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Reactive Spring Workshop

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Reactive Programming 101 what does it bring to the table?

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WHY?

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WHY? because blocking is evil

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sync/blocking main thread processing resumes I/O ! app does nothing

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sync/blocking main thread processing resumes I/O BAD ! app does nothing

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async & blocking main thread wait & join ! new threads, costly ! complex

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async & blocking main thread wait & join ! new threads, costly ! complex BAD

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async & nonblocking “event loop” in non-blocking processin g chunks no more threads than needed

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how do you achieve that without losing your mind ?

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Reactive Programming

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Composing asynchronous & event-based sequences, using non-blocking operators “ ”

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without sacrifice

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without sacrifice Callbacks ? Futures ? easy to block hard to compose callback hell ! not readable

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Pull? Push!

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Pull? Push!

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vs Iterable - Iterator Publisher - Subscriber

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Data in Flux

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Publisher Subscriber push events produces consumes feedback

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interfaces from Reactive Streams spec Publisher Subscriber feedback consumes push events produces

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Publisher Subscriber push events produces consumes feedback Subscriber onNext(T) onComplete(); onError(Throwable);

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Publisher Subscriber produces consumes feedback 0..N elements + 0..1 (complete | error)

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Publisher Subscriber push events produces consumes feedback backpressure

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Publisher Subscriber push events produces consumes feedback can I have an API though?

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Publisher Subscriber push events produces consumes feedback

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Reactor 3 types and operators

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Flux for 0..N elements

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Mono for at most 1 element

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Reactive Streams all the way

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focus on Java 8

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focus on Java 8 Duration, CompletableFuture, Streams

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an Rx-inspired API with a vocabulary of operators similar to RxJava...

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an Rx-inspired API ...but not exactly the same

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Flux/Mono generator operator operator operator nothing happens until you subscribe

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Flux/Mono generator Subscriber operator operator operator nothing happens until you subscribe

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Flux/Mono generator Subscriber operator operator operator per Subscription state Sub Sub Sub

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Flux/Mono generator Subscriber operator operator operator data flows Sub Sub Sub

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“elements of functional programming”

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threading contexts

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Reactor is agnostic

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however it facilitates switching

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Schedulers

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Schedulers elastic, parallel, single, timer...

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publishOn switch rest of the flux on a thread

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subscribeOn make the subscription and request happen on a particular thread

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Flux/Mono generator operator subscribeOn operator publishOn operator operator Subscriber Sub Sub Sub Sub Sub Sub

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Flux/Mono generator operator subscribe On operator publish On operator operator Subscriber Sub Sub Sub Sub Sub Sub

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Flux/Mono generator operator subscribeOn operator publishOn operator operator Subscriber Sub Sub Sub Sub Sub Sub

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Flux/Mono generator operator subscribeOn operator publishOn operator operator Subscriber Sub Sub Sub Sub Sub Sub

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Flux/Mono generator operator subscribeOn operator publishOn operator operator Subscriber Sub Sub Sub Sub Sub Sub

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Flux/Mono generator operator subscribeOn operator publishOn operator operator Subscriber Sub Sub Sub Sub Sub Sub

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CODING TIME!

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Bonus Slides operator step-by-step examples, backpressure

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map, filter, buffer

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Flux.range Subscriber map filter buffer

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Flux.range(5, 3) .map(i -> i + 3) .filter(i -> i % 2 == 0) .buffer(3)

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Flux.range Subscriber map filter buffer

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Flux.range Subscriber map filter buffer

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Flux.range Subscriber map filter buffer

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Flux.range Subscriber map filter buffer

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Flux.range Subscriber map filter buffer

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Flux.range Subscriber map filter buffer

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Flux.range Subscriber map filter buffer

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Flux.range(5, 3) .map(i -> i + 3) .filter(i -> i % 2 == 0) .buffer(3) 5, 6, 7 | 8, 9, 10 | 8, 10 | [8,10]|

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retry

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Flux.from Subscriber map filter retry Publisher from HTTP reactive client

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Flux.from Subscriber map filter retry Publisher from HTTP reactive client

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Flux.from Subscriber map filter retry Publisher from HTTP reactive client resubscribe

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Trickier: flatMap async sub-processes

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flatMap(user -> tweetStream(user))

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flatMap(user -> tweetStream(user))

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flatMap(user -> tweetStream(user))

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flatMap(user -> tweetStream(user))

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& much more...

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backpressure the "volume control"

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Publisher Subscriber subscribe

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Publisher Subscriber push data as fast as possible

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Publisher Subscriber subscribe with small request (eg. 1)

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Publisher Subscriber 1 onNext

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Publisher Subscriber request more (eg. 2)

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Publisher Subscriber 2 onNext

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Publisher Subscriber backpressure

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other ways of dealing with backpressure eg. drop, buffer...

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Credits ! Robot Devil: copyright FOX ! Volume Knob: CC0 (via Pixabay) ! Camel Shape: CC0 (via Pixabay) ! Dromedary Shape: CC-By-SA USPN,Whidou (via Wikimedia) ! Thread Balls: CC0 (via Pixabay) ! Coding Time: derived from KEMUDA Computer Lab (CC-By-SA Andy.aug, via Wikimedia) ! Sound Table: CC0 (via Pexels) ! Dam: CC-By-SA Matthew Hatton (via geograph.org.uk) ! logos: Pivotal, Spring, Twitter and Github logo copyright their respective companies.