翻译自：https://tech.io/playgrounds/929/reactive-programming-with-reactor-3/Flux
Flux
Description
A Flux is a Reactive Streams Publisher, augmented with a lot of operators
that can be used to generate, transform, orchestrate Flux sequences.
Flux 是一个反应式流发布者，由许多可用于生成、转换和编排Flux序列的运算符组成。
It can emit 0 to n onNext event) then either completes or errors
(onComplete and onError terminal events). If no terminal event is triggered,
the Flux is infinite.
它可以发出0到n个元素（onNext事件），然后完成或出错（onComplete和onError终端事件）。
如果没有触发终端事件，则Flux是无限的。
- Static factories on Flux allow to create sources, or generate them from
several callbacks types.Flux上的静态工厂允许创建源，或从几种回调类型生成源。 - Instance methods, the operators, let you build an asynchronous processing
pipeline that will produce an asynchronous sequence.实例方法（operators）允许您构建一个异步处理管道，该管道将生成异步序列。 - Each
Flux#subscribe()or multicasting operation such asFlux#publishand
Flux#publishNextwill materialize a dedicated instance of the pipeline and
trigger the data flow inside it.每个Flux#subscribe()或多播操作（如Flux#publish和Flux#publishNext）将具体化管道的专用实例， 并触发其中的数据流。
Flux in action :
Flux.fromIterable(getSomeLongList())
.delayElements(Duration.ofMillis(100))
.doOnNext(serviceA::someObserver)
.map(d -> d * 2)
.take(3)
.onErrorResumeWith(errorHandler::fallback)
.doAfterTerminate(serviceM::incrementTerminate)
.subscribe(System.out::println);
Practice
In this lesson we'll see different factory methods to create a Flux.
在本课中，我们将看到创建Flux的不同工厂方法。
Let's try a very simple example: just return an empty flux.
让我们尝试一个非常简单的示例：只返回一个空的flux。
// Return an empty Flux
Flux emptyFlux() {
return Flux.empty();
}
One can also create a Flux out of readily available data:
还可以从现成的数据中创建Flux：
// Return a Flux that contains 2 values "foo" and "bar" without using an array or a collection
Flux fooBarFluxFromValues() {
return Flux.just("foo", "bar");
}
This time we will use items of a list to publish on the flux
with fromIterable:
这一次，我们将使用列表中的项目在flux上发布（通过fromIterable）：
// Create a Flux from a List that contains 2 values "foo" and "bar"
Flux fooBarFluxFromList() {
List list = new ArrayList();
list.add("foo");
list.add("bar");
return Flux.fromIterable(list);
}
In imperative synchronous code, it's easy to manage exceptions with
familiar try-catch blocks, throw instructions...
在命令式同步代码中，使用熟悉的try-catch块、抛出指令很容易管理异常
But in an asynchronous context, we have to do things a bit differently.
Reactive Streams defines the onError signal to deal with exceptions.
Note that such an event is terminal: this is the last event the Flux will produce.
但在异步环境中，我们必须做一些不同的事情。反应流定义onError信号以处理异常。
注意，这样的事件是终端事件：这是Flux将产生的最后一个事件。
Flux#error produces a Flux that simply emits this signal, terminating immediately:
Flux#error产生一个Flux，该Flux仅发出【立即终止】信号：
// Create a Flux that emits an IllegalStateException
Flux errorFlux() {
return Flux.error(new IllegalStateException());
}
To finish with Flux, let's try to create a Flux that produces ten elements,
at a regular pace. In order to do that regular publishing, we can use interval.
But it produces an infinite stream (like ticks of a clock), and we want to
take only 10 elements, so don't forget to precise it.
为了完成Flux，让我们试着创建一个Flux，以固定的速度生成十个元素。为了定期发布，我们可以使用interval。
但它会产生一个无限流（就像时钟的滴答声），我们只需要10个元素，所以不要忘记对其进行精确计算。
// Create a Flux that emits increasing values from 0 to 9 each 100ms
Flux counter() {
return Flux.interval(Duration.ofMillis(100)).take(10);
}