请仔细阅读这篇文章以获得一个清晰的概念，

map vs flatMap:

要从列表中返回每个单词的长度，我们将执行如下操作。

简短版本如下

当我们收集两个列表时，如下所示

没有flat map =>[1,2]，[1,1] =>[[1,2]，[1,1]]这里在一个列表中放置了两个列表，因此输出将是包含列表的列表

使用flat map =>[1,2]，[1,1] =>[1,2,1,1]，这里两个列表被平铺，只有值被放在列表中，因此输出将是只包含元素的列表

基本上，它将所有对象合并为一个

##详细版本已给出如下:-

例如:-考虑一个列表[" STACK "， " OOOVVVER "]，我们试图返回一个列表像[" STACKOVER "](从该列表中只返回唯一的字母) 最初，我们将执行如下操作，从[" STACK "， " OOOVVVER "]返回一个列表[" STACKOVER "]

public class WordMap {
  public static void main(String[] args) {
    List<String> lst = Arrays.asList("STACK","OOOVER");
    lst.stream().map(w->w.split("")).distinct().collect(Collectors.toList());
  }
}

这里的问题是，传递给map方法的Lambda为每个单词返回一个字符串数组，因此map方法返回的流实际上是流类型，但我们需要的是流来表示字符流，下面的图像说明了这个问题。

图一:

你可能会想，我们可以用flatmap来解决这个问题，让我们看看如何用map和arrays。stream来解决这个问题 首先，你需要一个字符流而不是数组流。有一个叫做Arrays.stream()的方法，它将接受一个数组并生成一个流，例如:

String[] arrayOfWords = {"STACK", "OOOVVVER"};
Stream<String> streamOfWords = Arrays.stream(arrayOfWords);
streamOfWords.map(s->s.split("")) //Converting word in to array of letters
    .map(Arrays::stream).distinct() //Make array in to separate stream
    .collect(Collectors.toList());

上面的方法仍然不起作用，因为我们现在得到了一个流的列表(更准确地说，流>)。相反，我们必须首先将每个单词转换为一个单独的字母数组，然后将每个数组转换为一个单独的流

通过使用flatMap，我们应该能够修复这个问题如下:

String[] arrayOfWords = {"STACK", "OOOVVVER"};
Stream<String> streamOfWords = Arrays.stream(arrayOfWords);
streamOfWords.map(s->s.split("")) //Converting word in to array of letters
    .flatMap(Arrays::stream).distinct() //flattens each generated stream in to a single stream
    .collect(Collectors.toList());

flatMap不是用流而是用流的内容来映射每个数组。在使用map(Arrays::stream)时生成的所有单独流被合并成一个流。图B说明了使用flatMap方法的效果。将其与图A中的map进行比较。 图B

flatMap方法允许您用另一个流替换流的每个值，然后将所有生成的流连接到单个流中。

如果你熟悉c#也可以很好的类比。基本上c# Select类似于java map和c# SelectMany java flatMap。对于集合，同样适用于Kotlin。

通过阅读所有的信息，简单的理解方法是:

如果你有一个元素的平面列表，请使用map: [0,1,2,3,4,5] 如果你有一个元素的列表，请使用flatMap:[[1,3,5]，[2,4,6]]。这意味着，在映射操作应用于每个元素之前，您的列表需要被平铺

map和flatMap都可以应用于一个<T>的流，它们都返回一个<R>的流。不同之处在于map操作为每个输入值生成一个输出值，而flatMap操作为每个输入值生成任意数量(零个或多个)值。

这反映在每个操作的参数中。

map操作接受一个函数，该函数针对输入流中的每个值被调用，并产生一个结果值，该结果值被发送到输出流。

The flatMap operation takes a function that conceptually wants to consume one value and produce an arbitrary number of values. However, in Java, it's cumbersome for a method to return an arbitrary number of values, since methods can return only zero or one value. One could imagine an API where the mapper function for flatMap takes a value and returns an array or a List of values, which are then sent to the output. Given that this is the streams library, a particularly apt way to represent an arbitrary number of return values is for the mapper function itself to return a stream! The values from the stream returned by the mapper are drained from the stream and are passed to the output stream. The "clumps" of values returned by each call to the mapper function are not distinguished at all in the output stream, thus the output is said to have been "flattened."

典型的用法是flatMap的mapper函数返回Stream.empty()，如果它想发送零值，或者类似于Stream。(a, b, c)如果它想返回几个值。当然，任何流都可以返回。

map()和flatMap()

map ()

只接受一个函数<T, R>一个lambda参数，其中T是元素，R是使用T构建的返回元素。最后，我们将有一个带有类型为R的对象的流。一个简单的例子可以是:

Stream
  .of(1,2,3,4,5)
  .map(myInt -> "preFix_"+myInt)
  .forEach(System.out::println);

它只是取Type Integer的元素1到5，使用每个元素从String类型中构建一个值为“prefix_”+integer_value的新元素，并打印出来。

flatMap ()

知道flatMap()接受一个函数F<T, R> where是很有用的

T is a type from which a Stream can be built from/with. It can be a List (T.stream()), an array (Arrays.stream(someArray)), etc.. anything that from which a Stream can be with/or form. in the example below each dev has many languages, so dev. Languages is a List and will use a lambda parameter. R is the resulting Stream that will be built using T. Knowing that we have many instances of T, we will naturally have many Streams from R. All these Streams from Type R will now be combined into one single 'flat' Stream from Type R.

例子

Bachiri Taoufiq的例子(见这里的答案)1简单易懂。为了清晰起见，假设我们有一个开发团队:

dev_team = {dev_1,dev_2,dev_3}

，每个开发人员都懂多种语言:

dev_1 = {lang_a,lang_b,lang_c},
dev_2 = {lang_d},
dev_3 = {lang_e,lang_f}

在dev_team上应用Stream.map()来获取每个开发人员的语言:

dev_team.map(dev -> dev.getLanguages())

会给你这样的结构:

{ 
  {lang_a,lang_b,lang_c},
  {lang_d},
  {lang_e,lang_f}
}

它基本上是一个List<List<Languages>> /Object[Languages[]]。不是很漂亮，也不像java8 !!

使用Stream.flatMap()，你可以“扁平化”的东西，因为它采取上述结构 并将其转换为{lang_a, lang_b, lang_c, lang_d, lang_e, lang_f}，基本上可以作为List<Languages>/Language[]/etc…

所以最后，你的代码会像这样更有意义:

dev_team
   .stream()    /* {dev_1,dev_2,dev_3} */
   .map(dev -> dev.getLanguages()) /* {{lang_a,...,lang_c},{lang_d}{lang_e,lang_f}}} */
   .flatMap(languages ->  languages.stream()) /* {lang_a,...,lang_d, lang_e, lang_f} */
   .doWhateverWithYourNewStreamHere();

或者仅仅是:

dev_team
       .stream()    /* {dev_1,dev_2,dev_3} */
       .flatMap(dev -> dev.getLanguages().stream()) /* {lang_a,...,lang_d, lang_e, lang_f} */
       .doWhateverWithYourNewStreamHere();

何时使用map()和flatMap():

Use map() when each element of type T from your stream is supposed to be mapped/transformed to a single element of type R. The result is a mapping of type (1 start element -> 1 end element) and new stream of elements of type R is returned. Use flatMap() when each element of type T from your stream is supposed to mapped/transformed to a Collections of elements of type R. The result is a mapping of type (1 start element -> n end elements). These Collections are then merged (or flattened) to a new stream of elements of type R. This is useful for example to represent nested loops.

Java 8 之前：

List<Foo> myFoos = new ArrayList<Foo>();
    for(Foo foo: myFoos){
        for(Bar bar:  foo.getMyBars()){
            System.out.println(bar.getMyName());
        }
    }

后Java 8

myFoos
    .stream()
    .flatMap(foo -> foo.getMyBars().stream())
    .forEach(bar -> System.out.println(bar.getMyName()));

Oracle关于Optional的文章强调了map和flatmap的区别:

String version = computer.map(Computer::getSoundcard)
                  .map(Soundcard::getUSB)
                  .map(USB::getVersion)
                  .orElse("UNKNOWN");

Unfortunately, this code doesn't compile. Why? The variable computer is of type Optional<Computer>, so it is perfectly correct to call the map method. However, getSoundcard() returns an object of type Optional. This means the result of the map operation is an object of type Optional<Optional<Soundcard>>. As a result, the call to getUSB() is invalid because the outermost Optional contains as its value another Optional, which of course doesn't support the getUSB() method. With streams, the flatMap method takes a function as an argument, which returns another stream. This function is applied to each element of a stream, which would result in a stream of streams. However, flatMap has the effect of replacing each generated stream by the contents of that stream. In other words, all the separate streams that are generated by the function get amalgamated or "flattened" into one single stream. What we want here is something similar, but we want to "flatten" a two-level Optional into one. Optional also supports a flatMap method. Its purpose is to apply the transformation function on the value of an Optional (just like the map operation does) and then flatten the resulting two-level Optional into a single one. So, to make our code correct, we need to rewrite it as follows using flatMap:

String version = computer.flatMap(Computer::getSoundcard)
                   .flatMap(Soundcard::getUSB)
                   .map(USB::getVersion)
                   .orElse("UNKNOWN");

第一个flatMap确保返回Optional<Soundcard> 而不是一个Optional<Optional<Soundcard>>，和第二个flatMap 实现相同的目的，返回Optional<USB>。注意 第三个调用只需要一个map()，因为getVersion()返回一个 字符串而不是可选对象。

http://www.oracle.com/technetwork/articles/java/java8-optional-2175753.html