Reactive programming for java developers

Mar 18, 2019Download as pptx, pdf

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This document provides an overview of reactive programming and how it can be applied to Java applications using frameworks like Project Reactor and Spring WebFlux. It defines reactive programming as composing asynchronous and event-based streams using non-blocking operators. It discusses how reactive streams like Flux and Mono work in Project Reactor and how Spring WebFlux allows building reactive web applications that can handle high concurrency with low latency. Examples are provided of building reactive data repositories, handling streaming responses with backpressure, and orchestrating remote service calls reactively.

Reactive Programming
for Java Developers
Constantin PopaEngineering #5
16:00-16:45
Reactive Programming
for Java Developers
Constantin Popa

Reactive Programming
for Java Developers
Constantin Popa

Who here uses…
Java 8
Spring framework
RxJava/Reactor
Spring WebFlux

AGENDA
Reactive Programming 101
Reactive streams – Project Reactor
Reactive web apps – Spring WebFlux

sync&blocking
main thread
I/O
time
main thread
resume processing

async&blocking
main thread
time
wait & join
I/O
I/O

async&nonblocking
main thread
time
Event loop
worker thread
I/O request
I/O request
I/O Data
available

how do achieve that?
without losing your mind…

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

We don’t sacrifice much
callbacks?
Future? CompletableFuture?

vs
Iterable
-
Iterator
Publisher
-
Subscriber

Publisher Subscriber
produces consumes
push events
Feedback
interfaces from
Reactive Streams
specification
now part of Java 9, under
java.util.concurrent.Flow
Subscriber<T>
onNext(T)
onComplete()
onError(Throwable)
onSubscribe(Subscription)
0..N elements
+
0..1 (complete | error)
backpressure
These interfaces
don’t do much…
Subscription.request(n)
Subscription.cancel()

Interactive marble diagrams on http://rxmarbles.com
(most map to Reactor operators)

Reactive programming for java developers

Reactive streams vs Java 8 streams
”The design center for Streams is mostly about data that can be accessed
with no latency (either from data structures or generating functions)”
“The design center for Rx is about infinite streams of events which
may arrive asynchronously.”
Brian Goetz

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

Flux.range(1,3) map
filter
buffer Subscriber
123

More awesomeness
async sub-processes with flatMap

Schedulers.single()
Schedulers.parallel()
Schedulers.elastic()
Schedulers.immediate()

Reactive web applications Spring
WebFlux

Let's recap:
HTTP GET with reactive data repository
Designed to work with both Spring MVC and Spring WebFlux
Simply return reactive types(Flux, Observable) from @Controller
@GetMapping("/cars")
@ResponseBody
public Flux<Car> getCars() {
return this.repository.findAll();
}

Flux<T>:
finite collection or infinite stream?

“application/json”
finite collection(JSON array)

“text/event-stream”
“application/stream+json”
infinite stream

Use case #2
Response stream with backpressure

Handling backpressure
request(n)->write->flush->repeat

Let’s recap:
HTTP GET with streaming response
Simply return reactive types(Flux, Observable) from @Controller
Backpressure handling on both Spring MVC and Spring WebFlux

Use case #3
Reactive remote service orchestration

Let’s recap:
Reactive webclient
Orchestrate non-blocking, nested remote service calls with ease.
Similar to reactive data access

What WebFlux is good for:
High traffic
High concurrency with less hardware resources
Latency, streaming scenarios

Summary
Quite a steep learning curve
Doesn’t fit all scenarios, if it ain’t broken, don’t fix it
It’s fun time to be a Java developer!
Spring WebFlux and Reactor unlock the gates for easy Reactive
Programming on the server side and not only

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Reactive programming for java developers

1. Reactive Programming for Java Developers Constantin PopaEngineering #5 16:00-16:45 Reactive Programming for Java Developers Constantin Popa

2. Reactive Programming for Java Developers Constantin Popa

3. First a Survey

4. Who here uses… Java 8 Spring framework RxJava/Reactor Spring WebFlux

5. AGENDA Reactive Programming 101 Reactive streams – Project Reactor Reactive web apps – Spring WebFlux

6. Reactive Programming 101

7. Why? because blocking is evil

8. sync&blocking main thread I/O time main thread resume processing

9. async&blocking main thread time wait & join I/O I/O

10. async&nonblocking main thread time Event loop worker thread I/O request I/O request I/O Data available

11. how do achieve that? without losing your mind…

12. Reactive Programming

13. “Composing asynchronous & event-based streams using non-blocking operators”

14. We don’t sacrifice much callbacks? Future? CompletableFuture?

15. Pull? Push!

16. vs Iterable - Iterator Publisher - Subscriber

17. Data in Flux

18. Publisher Subscriber produces consumes push events Feedback interfaces from Reactive Streams specification now part of Java 9, under java.util.concurrent.Flow Subscriber<T> onNext(T) onComplete() onError(Throwable) onSubscribe(Subscription) 0..N elements + 0..1 (complete | error) backpressure These interfaces don’t do much… Subscription.request(n) Subscription.cancel()

19. Project Reactor

20. Flux<T> generates 0..N elements

21. Marble diagrams

22. Give the Flux a second chance

23. Interactive marble diagrams on http://rxmarbles.com (most map to Reactor operators)

24. Mono<T> generates 0..1 elements

26. Reactive streams vs Java 8 streams ”The design center for Streams is mostly about data that can be accessed with no latency (either from data structures or generating functions)” “The design center for Rx is about infinite streams of events which may arrive asynchronously.” Brian Goetz

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

28. Flux.range map filter buffer Subscriber Nothing happens until you subscribe

32. Flux.range(1,3) map filter buffer Subscriber 123

33. Flux.range(1,3) .map( number -> toShape()) .filter(shape -> isCircle()) .buffer() .subscribe(shape -> printShape())

34. More awesomeness async sub-processes with flatMap

36. Reactor is concurrency-agnostic

37. Flux.range(1,3) .map( number -> toShape()) .filter(shape -> isCircle()) .buffer() .subscribe(shape -> printShape())

38. Flux.range(1,3) .subscribeOn(Schedulers.elastic()) .map(number -> toShape()) .filter(shape -> isCircle()) .buffer() .publishOn(Schedulers.immediate()) .subscribe(shape -> printShape())

39. Schedulers.single() Schedulers.parallel() Schedulers.elastic() Schedulers.immediate()

40. Reactive web applications Spring WebFlux

41. Use case #1 Reactive data repository

42. Let's recap: HTTP GET with reactive data repository Designed to work with both Spring MVC and Spring WebFlux Simply return reactive types(Flux, Observable) from @Controller @GetMapping("/cars") @ResponseBody public Flux<Car> getCars() { return this.repository.findAll(); }

43. Flux<T>: finite collection or infinite stream?

44. Use media type to decide

45. “application/json” finite collection(JSON array)

46. “text/event-stream” “application/stream+json” infinite stream

47. DEMO

48. Use case #2 Response stream with backpressure

49. Handling backpressure request(n)->write->flush->repeat

50. DEMO

51. Let’s recap: HTTP GET with streaming response Simply return reactive types(Flux, Observable) from @Controller Backpressure handling on both Spring MVC and Spring WebFlux

52. Use case #3 Reactive remote service orchestration

53. DEMO

54. Let’s recap: Reactive webclient Orchestrate non-blocking, nested remote service calls with ease. Similar to reactive data access

57. What WebFlux is good for: High traffic High concurrency with less hardware resources Latency, streaming scenarios

58. Summary Quite a steep learning curve Doesn’t fit all scenarios, if it ain’t broken, don’t fix it It’s fun time to be a Java developer! Spring WebFlux and Reactor unlock the gates for easy Reactive Programming on the server side and not only

Reactive programming for java developers

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