? @JavaFXpert A non-blocking, reactive web framework that supports Reactive Streams back pressure, and runs on servers such as Netty, Undertow, and Servlet 3.1+ containers. See: Web on Reactive Stack by the Spring team
- 7. WebFlux Like WebMVC butReactive @JavaFXpert
- 8. Spring WebFlux Why wasit created? • Because of mobile devices, IoT, and our continuing trend to live online, some apps today have millions of clients. • Many apps have Black Friday* style usage patterns, where demand can spike exponentially. • Factors such as these drive the need for a non-blocking web stack that: • handles concurrency with a small number of threads and • scales with less hardware resources. @JavaFXpert * Referring to the busiest shopping day of the year in the US, not the last Friday before Christmas in the UK :-)
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- 12. Spring WebFlux Other reasonsfor creating it • Continuation style APIs enabled by Java 8 lambda expressions allow declarative composition of asynchronous logic • Lambdas also enabled Spring WebFlux to offer functional web endpoints alongside with annotated controllers @JavaFXpert
- 13. Spring WebFlux What doesreactive mean? • Reactive refers to programming models (and systems) that are built around asynchronously reacting to external changes (such as messages and events) • An important mechanism in reactive is non-blocking back pressure (flow control) * @JavaFXpert See: Web on Reactive Stack by the Spring team * In synchronous, imperative code, blocking calls serve as a natural form of back pressure that forces the caller to wait.
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- 15. Reactive systems vs.Reactive programming • Reactive systems represent an architectural style that allows multiple individual applications to coalesce as a single unit, reacting to its surroundings, while remaining aware of each other • Reactive programming is a subset of asynchronous programming and a paradigm where the availability of new information drives the logic forward rather than having control flow driven by a thread-of-execution @JavaFXpert From Reactive programming vs. Reactive systems by Jonas Bonér and Viktor Klang
- 16. Some Reactive programminguse cases • External Service Calls • Highly Concurrent Message Consumers • Spreadsheets • Abstraction Over (A)synchronous Processing @JavaFXpert From: Notes on Reactive Programming Part I: The Reactive Landscape by Dave Syer
- 17. Reactive Programming inJava A brief and incomplete history • Reactive programming ideas have been around for a while, appearing in programming languages (e.g. Erlang) and libraries (e.g. Reactive Extensions for .NET) • The open source RxJava (Reactive Extensions for Java) project helped move reactive programming forward on the Java platform. • The Reactive Streams initiative provided a standard and specification for compatibility among reactive implementations in Java. This initiative is a collaboration between engineers from Kaazing, Lightbend, Netflix, Pivotal, Red Hat, Twitter and others. @JavaFXpert
- 18. Reactive Programming inJava • Reactive Streams • RxJava • Reactor • Spring Framework 5 • Ratpack • Akka • Vert.x @JavaFXpert From: Notes on Reactive Programming Part I: The Reactive Landscape by Dave Syer
- 19. Reactive Streams: @JavaFXpert github.com/reactive-streams/reactive-streams-jvm Is astandard and specification for stream-oriented libraries that: • process a potentially unbounded number of elements • sequentially, • with the ability to asynchronously pass elements between components, • with mandatory non-blocking backpressure. reactive-streams.org
- 20. public interface Subscriber<T>{ public void onSubscribe(Subscription s); public void onNext(T t); public void onError(Throwable t); public void onComplete(); } public interface Subscriber<T> { public void onSubscribe(Subscription s); public void onNext(T t); public void onError(Throwable t); public void onComplete(); } Reactive Streams API for Java @JavaFXpert enables interoperability between different Reactive implementations public interface Publisher<T> { public void subscribe(Subscriber<? super T> s); } public interface Subscription { public void request(long n); public void cancel(); } public interface Processor<T, R> extends Subscriber<T>, Publisher<R> { } Adopted by Java 9 in the Flow class
- 21. Reactive Streams withSpring @JavaFXpert From: Servlet and Reactive Stacks in Spring Framework 5 by Rossen Stoyanchev Streaming to database with non-blocking back pressure JSON stream
- 22. Reactive Streams withSpring @JavaFXpert From: Servlet and Reactive Stacks in Spring Framework 5 by Rossen Stoyanchev Streaming from database with non-blocking back pressure JSON stream
- 23. 23 Project Reactor The reactivelibrary of choice for Spring WebFlux
- 24. Project Reactor Avoiding callbackhell and other asynchronous pitfalls Reactive libraries such as Reactor aim to address drawbacks of "classic" asynchronous approaches on the JVM while also focusing on additional aspects: • Composability and readability • Data as a flow manipulated with a rich vocabulary of operators • Nothing happens until you subscribe • Backpressure or the ability for the consumer to signal the producer that the rate of emission is too high • High level but high value abstraction that is concurrency-agnostic @JavaFXpertSee: From Imperative to Reactive Programming in Project Reactor Guide
- 25. abstract class Flux<T> implementsPublisher<T> { ... } abstract class Flux<T> implements Publisher<T> { ... } Reactive Types
- 26. abstract class Mono<T> implementsPublisher<T> { ... } abstract class Mono<T> implements Publisher<T> { ... } Reactive Types
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- 29. Flux.just("Hello", "Reactor", "World") .subscribe(s-> System.out.println(s)); @JavaFXpert Hello Reactor World Project Reactor Simple example
- 30. Project Reactor Marble diagram:Mono @JavaFXpert
- 31. Project Reactor Marble diagram:Flux @JavaFXpert
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- 38. App we’ll usefor code examples @JavaFXpert
- 39. @JavaFXpert CardDeck Repository Hand Frequency Respository Card Deck Service Card Shuffling Service Proxy Poker Service Card Deck Controller Poker Controller Poker Service Card Deck DataLoader WebClient Mono<CardHand> Flux<HandFrequency> Flux<Card>Mono<String> Flux<HandFrequency> Flux<Card>Flux<Card> Reactive Card Magic Application Architecture
- 40. Getting a NewDeck @JavaFXpert
- 41. @RestController @RequestMapping("/cards/deck") public class CardDeckController{ private final CardDeckService cardDeckService; @Autowired public CardDeckController( CardDeckService cardDeckService) { this.cardDeckService = cardDeckService; } @GetMapping("/new") public Mono<CardHand> getCardDeck(@RequestParam(defaultValue = "52") int numcards) { return cardDeckService.generate() .take(numcards) .collectList() .map(l -> new CardHand(l, "New Deck")); } } @JavaFXpert Annotated controller example
- 42. @RestController @RequestMapping("/cards/deck") public class CardDeckController{ private final CardDeckService cardDeckService; @Autowired public CardDeckController( CardDeckService cardDeckService) { this.cardDeckService = cardDeckService; } @GetMapping("/new") public Mono<CardHand> getCardDeck(@RequestParam(defaultValue = "52") int numcards) { return cardDeckService.generate() .take(numcards) .collectList() .map(l -> new CardHand(l, "New Deck")); } } Annotated controller example @JavaFXpert
- 43. @Bean RouterFunction<ServerResponse> newDeckRoutes(CardDeckService cds){ int defaultNumCards = 52; return RouterFunctions.route( RequestPredicates.GET("/newdeck"), request -> cds.generate() .take(request.queryParam("numcards") .map(Integer::parseInt).orElse(defaultNumCards)) .collectList() .map(l -> new CardHand(l,"New Deck")) .flatMap(ServerResponse.ok()::syncBody)); } Functional endpoint example @JavaFXpert
- 44. Spring WebFlux Using WebClient WebClientis a reactive, non-blocking client for HTTP requests with a functional-style API client and Reactive Streams support. By comparison to the RestTemplate, WebClient is: • non-blocking, reactive, and supports higher concurrency with less hardware resources. • provides a functional API that takes advantage of Java 8 lambdas. • supports both synchronous and asynchronous scenarios. • supports streaming up or down from a server. @JavaFXpertFrom Web on Reactive Stack - WebClient
- 45. Identifying a Pokerhand @JavaFXpert
- 46. WebClient pokerWebClient =WebClient.create("http://127.0.0.1:8080"); Mono<String> pokerHandMono = pokerWebClient.post() .uri("/poker/idhand") .body(cardFlux, Card.class) .retrieve() .bodyToMono(String.class); WebClient example @JavaFXpert Calling an endpoint to identify a Poker hand
- 47. Using Reactor operators examplesfrom the Reactive Card Magic application @JavaFXpert Mono defaultIfEmpty() flatMap() flatMapMany() map() retryWhen() then() timeout() Flux as() flatMapIterable() sort() collectList() fromArray() subscribe() compose() fromStream() subscribeOn() concatWith() index() take() defer() just() transform() distinct() map() zip() filter() range() flatMap() skip()
- 48. Dealing ten cardsof same suit @JavaFXpert
- 49. @GetMapping("/{suit}") public Mono<CardHand> getCardDeckBySuit( @PathVariableString suit, @RequestParam(defaultValue = "10") int numcards ) { return cardDeckService.generate() .filter(card -> card.getSuit() .equalsIgnoreCase(suit)) .take(numcards) .collectList() .map(l -> new CardHand(l, "Only " + suit)); } @JavaFXpert Dealing ten cards of same suit Examining filter(), take(), collectList() and map() operators
- 50. @GetMapping("/{suit}") public Mono<CardHand> getCardDeckBySuit( @PathVariableString suit, @RequestParam(defaultValue = "10") int numcards ) { return cardDeckService.generate() .filter(card -> card.getSuit() .equalsIgnoreCase(suit)) .take(numcards) .collectList() .map(l -> new CardHand(l, "Only " + suit)); } @JavaFXpert Dealing ten cards of same suit Examining filter(), take(), collectList() and map() operators
- 51. Flux filter operator publicfinal Flux<T> filter(Predicate<? super T> p) @JavaFXpert API documentation
- 52. Flux take operator publicfinal Flux<T> take(long n) @JavaFXpert API documentation
- 53. Flux collectList operator publicfinal Mono<List<T>> collectList() @JavaFXpert API documentation
- 54. Mono map operator publicfinal <R> Mono<R> map(Function<? super T,? extends R> mapper) @JavaFXpert API documentation
- 56. Flux<Card> filter( card ->) take( 10 ) Flux<Card> Flux<Card> collectList() Mono<List<Card>> map( list -> new CardHand(list, “Only s“)) Mono<CardHand> Only Hearts take( 9 )take( 8 )take( 7 )take( 6 )take( 5 )take( 4 )take( 3 )take( 2 )take( 1 )take( 0 )
- 57. Deal Poker hand:Alternating @JavaFXpert
- 58. private static finalComparator<Card> worthComparator = Comparator.comparingInt(Card::getWorth); public Flux<Card> dealPokerHand(Flux<Card> cardFlux) { return cardFlux.index() .take(9) .filter(t -> t.getT1() % 2 == 0) .map(Tuple2::getT2) // (t -> t.getT2()) .sort(worthComparator); } @JavaFXpert Examining index() and sort() operators Deal Poker hand: Alternating
- 59. Flux index operator publicfinal Flux<Tuple2<Long,T>> index() @JavaFXpertAPI documentation
- 60. Flux index operatorand Tuple2 Flux<Tuple2<Long,Card>> @JavaFXpertTuple2 API documentation 1 0 2 3 index value
- 61. Flux sort operator publicfinal Flux<T> sort(Comparator<? super T> sortFunction) @JavaFXpertAPI documentation
- 63. take( 9 )take(8 )take( 7 )take( 6 )take( 5 )take( 4 )take( 3 )take( 2 )take( 1 )take( 0 ) Flux<Card> index() Flux<Tuple2<Long,Card>> filter( t -> t.getT1() % 2 == 0 ) map( Tuple2::getT2 ) 1 2 3 4 5 6 7 8 0 1 2 3 4 5 6 7 8Flux<Tuple2<Long,Card>> Flux<Tuple2<Long,Card>> 0 2 4 6 8 Flux<Card> Flux<Card> sort(worthComparator) 0 take( 9 )
- 64. Reactive Card Magic Ifwe have time, walk through more code including: • Additional shuffling operations such as Riffle Shuffle • Populating the Card Deck repository • The /shuffledealrepeat endpoint • The /handfrequencies endpoint • Testing with StepVerifier @JavaFXpert
- 65. Spring WebFlux Spring MVCand/or WebFlux? @JavaFXpertFrom Web on Reactive Stack - Applicability
- 66. Reactive Card Magic Whathave we covered? Any more questions? • Spring WebFlux (what, why, etc.) • Reactive systems and Reactive programming • Reactive programming in Java • Project Reactor • WebClient reactive client • Code and concepts walkthrough of Reactive Card Magic application @JavaFXpert
- 67. Web resources • SpringFramework 5 Web on Reactive Stack: docs.spring.io/spring/docs/current/spring-framework-reference/web-reactive.html#spring-webflux • Project Reactor: projectreactor.io • The Reactive Manifesto: reactivemanifesto.org • Reactive Card Magic app: github.com/JavaFXpert/card-deck-demo • James Weaver’s blogs: • JavaFXpert.com • CulturedEar.com @JavaFXpert
- 68. Reactive Card Magic @JavaFXpert Webon Reactive Stack with Spring