Java8中Lambda表达式

Java8中Lambda表达式的10个例子
例1 用Lambda表达式实现Runnable接口

//Before Java 8:
new Thread(new Runnable() {
@Override
public void run() {
    System.out.println("Before Java8, too much code for too little to do");
}
}).start();
//Java 8 way:
new Thread( () -> System.out.println("In Java8, Lambda expression rocks !!") ).start();

//Before Java 8:
new Thread(new Runnable() {
@Override
public void run() {
	System.out.println("Before Java8, too much code for too little to do");
}
}).start();
//Java 8 way:
new Thread( () -> System.out.println("In Java8, Lambda expression rocks !!") ).start();

输出:
too much code, for too little to do
Lambda expression rocks !!
这个例子使我们学到了java8中Lambda表达式的书写方式：
(参数) -> 表达式
(参数) -> 语句
(参数) -> { 语句 }
例如，如果你的方法只是在控制台打印信息，则可以这么写：

() -> System.out.println("Hello Lambda Expressions");

() -> System.out.println("Hello Lambda Expressions");

如果你的方法接收两个参数，那么：

(int even, int odd) -> even + odd

(int even, int odd) -> even + odd

顺带提一句，一般来说在Lambda表达式中要尽量保持变量的简洁性。这会使你的代码简短而能保持在一行之内。所以像上面的代码可以选择变量名类似a,b或者x,y之类的，比起even和odd来会更好。

例2 用Lambda表达式写事件监听程序
要是你用过Swing API，那就少不了事件监听代码，这是使用匿名类的经典例子。现在我们可以用Lambda表达式来抒写更好的事件处理代码。

// Before Java 8:
JButton show = new JButton("Show");
show.addActionListener(new ActionListener() {
    @Override
    public void actionPerformed(ActionEvent e) {
        System.out.println("Event handling without lambda expression is boring");
    }
});
// Java 8 way:
show.addActionListener((e) -> {
    System.out.println("Light, Camera, Action !! Lambda expressions Rocks");
});

// Before Java 8:
JButton show = new JButton("Show");
show.addActionListener(new ActionListener() {
	@Override
	public void actionPerformed(ActionEvent e) {
		System.out.println("Event handling without lambda expression is boring");
	}
});
// Java 8 way:
show.addActionListener((e) -> {
	System.out.println("Light, Camera, Action !! Lambda expressions Rocks");
});

另外一个常用匿名类的地方是给Collections.sort()方法提供自定义的Comparator接口实现。这个地方也可以用Lambda表达式。

例3 用Lambda表达式进行List迭代

//Prior Java 8 :
List features = Arrays.asList("Lambdas", "Default Method", "Stream API", "Date and Time API");
for (String feature : features) {
    System.out.println(feature);
}
//In Java 8:
List features = Arrays.asList("Lambdas", "Default Method", "Stream API", "Date and Time API");
features.forEach(n -> System.out.println(n));

//Prior Java 8 :
List features = Arrays.asList("Lambdas", "Default Method", "Stream API", "Date and Time API");
for (String feature : features) {
    System.out.println(feature);
}
//In Java 8:
List features = Arrays.asList("Lambdas", "Default Method", "Stream API", "Date and Time API");
features.forEach(n -> System.out.println(n));

// 用java8的方法引用更好，方法引用由::(双冒号)操作符来完成,看起来像c++中的作用域操作符

features.forEach(System.out::println);

features.forEach(System.out::println);

输出:
Lambdas
Default Method
Stream API
Date and Time API

例4 使用Lambda表达式和函数式接口Predicate
除了提供函数式编程语言级别的支持外，java8同时也新增了一个新的包java.util.function。其中包含了许多类来支持java函数式编程。其中之一是Predicate接口，使用这个接口和lamb表达式就可以以更少的代码为API方法添加更多的动态行为。
以下是Predicate的使用范例，展示了过滤集合数据的许多共性。

public static void main(args[]){
    List languages = Arrays.asList("Java", "Scala", "C++", "Haskell", "Lisp");
    System.out.println("Languages which starts with J :");
    filter(languages, (str)->str.startsWith("J"));
    System.out.println("Languages which ends with a ");
    filter(languages, (str)->str.endsWith("a"));
    System.out.println("Print all languages :");
    filter(languages, (str)->true);
    System.out.println("Print no language : ");
    filter(languages, (str)->false);
    System.out.println("Print language whose length greater than 4:");
    filter(languages, (str)->str.length() > 4);
}
public static void filter(List names, Predicate condition) {
    for(String name: names) {
        if(condition.test(name)) {
            System.out.println(name + " ");
        }
    }
}

public static void main(args[]){
    List languages = Arrays.asList("Java", "Scala", "C++", "Haskell", "Lisp");
    System.out.println("Languages which starts with J :");
    filter(languages, (str)->str.startsWith("J"));
    System.out.println("Languages which ends with a ");
    filter(languages, (str)->str.endsWith("a"));
    System.out.println("Print all languages :");
    filter(languages, (str)->true);
    System.out.println("Print no language : ");
    filter(languages, (str)->false);
    System.out.println("Print language whose length greater than 4:");
    filter(languages, (str)->str.length() > 4);
}
public static void filter(List names, Predicate condition) {
    for(String name: names) {
        if(condition.test(name)) {
            System.out.println(name + " ");
        }
    }
}

输出:
Languages which starts with J :
Java
Languages which ends with a
Java
Scala
Print all languages :
Java
Scala
C++
Haskell
Lisp
Print no language :
Print language whose length greater than 4:
Scala
Haskell

//更佳的方式
public static void filter(List names, Predicate condition) {
    names.stream().filter((name) -> (condition.test(name))).forEach((name) -> {
        System.out.println(name + " ");
    });
}

//更佳的方式
public static void filter(List names, Predicate condition) {
	names.stream().filter((name) -> (condition.test(name))).forEach((name) -> {
		System.out.println(name + " ");
	});
}

可以看到Stream API的filter方法也接受一个Predicate，意味着可以用内联代码直接替换我们自定义的filter()方法。这就是Lambda表达式的威力所在。除此之外Predicate接口也可以测试多个条件，将会在下面的例子中加以说明。

例5: Lambda表达式结合Predicate
就像上个例子所说，Predicate允许组合两个以上的条件，它提供了类似于逻辑与和或的操作and(),or()和xor()，这些方法可以用来组合传递到filter方法中的多个条件。例如为了获取所有以J开头并有四个字符长度的语言，可以定义两个单独的Predicate实例覆盖每个条件然后用and方法将他们组合在一起。看例子：

Predicate<String> startsWithJ = (n) -> n.startsWith("J");
Predicate<String> fourLetterLong = (n) -> n.length() == 4;
names.stream().filter(startsWithJ.and(fourLetterLong)).forEach((n) -> System.out.print("\nName, which starts with 'J' and four letter long is : " + n));

Predicate<String> startsWithJ = (n) -> n.startsWith("J");
Predicate<String> fourLetterLong = (n) -> n.length() == 4;
names.stream().filter(startsWithJ.and(fourLetterLong)).forEach((n) -> System.out.print("\nName, which starts with 'J' and four letter long is : " + n));

类似可以用or或者xor。这个例子也强调了单独用或者按需组合用Predicate的重要性。简而言之用Predicate和Lambda表达式的优势你可以写的更少做得更多。

例6 Map和Reduce的例子
6.1 Map
在这个例子中，我们要将costBeforeTax的每个元素以加上他们的增值税。传递一个Lambda表达式给map方法使之应用于每个元素，之后在用forEach打印结果。

// Without lambda expressions:
List costBeforeTax = Arrays.asList(100, 200, 300, 400, 500);
for (Integer cost : costBeforeTax) {
    double price = cost + .12*cost;
    System.out.println(price);
}
// With Lambda expression:
List costBeforeTax = Arrays.asList(100, 200, 300, 400, 500);
costBeforeTax.stream().map((cost) -> cost + .12*cost).forEach(System.out::println);

// Without lambda expressions:
List costBeforeTax = Arrays.asList(100, 200, 300, 400, 500);
for (Integer cost : costBeforeTax) {
	double price = cost + .12*cost;
	System.out.println(price);
} 
// With Lambda expression:
List costBeforeTax = Arrays.asList(100, 200, 300, 400, 500);
costBeforeTax.stream().map((cost) -> cost + .12*cost).forEach(System.out::println);

输出
112.0
224.0
336.0
448.0
560.0
112.0
224.0
336.0
448.0
560.0
6.2 Reduce
还有另外一个函数reduce可以将所有值转换为一个值。map跟reduce操作是函数式编程的核心，reduce也被称作折叠操作。reduce并不是一种新的操作，在SQL中我们用的一些聚集函数比如sum，avg，count等他们实际上也是reduce操作，因为他们也是将多个值进行操作然后返回一个值。Stream API定义了reduce函数，可以接受一个Lambda表达式然后组合所有值。Stream类中像IntStream都有内置的方法像average(), count(), sum(), mapToLong(), mapToDouble()等转换方法。我们可以用内置的方法也可以自定义。

// Old way:
List costBeforeTax = Arrays.asList(100, 200, 300, 400, 500);
double total = 0;
for (Integer cost : costBeforeTax) {
    double price = cost + .12*cost;
    total = total + price;
}
System.out.println("Total : " + total);
// New way:
List costBeforeTax = Arrays.asList(100, 200, 300, 400, 500);
double bill = costBeforeTax.stream().map((cost) -> cost + .12*cost).reduce((sum, cost) -> sum
+ cost).get();
System.out.println("Total : " + bill);

// Old way:
List costBeforeTax = Arrays.asList(100, 200, 300, 400, 500);
double total = 0;
for (Integer cost : costBeforeTax) {
	double price = cost + .12*cost;
	total = total + price;
}
System.out.println("Total : " + total);
// New way:
List costBeforeTax = Arrays.asList(100, 200, 300, 400, 500);
double bill = costBeforeTax.stream().map((cost) -> cost + .12*cost).reduce((sum, cost) -> sum
+ cost).get();
System.out.println("Total : " + bill);

输出
Total : 1680.0
Total : 1680.0

例7 用filter创建一个字符串List
在java开发中对大的集合进行过滤是常用的操作。用Lambda表达式和Stream API会让操作变得简单易懂。
Stream提供了一个filter()方法，接受一个Predicate对象。这意味着可以传递一个Lambda表达式作为过滤逻辑，看例子:

//创建一个长度大于两个字符的字符串List
List<String> filtered = strList.stream().filter(x -> x.length()>
2).collect(Collectors.toList());
System.out.printf("Original List : %s, filtered list : %s %n", strList, filtered);

//创建一个长度大于两个字符的字符串List
List<String> filtered = strList.stream().filter(x -> x.length()>
2).collect(Collectors.toList());
System.out.printf("Original List : %s, filtered list : %s %n", strList, filtered);

输出 :
Original List : [abc, , bcd, , defg, jk], filtered list : [abc, bcd, defg]

例8 给每个List元素应用函数
在工作中我们经常会碰到这样的情况：给List中每个元素加以一定的操作例如乘以或者除以某个值等。这些操作用map方法再好不过了，我们可以将转换逻辑以Lambda表达式传给map方法来应用于每个元素：
//将字符串转为大写然后用逗号连起来

List<String> G7 = Arrays.asList("USA", "Japan", "France", "Germany", "Italy","U.K.","Canada");
String G7Countries = G7.stream().map(x -> x.toUpperCase()).collect(Collectors.joining(", "));
System.out.println(G7Countries);

List<String> G7 = Arrays.asList("USA", "Japan", "France", "Germany", "Italy","U.K.","Canada");
String G7Countries = G7.stream().map(x -> x.toUpperCase()).collect(Collectors.joining(", "));
System.out.println(G7Countries);

输出:
USA, JAPAN, FRANCE, GERMANY, ITALY, U.K., CANADA

例9 复制不同值到子列表
本例演示如何利用Stream类的distinct方法过滤重复值到集合中。

List<Integer> numbers = Arrays.asList(9, 10, 3, 4, 7, 3, 4);
List<Integer> distinct = numbers.stream().map( i ->i*i).distinct().collect(Collectors.toList());
System.out.printf("Original List : %s, Square Without duplicates : %s %n", numbers, distinct);

List<Integer> numbers = Arrays.asList(9, 10, 3, 4, 7, 3, 4);
List<Integer> distinct = numbers.stream().map( i ->i*i).distinct().collect(Collectors.toList());
System.out.printf("Original List : %s, Square Without duplicates : %s %n", numbers, distinct);

输出 :
Original List : [9, 10, 3, 4, 7, 3, 4], Square Without duplicates : [81, 100, 9, 16, 49]

例10 计算List中元素的最大，最小，和以及平均值
在Stream类中像IntStream, LongStream and DoubleStream有一个非常有用的方法summaryStattics()，返回IntSummaryStatistics, LongSummaryStatistics or DoubleSummaryStatistics其描述了这个流中元素的统计数据。下面的例子中我们用这个方法来计算一个List中的最大最小值总和以及均值:

List<Integer> primes = Arrays.asList(2, 3, 5, 7, 11, 13, 17, 19, 23, 29);
IntSummaryStatistics stats = primes.stream().mapToInt((x) -> x).summaryStatistics();
System.out.println("Highest prime number in List : " + stats.getMax());
System.out.println("Lowest prime number in List : " + stats.getMin());
System.out.println("Sum of all prime numbers : " + stats.getSum());
System.out.println("Average of all prime numbers : " + stats.getAverage());

List<Integer> primes = Arrays.asList(2, 3, 5, 7, 11, 13, 17, 19, 23, 29);
IntSummaryStatistics stats = primes.stream().mapToInt((x) -> x).summaryStatistics();
System.out.println("Highest prime number in List : " + stats.getMax());
System.out.println("Lowest prime number in List : " + stats.getMin());
System.out.println("Sum of all prime numbers : " + stats.getSum());
System.out.println("Average of all prime numbers : " + stats.getAverage());

输出:
Highest prime number in List : 29
Lowest prime number in List : 2
Sum of all prime numbers : 129
Average of all prime numbers : 12.9