1、Stream的创建
1.1、通过集合创建流
List<String> list = Arrays.asList("a", "b", "c", "d");
//创建顺序流(顺序执行)
Stream<String> stream = list.stream();
//创建并行流(多线程并行执行,速度快)
Stream<String> parallelStream = list.parallelStream();
1.2、通过数组创建流
int[] array = {1,2,3};
IntStream stream1 = Arrays.stream(array);
1.3、通过Stream的静态方法of()
Stream<Integer> stream2 = Stream.of(1, 2, 3);
1.4、通过Stream的静态方法iterate()、generate()创建无限流
//iterate(final T seed, final UnaryOperator<T> f)
Stream<Integer> stream3 = Stream.iterate(0, x -> x + 5).limit(5);
stream3.forEach(System.out::println);
//generate(Supplier<? extends T> s)
Stream<Double> stream4 = Stream.generate(Math::random).limit(3);
stream4.forEach(System.out::println);
输出结果:
0
5
10
15
20
0.777749700073161
0.459997520455924
0.6574387383079919
2、Stream的使用
2.1、筛选(filter)
筛选Integer集合大于3的元素,并打印
List<Integer> list = Arrays.asList(1, 2, 3, 4, 5, 6);
list.stream().filter(o -> o > 3).forEach(System.out::println);
输出结果:
4
5
6
2.2、聚合(max/min/count)
获取集合中最长、最短的元素
List<String> list = Arrays.asList("java", "php", "oracle", "mysql");
Optional<String> max = list.stream().max(Comparator.comparing(String::length));
Optional<String> min = list.stream().min(Comparator.comparing(String::length));
System.out.println("最长的字符串:"+max.get());
System.out.println("最短的字符串:"+min.get());
输出结果:
最长的字符串:oracle
最短的字符串:php
获取集合大于3的元素个数
List<Integer> list = Arrays.asList(1, 2, 3, 4, 5, 6);
long count = list.stream().filter(o -> o > 3).count();
System.out.println("list中大于3的元素个数:"+count);
输出结果:
list中大于3的元素个数:3
2.3、映射(map/flatMap)
将集合所有字母改为大写
List<String> list = Arrays.asList("java", "php", "oracle", "mysql");
//map(Function<? super T, ? extends R> mapper):放入一种类型,返回另外一种类型
list.stream().map(String::toUpperCase).forEach(System.out::println);
输出结果:
JAVA
PHP
ORACLE
MYSQL
将两个字符数组合并成一个新的字符数组
List<String> list = Arrays.asList("m,k,l,a", "1,3,5,7");
List<String> listNew = list.stream().flatMap(s -> {
// 将每个元素转换成一个stream
String[] split = s.split(",");
Stream<String> s2 = Arrays.stream(split);
return s2;
}).collect(Collectors.toList());
System.out.println("处理前的集合:" + list);
System.out.println("处理后的集合:" + listNew);
输出结果:
处理前的集合:[m-k-l-a, 1-3-5]
处理后的集合:[m, k, l, a, 1, 3, 5]
2.4、归约(reduce)
归约,也称缩减,顾名思义,是把一个流缩减成一个值,能实现对集合求和、求乘积和求最值操作。
案例一:求Integer集合的元素之和、乘积和最大值。
public class StreamTest {
public static void main(String[] args) {
List<Integer> list = Arrays.asList(1, 3, 2, 8, 11, 4);
// 求和方式1
Optional<Integer> sum = list.stream().reduce((x, y) -> x + y);
// 求和方式2
Optional<Integer> sum2 = list.stream().reduce(Integer::sum);
// 求和方式3
Integer sum3 = list.stream().reduce(0, Integer::sum);
// 求乘积
Optional<Integer> product = list.stream().reduce((x, y) -> x * y);
// 求最大值方式1
Optional<Integer> max = list.stream().reduce((x, y) -> x > y ? x : y);
// 求最大值写法2
Integer max2 = list.stream().reduce(1, Integer::max);
System.out.println("list求和:" + sum.get() + "," + sum2.get() + "," + sum3);
System.out.println("list求积:" + product.get());
System.out.println("list求和:" + max.get() + "," + max2);
}
}
案例二:求所有员工的工资之和和最高工资。
public class StreamTest {
public static void main(String[] args) {
List<Person> personList = new ArrayList<Person>();
personList.add(new Person("Tom", 8900, 23, "male", "New York"));
personList.add(new Person("Jack", 7000, 25, "male", "Washington"));
personList.add(new Person("Lily", 7800, 21, "female", "Washington"));
personList.add(new Person("Anni", 8200, 24, "female", "New York"));
personList.add(new Person("Owen", 9500, 25, "male", "New York"));
personList.add(new Person("Alisa", 7900, 26, "female", "New York"));
// 求工资之和方式1:
Optional<Integer> sumSalary = personList.stream().map(Person::getSalary).reduce(Integer::sum);
// 求工资之和方式2:
Integer sumSalary2 = personList.stream().reduce(0, (sum, p) -> sum += p.getSalary(),
(sum1, sum2) -> sum1 + sum2);
// 求工资之和方式3:
Integer sumSalary3 = personList.stream().reduce(0, (sum, p) -> sum += p.getSalary(), Integer::sum);
// 求最高工资方式1:
Integer maxSalary = personList.stream().reduce(0, (max, p) -> max > p.getSalary() ? max : p.getSalary(),
Integer::max);
// 求最高工资方式2:
Integer maxSalary2 = personList.stream().reduce(0, (max, p) -> max > p.getSalary() ? max : p.getSalary(),
(max1, max2) -> max1 > max2 ? max1 : max2);
System.out.println("工资之和:" + sumSalary.get() + "," + sumSalary2 + "," + sumSalary3);
System.out.println("最高工资:" + maxSalary + "," + maxSalary2);
}
}
2.5、收集(collect)
就是把一个流收集起来,最终可以是收集成一个值也可以收集成一个新的集合。
2.5.1、归集(toList/toSet/toMap)
public class StreamTest {
public static void main(String[] args) {
List<Integer> list = Arrays.asList(1, 6, 3, 4, 6, 7, 9, 6, 20);
List<Integer> listNew = list.stream().filter(x -> x % 2 == 0).collect(Collectors.toList());
Set<Integer> set = list.stream().filter(x -> x % 2 == 0).collect(Collectors.toSet());
List<Person> personList = new ArrayList<Person>();
personList.add(new Person("Tom", 8900, 23, "male", "New York"));
personList.add(new Person("Jack", 7000, 25, "male", "Washington"));
personList.add(new Person("Lily", 7800, 21, "female", "Washington"));
personList.add(new Person("Anni", 8200, 24, "female", "New York"));
Map<?, Person> map = personList.stream().filter(p -> p.getSalary() > 8000)
.collect(Collectors.toMap(Person::getName, p -> p));
System.out.println("toList:" + listNew);
System.out.println("toSet:" + set);
System.out.println("toMap:" + map);
}
}
输出结果:
toList:[6, 4, 6, 6, 20]
toSet:[4, 20, 6]
toMap:{Tom=mutest.Person@5fd0d5ae, Anni=mutest.Person@2d98a335}
2.5.2、统计(count/averaging)
统计员工人数、平均工资、工资总额、最高工资。
public class StreamTest {
public static void main(String[] args) {
List<Person> personList = new ArrayList<Person>();
personList.add(new Person("Tom", 8900, 23, "male", "New York"));
personList.add(new Person("Jack", 7000, 25, "male", "Washington"));
personList.add(new Person("Lily", 7800, 21, "female", "Washington"));
// 求总数
Long count = personList.stream().collect(Collectors.counting());
// 求平均工资
Double average = personList.stream().collect(Collectors.averagingDouble(Person::getSalary));
// 求最高工资
Optional<Integer> max = personList.stream().map(Person::getSalary).collect(Collectors.maxBy(Integer::compare));
// 求工资之和
Integer sum = personList.stream().collect(Collectors.summingInt(Person::getSalary));
// 一次性统计所有信息
DoubleSummaryStatistics collect = personList.stream().collect(Collectors.summarizingDouble(Person::getSalary));
System.out.println("员工总数:" + count);
System.out.println("员工平均工资:" + average);
System.out.println("员工工资总和:" + sum);
System.out.println("员工工资所有统计:" + collect);
}
}
输出结果:
员工总数:3
员工平均工资:7900.0
员工工资总和:23700
员工工资所有统计:DoubleSummaryStatistics{count=3, sum=23700.000000,min=7000.000000, average=7900.000000, max=8900.000000}
2.5.3、分组(partitioningBy/groupingBy)
将员工按薪资是否高于8000分为两部分;将员工按性别和地区分组
public class StreamTest {
public static void main(String[] args) {
List<Person> personList = new ArrayList<Person>();
personList.add(new Person("Tom", 8900, "male", "New York"));
personList.add(new Person("Jack", 7000, "male", "Washington"));
personList.add(new Person("Lily", 7800, "female", "Washington"));
personList.add(new Person("Anni", 8200, "female", "New York"));
personList.add(new Person("Owen", 9500, "male", "New York"));
personList.add(new Person("Alisa", 7900, "female", "New York"));
// 将员工按薪资是否高于8000分组
Map<Boolean, List<Person>> part = personList.stream().collect(Collectors.partitioningBy(x -> x.getSalary() > 8000));
// 将员工按性别分组
Map<String, List<Person>> group = personList.stream().collect(Collectors.groupingBy(Person::getSex));
// 将员工先按性别分组,再按地区分组
Map<String, Map<String, List<Person>>> group2 = personList.stream().collect(Collectors.groupingBy(Person::getSex, Collectors.groupingBy(Person::getArea)));
System.out.println("员工按薪资是否大于8000分组情况:" + part);
System.out.println("员工按性别分组情况:" + group);
System.out.println("员工按性别、地区:" + group2);
}
}
输出结果:
员工按薪资是否大于8000分组情况:{false=[mutest.Person@2d98a335, mutest.Person@16b98e56, mutest.Person@7ef20235], true=[mutest.Person@27d6c5e0, mutest.Person@4f3f5b24, mutest.Person@15aeb7ab]}
员工按性别分组情况:{female=[mutest.Person@16b98e56, mutest.Person@4f3f5b24, mutest.Person@7ef20235], male=[mutest.Person@27d6c5e0, mutest.Person@2d98a335, mutest.Person@15aeb7ab]}
员工按性别、地区:{female={New York=[mutest.Person@4f3f5b24, mutest.Person@7ef20235], Washington=[mutest.Person@16b98e56]}, male={New York=[mutest.Person@27d6c5e0, mutest.Person@15aeb7ab], Washington=[mutest.Person@2d98a335]}}
2.5.4、接合(joining)
joining可以将stream中的元素用特定的连接符(没有的话,则直接连接)连接成一个字符串。
public class StreamTest {
public static void main(String[] args) {
List<Person> personList = new ArrayList<Person>();
personList.add(new Person("Tom", 8900, 23, "male", "New York"));
personList.add(new Person("Jack", 7000, 25, "male", "Washington"));
personList.add(new Person("Lily", 7800, 21, "female", "Washington"));
String names = personList.stream().map(p -> p.getName()).collect(Collectors.joining(","));
System.out.println("所有员工的姓名:" + names);
List<String> list = Arrays.asList("A", "B", "C");
String string = list.stream().collect(Collectors.joining("-"));
System.out.println("拼接后的字符串:" + string);
}
}
输出结果:
所有员工的姓名:Tom,Jack,Lily
拼接后的字符串:A-B-C
2.6、排序(sorted)
- sorted():自然排序,流中元素需实现Comparable接口
- sorted(Comparator com):Comparator排序器自定义排序
将员工按工资由高到低(工资一样则按年龄由大到小)排序
public class StreamTest {
public static void main(String[] args) {
List<Person> personList = new ArrayList<Person>();
personList.add(new Person("Sherry", 9000, 24, "female", "New York"));
personList.add(new Person("Tom", 8900, 22, "male", "Washington"));
personList.add(new Person("Jack", 9000, 25, "male", "Washington"));
personList.add(new Person("Lily", 8800, 26, "male", "New York"));
personList.add(new Person("Alisa", 9000, 26, "female", "New York"));
// 按工资升序排序(自然排序)
List<String> newList = personList.stream().sorted(Comparator.comparing(Person::getSalary)).map(Person::getName)
.collect(Collectors.toList());
// 按工资倒序排序
List<String> newList2 = personList.stream().sorted(Comparator.comparing(Person::getSalary).reversed())
.map(Person::getName).collect(Collectors.toList());
// 先按工资再按年龄升序排序
List<String> newList3 = personList.stream()
.sorted(Comparator.comparing(Person::getSalary).thenComparing(Person::getAge)).map(Person::getName)
.collect(Collectors.toList());
// 先按工资再按年龄自定义排序(降序)
List<String> newList4 = personList.stream().sorted((p1, p2) -> {
if (p1.getSalary() == p2.getSalary()) {
return p2.getAge() - p1.getAge();
} else {
return p2.getSalary() - p1.getSalary();
}
}).map(Person::getName).collect(Collectors.toList());
System.out.println("按工资升序排序:" + newList);
System.out.println("按工资降序排序:" + newList2);
System.out.println("先按工资再按年龄升序排序:" + newList3);
System.out.println("先按工资再按年龄自定义降序排序:" + newList4);
}
}
2.7、提取/组合
流也可以进行合并、去重、限制、跳过等操作。
public class StreamTest {
public static void main(String[] args) {
String[] arr1 = { "a", "b", "c", "d" };
String[] arr2 = { "d", "e", "f", "g" };
Stream<String> stream1 = Stream.of(arr1);
Stream<String> stream2 = Stream.of(arr2);
// concat:合并两个流 distinct:去重
List<String> newList = Stream.concat(stream1, stream2).distinct().collect(Collectors.toList());
// limit:限制从流中获得前n个数据
List<Integer> collect = Stream.iterate(1, x -> x + 2).limit(10).collect(Collectors.toList());
// skip:跳过前n个数据
List<Integer> collect2 = Stream.iterate(1, x -> x + 2).skip(1).limit(5).collect(Collectors.toList());
System.out.println("流合并:" + newList);
System.out.println("limit:" + collect);
System.out.println("skip:" + collect2);
}
}
输出结果:
流合并:[a, b, c, d, e, f, g]
limit:[1, 3, 5, 7, 9, 11, 13, 15, 17, 19]
skip:[3, 5, 7, 9, 11]
2.8、peek 和 forEach
相同点: peek和forEach都是遍历流内对象并且对对象进行一定的操作
不同点: forEach 返回void 结束Stream操作,peek 会继续返回Stream对象
3、Optional 类
public class Java8Tester {
public static void main(String args[]){
Java8Tester java8Tester = new Java8Tester();
Integer value1 = null;
Integer value2 = new Integer(10);
// Optional.ofNullable - 允许传递为 null 参数
Optional<Integer> a = Optional.ofNullable(value1);
// Optional.of - 如果传递的参数是 null,抛出异常 NullPointerException
Optional<Integer> b = Optional.of(value2);
System.out.println(java8Tester.sum(a,b));
}
public Integer sum(Optional<Integer> a, Optional<Integer> b){
// Optional.isPresent - 判断值是否存在
System.out.println("第一个参数值存在: " + a.isPresent());
System.out.println("第二个参数值存在: " + b.isPresent());
// Optional.orElse - 如果值存在,返回它,否则返回默认值
Integer value1 = a.orElse(new Integer(0));
//Optional.get - 获取值,值需要存在
Integer value2 = b.get();
return value1 + value2;
}
}
输出结果:
$ javac Java8Tester.java
$ java Java8Tester
第一个参数值存在: false
第二个参数值存在: true
10
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