20 個實例玩轉 Java 8 Stream
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1 Stream概述
2 Stream的創(chuàng)建
List<String> list = Arrays.asList("a", "b", "c");
// 創(chuàng)建一個順序流
Stream<String> stream = list.stream();
// 創(chuàng)建一個并行流
Stream<String> parallelStream = list.parallelStream();
int[] array={1,3,5,6,8};
IntStream stream = Arrays.stream(array);
Stream<Integer> stream = Stream.of(1, 2, 3, 4, 5, 6);
Stream<Integer> stream2 = Stream.iterate(0, (x) -> x + 3).limit(4);
stream2.forEach(System.out::println);
Stream<Double> stream3 = Stream.generate(Math::random).limit(3);
stream3.forEach(System.out::println);
Optional<Integer> findFirst = list.stream().parallel().filter(x->x>6).findFirst();
3 Stream的使用
案例使用的員工類
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"));
class Person {
private String name; // 姓名
private int salary; // 薪資
private int age; // 年齡
private String sex; //性別
private String area; // 地區(qū)
// 構造方法
public Person(String name, int salary, int age,String sex,String area) {
this.name = name;
this.salary = salary;
this.age = age;
this.sex = sex;
this.area = area;
}
// 省略了get和set，請自行添加
}
3.1 遍歷/匹配（foreach/find/match）
// import已省略，請自行添加，后面代碼亦是
public class StreamTest {
public static void main(String[] args) {
List<Integer> list = Arrays.asList(7, 6, 9, 3, 8, 2, 1);
// 遍歷輸出符合條件的元素
list.stream().filter(x -> x > 6).forEach(System.out::println);
// 匹配第一個
Optional<Integer> findFirst = list.stream().filter(x -> x > 6).findFirst();
// 匹配任意（適用于并行流）
Optional<Integer> findAny = list.parallelStream().filter(x -> x > 6).findAny();
// 是否包含符合特定條件的元素
boolean anyMatch = list.stream().anyMatch(x -> x < 6);
System.out.println("匹配第一個值：" + findFirst.get());
System.out.println("匹配任意一個值：" + findAny.get());
System.out.println("是否存在大于6的值：" + anyMatch);
}
}
3.2 篩選（filter）
public class StreamTest {
public static void main(String[] args) {
List<Integer> list = Arrays.asList(6, 7, 3, 8, 1, 2, 9);
Stream<Integer> stream = list.stream();
stream.filter(x -> x > 7).forEach(System.out::println);
}
}
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"));
List<String> fiterList = personList.stream().filter(x -> x.getSalary() > 8000).map(Person::getName)
.collect(Collectors.toList());
System.out.print("高于8000的員工姓名：" + fiterList);
}
}
3.3 聚合（max/min/count)
public class StreamTest {
public static void main(String[] args) {
List<String> list = Arrays.asList("adnm", "admmt", "pot", "xbangd", "weoujgsd");
Optional<String> max = list.stream().max(Comparator.comparing(String::length));
System.out.println("最長的字符串：" + max.get());
}
}
public class StreamTest {
public static void main(String[] args) {
List<Integer> list = Arrays.asList(7, 6, 9, 4, 11, 6);
// 自然排序
Optional<Integer> max = list.stream().max(Integer::compareTo);
// 自定義排序
Optional<Integer> max2 = list.stream().max(new Comparator<Integer>() {
@Override
public int compare(Integer o1, Integer o2) {
return o1.compareTo(o2);
}
});
System.out.println("自然排序的最大值：" + max.get());
System.out.println("自定義排序的最大值：" + max2.get());
}
}
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"));
Optional<Person> max = personList.stream().max(Comparator.comparingInt(Person::getSalary));
System.out.println("員工工資最大值：" + max.get().getSalary());
}
}
import java.util.Arrays;
import java.util.List;
public class StreamTest {
public static void main(String[] args) {
List<Integer> list = Arrays.asList(7, 6, 4, 8, 2, 11, 9);
long count = list.stream().filter(x -> x > 6).count();
System.out.println("list中大于6的元素個數：" + count);
}
}
3.4 映射(map/flatMap)
public class StreamTest {
public static void main(String[] args) {
String[] strArr = { "abcd", "bcdd", "defde", "fTr" };
List<String> strList = Arrays.stream(strArr).map(String::toUpperCase).collect(Collectors.toList());
List<Integer> intList = Arrays.asList(1, 3, 5, 7, 9, 11);
List<Integer> intListNew = intList.stream().map(x -> x + 3).collect(Collectors.toList());
System.out.println("每個元素大寫：" + strList);
System.out.println("每個元素+3：" + intListNew);
}
}
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"));
// 不改變原來員工集合的方式
List<Person> personListNew = personList.stream().map(person -> {
Person personNew = new Person(person.getName(), 0, 0, null, null);
personNew.setSalary(person.getSalary() + 10000);
return personNew;
}).collect(Collectors.toList());
System.out.println("一次改動前：" + personList.get(0).getName() + "-->" + personList.get(0).getSalary());
System.out.println("一次改動后：" + personListNew.get(0).getName() + "-->" + personListNew.get(0).getSalary());
// 改變原來員工集合的方式
List<Person> personListNew2 = personList.stream().map(person -> {
person.setSalary(person.getSalary() + 10000);
return person;
}).collect(Collectors.toList());
System.out.println("二次改動前：" + personList.get(0).getName() + "-->" + personListNew.get(0).getSalary());
System.out.println("二次改動后：" + personListNew2.get(0).getName() + "-->" + personListNew.get(0).getSalary());
}
}
public class StreamTest {
public static void main(String[] args) {
List<String> list = Arrays.asList("m,k,l,a", "1,3,5,7");
List<String> listNew = list.stream().flatMap(s -> {
// 將每個元素轉換成一個stream
String[] split = s.split(",");
Stream<String> s2 = Arrays.stream(split);
return s2;
}).collect(Collectors.toList());
System.out.println("處理前的集合：" + list);
System.out.println("處理后的集合：" + listNew);
}
}
3.5 歸約(reduce)
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);
// 求乘積
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);
// 求最大值寫法2
Integer max2 = list.stream().reduce(1, Integer::max);
System.out.println("list求和：" + sum.get() + "," + sum2.get() + "," + sum3);
System.out.println("list求積：" + product.get());
System.out.println("list求和：" + max.get() + "," + max2);
}
}
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"));
// 求工資之和方式1：
Optional<Integer> sumSalary = personList.stream().map(Person::getSalary).reduce(Integer::sum);
// 求工資之和方式2：
Integer sumSalary2 = personList.stream().reduce(0, (sum, p) -> sum += p.getSalary(),
(sum1, sum2) -> sum1 + sum2);
// 求工資之和方式3：
Integer sumSalary3 = personList.stream().reduce(0, (sum, p) -> sum += p.getSalary(), Integer::sum);
// 求最高工資方式1：
Integer maxSalary = personList.stream().reduce(0, (max, p) -> max > p.getSalary() ? max : p.getSalary(),
Integer::max);
// 求最高工資方式2：
Integer maxSalary2 = personList.stream().reduce(0, (max, p) -> max > p.getSalary() ? max : p.getSalary(),
(max1, max2) -> max1 > max2 ? max1 : max2);
System.out.println("工資之和：" + sumSalary.get() + "," + sumSalary2 + "," + sumSalary3);
System.out.println("最高工資：" + maxSalary + "," + maxSalary2);
}
}
3.6 收集(collect)
3.6.1 歸集(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);
}
}
3.6.2 統(tǒng)計(count/averaging)
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"));
// 求總數
Long count = personList.stream().collect(Collectors.counting());
// 求平均工資
Double average = personList.stream().collect(Collectors.averagingDouble(Person::getSalary));
// 求最高工資
Optional<Integer> max = personList.stream().map(Person::getSalary).collect(Collectors.maxBy(Integer::compare));
// 求工資之和
Integer sum = personList.stream().collect(Collectors.summingInt(Person::getSalary));
// 一次性統(tǒng)計所有信息
DoubleSummaryStatistics collect = personList.stream().collect(Collectors.summarizingDouble(Person::getSalary));
System.out.println("員工總數：" + count);
System.out.println("員工平均工資：" + average);
System.out.println("員工工資總和：" + sum);
System.out.println("員工工資所有統(tǒng)計：" + collect);
}
}
3.6.3 分組(partitioningBy/groupingBy)
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"));
// 將員工按薪資是否高于8000分組
Map<Boolean, List<Person>> part = personList.stream().collect(Collectors.partitioningBy(x -> x.getSalary() > 8000));
// 將員工按性別分組
Map<String, List<Person>> group = personList.stream().collect(Collectors.groupingBy(Person::getSex));
// 將員工先按性別分組，再按地區(qū)分組
Map<String, Map<String, List<Person>>> group2 = personList.stream().collect(Collectors.groupingBy(Person::getSex, Collectors.groupingBy(Person::getArea)));
System.out.println("員工按薪資是否大于8000分組情況：" + part);
System.out.println("員工按性別分組情況：" + group);
System.out.println("員工按性別、地區(qū)：" + group2);
}
}
員工按薪資是否大于8000分組情況：{false=[mutest.Person@2d98a335, mutest.Person@16b98e56, mutest.Person@7ef20235], true=[mutest.Person@27d6c5e0, mutest.Person@4f3f5b24, mutest.Person@15aeb7ab]}
員工按性別分組情況：{female=[mutest.Person@16b98e56, mutest.Person@4f3f5b24, mutest.Person@7ef20235], male=[mutest.Person@27d6c5e0, mutest.Person@2d98a335, mutest.Person@15aeb7ab]}
員工按性別、地區(qū)：{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]}}
3.6.4 接合(joining)
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("所有員工的姓名：" + 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);
}
}
3.6.5 歸約(reducing)
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"));
// 每個員工減去起征點后的薪資之和（這個例子并不嚴謹，但一時沒想到好的例子）
Integer sum = personList.stream().collect(Collectors.reducing(0, Person::getSalary, (i, j) -> (i + j - 5000)));
System.out.println("員工扣稅薪資總和：" + sum);
// stream的reduce
Optional<Integer> sum2 = personList.stream().map(Person::getSalary).reduce(Integer::sum);
System.out.println("員工薪資總和：" + sum2.get());
}
}
3.7 排序(sorted)
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"));
// 按工資升序排序（自然排序）
List<String> newList = personList.stream().sorted(Comparator.comparing(Person::getSalary)).map(Person::getName)
.collect(Collectors.toList());
// 按工資倒序排序
List<String> newList2 = personList.stream().sorted(Comparator.comparing(Person::getSalary).reversed())
.map(Person::getName).collect(Collectors.toList());
// 先按工資再按年齡升序排序
List<String> newList3 = personList.stream()
.sorted(Comparator.comparing(Person::getSalary).thenComparing(Person::getAge)).map(Person::getName)
.collect(Collectors.toList());
// 先按工資再按年齡自定義排序（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("按工資升序排序：" + newList);
System.out.println("按工資降序排序：" + newList2);
System.out.println("先按工資再按年齡升序排序：" + newList3);
System.out.println("先按工資再按年齡自定義降序排序：" + newList4);
}
}
3.8 提取/組合
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:合并兩個流 distinct：去重
List<String> newList = Stream.concat(stream1, stream2).distinct().collect(Collectors.toList());
// limit：限制從流中獲得前n個數據
List<Integer> collect = Stream.iterate(1, x -> x + 2).limit(10).collect(Collectors.toList());
// skip：跳過前n個數據
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);
}
}
作者 | 云深i不知處
來源 | csdn.net/mu_wind/article/details/109516995
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