【Java SE】流

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1、创建流

2、过滤 filter

3、映射 map flatMap

4、分组 groupingBy

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import java.util.*;
import java.util.stream.Collectors;

 

人对象

class Person {
    private String name;
    private int age;
}

 

1、创建流

// 数组创建流
public static<T> Stream<T> of(T... values);
// 空流
public static<T> Stream<T> empty();

基本流

short a = 1;
short b = 2;
Stream<Short> shortStream = Stream.of(a, b);
Stream<Character> charStream = Stream.of('a', 'b');
byte c = 1;
byte d = 2;
Stream<Byte> byteStream = Stream.of(c, d);
Stream<Boolean> booleanStream = Stream.of(true, false);
Stream<Integer> integerStream = Stream.of(1,2,3);
IntStream intStream = IntStream.of(1,2,3);
int[] intArray1 = new int[] {1,2,3};
int[] intArray2 = new int[] {4,5,6};
IntStream intStream1 = Arrays.stream(intArray1);
IntStream intStream2 = Arrays.stream(intArray2, 1, 2);
IntStream stepIntStream = IntStream.range(0, 100);// 生成0 ~ 99 不含100
IntStream stepIntStream2 = IntStream.rangeClosed(0, 100);// 生成0 ~ 99 不含100
LongStream longStream = LongStream.of(1,2,3);
LongStream longStepStream = LongStream.range(0, 100);// 生成0 ~ 99 不含100
LongStream longStepStream2 = LongStream.rangeClosed(0, 100);// 生成0 ~ 99 不含100
DoubleStream doubleStream = DoubleStream.of(1,2,3);
java.util.Random random = new Random();
IntStream randomIntStream = random.ints();
LongStream randomLongStream = random.longs();
DoubleStream randomDoubleStream = random.doubles();

 

 

2、过滤 filter

List<Person> list = new ArrayList<>();
list.add(new Person("Alice", 20));
list.add(new Person("Tom", 11));// 滤过年龄大于15的人
List<Person> resultList = list.stream().filter(p -> p.getAge() > 15).collect(Collectors.toList());

3、映射 map  flatMap

List<Person> list = new ArrayList<>();
list.add(new Person("Alice", 20));
list.add(new Person("Tom", 21));
// 映射出姓名
List<String> resultList = list.stream().map(Person::getName).collect(Collectors.toList());
System.out.println(resultList);

List<String> words = new ArrayList<>();
words.add("h,e,l,l,o");
words.add("w,o,r,l,d");
// map 的结果是流
List<Stream> resultStream = words.stream().map(w -> Stream.of(w.split(","))).collect(Collectors.toList());
// flatMap 的结果是字符
List<String> resultList = words.stream().flatMap(w -> Stream.of(w.split(","))).collect(Collectors.toList());
System.out.println(resultList);

4、分组 groupingBy

List<Person> list = new ArrayList<>();
list.add(new Person("Alice", 10));
list.add(new Person("Alice", 20));
list.add(new Person("Tom", 11));
list.add(new Person("Tom", 21));

名称分组

Map<String, List<Person>> groupName = list.stream().collect(Collectors.groupingBy(Person::getName));
System.out.println(groupName);
// 结果
{Tom=[Person{name='Tom', age='11'}, Person{name='Tom', age='21'}], Alice=[Person{name='Alice', age='10'}, Person{name='Alice', age='20'}]}

分组件数

Map<String, Long> groupCount = list.stream().collect(Collectors.groupingBy(Person::getName, Collectors.counting()));
System.out.println(groupCount);
// 结果
{Tom=2, Alice=2}

分组合计

Map<String, Integer> groupSum = list.stream().collect(Collectors.groupingBy(Person::getName, Collectors.summingInt(Person::getAge)));
System.out.println(groupSum);
// 结果
{Tom=32, Alice=30}

分组最大值

List<Person> list = new ArrayList<>();
list.add(new Person("Alice", 10));
list.add(new Person("Alice", 20));
list.add(new Person("Tom", 11));
list.add(new Person("Tom", 21));
Map<String, Optional<Person>> groupMax = list.stream().collect(Collectors.groupingBy(Person::getName, Collectors.maxBy(Comparator.comparing(Person::getAge))));
Optional<Person> tom = groupMax.get("Tom");
tom.ifPresent(v -> System.out.println(v));
// 结果
Person{name='Tom', age='21'}

分组最小值

List<Person> list = new ArrayList<>();
list.add(new Person("Alice", 10));
list.add(new Person("Alice", 20));
list.add(new Person("Tom", 11));
list.add(new Person("Tom", 21));
Map<String, Optional<Person>> groupMin = list.stream().collect(Collectors.groupingBy(Person::getName, Collectors.minBy(Comparator.comparing(Person::getAge))));
Optional<Person> tom = groupMin.get("Alice");
tom.ifPresent(v -> System.out.println(v));
// 结果
Person{name='Alice', age='10'}

分组映射比较

年龄分组后，映射出名字最长的人

List<Person> list = new ArrayList<>();
list.add(new Person("Jean", 10));
list.add(new Person("Alice", 20));
list.add(new Person("Tom", 20));
list.add(new Person("Bob", 30));
Map<Integer, Optional<String>> groupByAge = list.stream().collect(Collectors.groupingBy(Person::getAge, Collectors.mapping(Person::getName, Collectors.maxBy(Comparator.comparing(String::length)))));
for (Map.Entry<Integer, Optional<String>> item : groupByAge.entrySet()) {
    Integer age = item.getKey();
    Optional<String> optional = item.getValue();
    optional.ifPresent(v -> System.out.println(v + " : " + age));
}

reduce 方法是一种用于从流中计算某个值的通用方法

List<Integer> scores = new ArrayList<>();
scores.add(10);
scores.add(20);
scores.add(30);
Optional<Integer> sumOptional = scores.stream().reduce((x,y) -> x + y);
int sum2 = scores.stream().reduce(0, (x,y) -> x + y);// 第一个参数是幺元值，0是加法的幺元值，没有幺元值就存在没有值的情况返回optional
sumOptional.ifPresent(v -> System.out.println(v));
System.out.println(sum2);