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Spring Reactor 项目核心库

时间:2022-10-18 16:04:38浏览次数:89  
标签:Reactor Reactive Spring System Flux io Mono 核心


Reactor Core

Non-Blocking ​​Reactive Streams​​​ Foundation for the JVM both implementing a ​​Reactive Extensions​​ inspired API and efficient event streaming support.

Getting it

Reactor 3 requires Java 8 or + to run.

With Gradle from repo.spring.io or Maven Central repositories (stable releases only):

    repositories {
// maven { url 'http://repo.spring.io/snapshot' }
maven { url 'http://repo.spring.io/milestone' }
mavenCentral()
}

dependencies {
//compile "io.projectreactor:reactor-core:3.1.4.RELEASE"
//testCompile("io.projectreactor:reactor-test:3.1.4.RELEASE")
compile "io.projectreactor:reactor-core:3.2.0.M1"
testCompile("io.projectreactor:reactor-test:3.2.0.M1")
}

See the ​​reference documentation​​ for more information on getting it (eg. using Maven, or on how to get milestones and snapshots).

Note about Android support: Reactor 3 doesn't officially support nor target Android.
However it should work fine with Android SDK 26 (Android O) and above. See the
​​​complete note​​ in the reference guide.

Getting Started

New to Reactive Programming or bored of reading already ? Try the ​​Introduction to Reactor Core hands-on​​ !

If you are familiar with RxJava or if you want to check more detailled introduction, be sure to check

Flux

A Reactive Streams Publisher with basic flow operators.

  • Static factories on Flux allow for source generation from arbitrary callbacks types.
  • Instance methods allows operational building, materialized on eachFlux#subscribe(),Flux#subscribe()or multicasting operations such asFlux#publishandFlux#publishNext.

Flux in action :

Flux.fromIterable(getSomeLongList())
.mergeWith(Flux.interval(100))
.doOnNext(serviceA::someObserver)
.map(d -> d * 2)
.take(3)
.onErrorResumeWith(errorHandler::fallback)
.doAfterTerminate(serviceM::incrementTerminate)
.subscribe(System.out::println);

Mono

A Reactive Streams Publisher constrained to ZERO or ONE element with appropriate operators.

  • Static factories on Mono allow for deterministiczero or onesequence generation from arbitrary callbacks types.
  • Instance methods allows operational building, materialized on eachMono#subscribe()orMono#get()eventually called.

Mono in action :

Mono.fromCallable(System::currentTimeMillis)
.flatMap(time -> Mono.first(serviceA.findRecent(time), serviceB.findRecent(time)))
.timeout(Duration.ofSeconds(3), errorHandler::fallback)
.doOnSuccess(r -> serviceM.incrementSuccess())
.subscribe(System.out::println);

Blocking Mono result :

Tuple2<Long, Long> nowAndLater = 
Mono.zip(
Mono.just(System.currentTimeMillis()),
Flux.just(1).delay(1).map(i -> System.currentTimeMillis()))
.block();

Schedulers

Reactor uses a ​​Scheduler​​​ as a
contract for arbitrary task execution. It provides some guarantees required by Reactive
Streams flows like FIFO execution.

You can use or create efficient ​​schedulers​​ to jump thread on the producing flows (subscribeOn) or receiving flows (publishOn):


Mono.fromCallable( () -> System.currentTimeMillis() )
.repeat()
.publishOn(Schedulers.single())
.log("foo.bar")
.flatMap(time ->
Mono.fromCallable(() -> { Thread.sleep(1000); return time; })
.subscribeOn(Schedulers.parallel())
, 8) //maxConcurrency 8
.subscribe();

ParallelFlux

​ParallelFlux​​​ can starve your CPU's from any sequence whose work can be subdivided in concurrent
tasks. Turn back into a ​​​Flux​​​ with ​​ParallelFlux#sequential()​​​, an unordered join or
use abitrary merge strategies via 'groups()'.

Mono.fromCallable( () -> System.currentTimeMillis() )
.repeat()
.parallel(8) //parallelism
.runOn(Schedulers.parallel())
.doOnNext( d -> System.out.println("I'm on thread "+Thread.currentThread()) )
.subscribe()

Custom sources : Flux.create and FluxSink, Mono.create and MonoSink

To bridge a Subscriber or Processor into an outside context that is taking care of
producing non concurrently, use ​​​Flux#create​​​, ​​Mono#create​​.

Flux.create(sink -> {
ActionListener al = e -> {
sink.next(textField.getText());
};

// without cancellation support:
button.addActionListener(al);

// with cancellation support:
sink.onCancel(() -> {
button.removeListener(al);
});
},
// Overflow (backpressure) handling, default is BUFFER
FluxSink.OverflowStrategy.LATEST)
.timeout(3)
.doOnComplete(() -> System.out.println("completed!"))
.subscribe(System.out::println)

The Backpressure Thing

Most of this cool stuff uses bounded ring buffer implementation under the hood to mitigate signal processing difference between producers and consumers. Now, the operators and processors or any standard reactive stream component working on the sequence will be instructed to flow in when these buffers have free room AND only then. This means that we make sure we both have a deterministic capacity model (bounded buffer) and we never block (request more data on write capacity). Yup, it's not rocket science after all, the boring part is already being worked by us in collaboration with ​​Reactive Streams Commons​​ on going research effort.

What's more in it ?

"Operator Fusion" (flow optimizers), health state observers, helpers to build custom reactive components, bounded queue generator, hash-wheel timer, converters from/to Java 9 Flow, Publisher and Java 8 CompletableFuture. The repository contains a ​​reactor-test​​​ project with test features like the ​​StepVerifier​​.


Reference Guide

​http://projectreactor.io/docs/core/release/reference/docs/index.html​

Javadoc

​https://projectreactor.io/docs/core/release/api/​

Getting started with Flux and Mono

​https://github.com/reactor/lite-rx-api-hands-on​

Reactor By Example

Head-First Spring & Reactor

​https://github.com/reactor/head-first-reactive-with-spring-and-reactor/​

Beyond Reactor Core


Powered by Reactive Streams Commons

Licensed under Apache Software License 2.0

Sponsored by Pivotal

标签:Reactor,Reactive,Spring,System,Flux,io,Mono,核心
From: https://blog.51cto.com/u_15236724/5766898

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