RxJava（三） flatMap操作符用法详解

flatMap操作符的作用
官方文档解释：

Returns an Observable that emits items based on applying a function that you supply to each item emitted by the source Observable, where that function returns an Observable, and then merging those resulting Observables and emitting the results of this merger.

官方流程图：

对Observable发射的数据都应用(apply)一个函数，这个函数返回一个Observable，然后合并这些Observables，并且发送（emit）合并的结果。 flatMap和map操作符很相像，flatMap发送的是合并后的Observables，map操作符发送的是应用函数后返回的结果集

flatMap操作符使用示例

继续map操作符的案例

private Observable processUrlIpByOneFlatMap() {
        return Observable.just(
                "http://www.baidu.com/",
                "http://www.google.com/",
                "https://www.bing.com/")
                .flatMap(new Func1>() {
                    @Override
                    public Observable call(String s) {
                        return createIpObservable(s);
                    }
                })
                .subscribeOn(Schedulers.io())
                .observeOn(AndroidSchedulers.mainThread())
                .subscribe(new Action1() {
                    @Override
                    public void call(String s) {
                        printLog(tvLogs, "Consume Data <- ", s);
                    }
                }, new Action1() {
                    @Override
                    public void call(Throwable throwable) {
                        printErrorLog(tvLogs, "throwable call()", throwable.getMessage());
                    }
                });
    }

    //根据主机获取ip
    private Observable createIpObservable(final String url) {
        return Observable.create(new Observable.OnSubscribe() {
            @Override
            public void call(Subscriber subscriber) {
                try {
                    String ip = getIPByUrl(url);
                    subscriber.onNext(ip);
                    printLog(tvLogs, "Emit Data -> ",url+" : " +ip);
                } catch (MalformedURLException e) {
                    e.printStackTrace();
                    //subscriber.onError(e);
                    subscriber.onNext(null);
                } catch (UnknownHostException e) {
                    e.printStackTrace();
                    //subscriber.onError(e);
                    subscriber.onNext(null);
                }
                subscriber.onCompleted();
            }
        });
    }

输出结果：

Emit Data -> 'http://www.baidu.com/ : 115.239.211.112'
Main Thread:false, Thread Name:RxCachedThreadScheduler-1
Consume Data <- '115.239.211.112'
Main Thread:true, Thread Name:main

Emit Data -> 'http://www.google.com/ : 216.58.199.100'
Main Thread:false, Thread Name:RxCachedThreadScheduler-1
Consume Data <- '216.58.199.100'
Main Thread:true, Thread Name:main

Emit Data -> 'https://www.bing.com/ : 202.89.233.104'
Main Thread:false, Thread Name:RxCachedThreadScheduler-1
Consume Data <- '202.89.233.104'
Main Thread:true, Thread Name:main

flatMap进阶使用

我们从上面的输出结果可以看出，效果和使用map操作符的效果是一样。
我们同时也发现线程的名称（Thread Name）都是 RxCachedThreadScheduler-1 ，说明他们是通过一个线程来完成所有的任务的。
如果任务很多，仅仅通过一个线程去做，效率上是不是有点低呢？如果我想使用多个线程来完成这些任务该怎么做呢？
很简单，只需要在创建Observable的时候加上subscribeOn(Schedulers.io()) 即可。完整代码如下：

//根据主机获取ip
    private Observable createIpObservable(final String url) {
        return Observable.create(new Observable.OnSubscribe() {
            @Override
            public void call(Subscriber subscriber) {
                try {
                    String ip = getIPByUrl(url);
                    subscriber.onNext(ip);
                    printLog(tvLogs, "Emit Data -> ",url+" : " +ip);
                } catch (MalformedURLException e) {
                    e.printStackTrace();
                    //subscriber.onError(e);
                    subscriber.onNext(null);
                } catch (UnknownHostException e) {
                    e.printStackTrace();
                    //subscriber.onError(e);
                    subscriber.onNext(null);
                }
                subscriber.onCompleted();
            }
        })
        .subscribeOn(Schedulers.io());

看下运行结果：

Consume Data <- ‘202.89.233.103’ Main Thread:true, Thread Name:main Emit Data -> ‘[https://www.bing.com/](https://www.bing.com/) : 202.89.233.103’ Main Thread:false, Thread Name:RxCachedThreadScheduler-8
Emit Data -> ‘[http://www.google.com/](http://www.google.com/) : 216.58.203.36’ Main Thread:false, Thread Name:RxCachedThreadScheduler-7 Consume Data <- ‘216.58.203.36’ Main Thread:true, Thread Name:main
Emit Data -> ‘[http://www.baidu.com/](http://www.baidu.com/) : 115.239.211.112’ Main Thread:false, Thread Name:RxCachedThreadScheduler-6 Consume Data <- ‘115.239.211.112’ Main Thread:true, Thread Name:main 

从运行可以看出，执行完成任务的不是一个线程了，而是三个不同的线程 RxCachedThreadScheduler-8 、RxCachedThreadScheduler-7、RxCachedThreadScheduler-6 。

但是发现一个问题，输出的结果的顺序乱了，不是我们输入的baidu.com/google.com/bing.com顺序了。

那怎么办呢？

这时候concatMap操作符就闪亮登场了，下一篇将介绍concatMap操作符的用法。