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JDK8新特性-Stream流


个人简介

作者是一个来自河源的大三在校生,以下笔记都是作者自学之路的一些浅薄经验,如有错误请指正,将来会不断的完善笔记,帮助更多的Java爱好者入门。

文章目录

    • 个人简介
    • JDK8新特性-Stream流
      • 教程概述
      • Stream流的创建
        • 用集合创建流
        • 用数组创建流
        • 使用Stream的静态方法创建流
      • 顺序流转换成并行流
      • 流的遍历和查找元素(forEach、find)
        • 遍历Stream顺序流
        • 遍历并行流(多线程,输出顺序会不一样)
        • 找出流中第一个元素
      • 流的筛选(filter)
        • 案例1:集合中大于5的元素,并打印出来
        • 案例2:筛选年龄大于25岁的人,并形成一个只有name的新的集合
      • 聚合(max、min、count)
        • 案例3:获取String集合中最长的元素
        • 案例4:比较集合中数字最大的并输出
        • 案例5:计算Integer集合中大于6的元素的个数
      • 映射(map)
        • 案例6:英文字符串数组的元素全部改为大写
        • 案例7:整数数组每个元素+3
        • 案例8:将员工的薪资全部增加1000
      • 归约(reduce)
        • 案例9:求所有员工的工资之和。
        • 案例10:最高工资
      • 收集(collect)
        • Stream流转List(toList)
        • Stream流转Set(toSet)
        • Stream流转Map(toMap)
        • 案例11:求流的平均值
      • 排序(sorted)
        • 排序注意点
        • 案例12:对纯数字进行排序
        • 案例13:将对象的薪资属性进行排序
      • 去重和限制(distinct、limit)

JDK8新特性-Stream流

教程概述

  • 本教程附有非常多的例子,看完肯定能懂Stream流!
  • 看完本教程,对于Stream api基本的使用完全没有问题,底层原理则不会深究!
  • 本教程借鉴过很多其他大佬的教程,并进行总结创新,难免会有相同之处。

Stream流的创建

用集合创建流

  //创建普通顺序流      Stream<Integer> stream = asList.stream();      //创建并行流      Stream<Integer> parallelStream = asList.parallelStream();

用数组创建流

  int arr[]={1,2,3,4,5};      IntStream intStream = Arrays.stream(arr);

使用Stream的静态方法创建流

Stream<Integer> integerStream = Stream.of(1, 2, 3, 4, 5, 6);

顺序流转换成并行流

  List<Integer> asList = Arrays.asList(1, 2, 3, 4, 5);      //创建顺序流      Stream<Integer> integerStream = asList.stream();      //把顺序流转换成并行流      Stream<Integer> parallel = integerStream.parallel();

实体类Person:

class Person {    private String name;  // 姓名    private double salary; // 薪资    private int age; // 年龄    public Person(String name, double salary, int age) { this.name = name; this.salary = salary; this.age = age;    }    public String getName() { return name;    }    public void setName(String name) { this.name = name;    }    public double getSalary() { return salary;    }    public void setSalary(double salary) { this.salary = salary;    }    public int getAge() { return age;    }    public void setAge(int age) { this.age = age;    }    @Override    public String toString() { return "Person{" +  "name='" + name + '\'' +  ", salary=" + salary +  ", age=" + age +  '}';    }}

流的遍历和查找元素(forEach、find)

遍历Stream顺序流

  List<Person> list=new ArrayList<>();      list.add(new Person("z1",2000.0,18));      list.add(new Person("z2",3200.0,15));      list.add(new Person("z3",1500.0,27));      list.add(new Person("z4",7000.0,36));      list.add(new Person("z5",5000.0,22));      list.add(new Person("z6",4200.0,42));    //创建Stream顺序流      Stream<Person> stream = list.stream();      //遍历Stream顺序流      stream.forEach(System.out::println);

遍历并行流(多线程,输出顺序会不一样)

  //创建并行流(多线程)      Stream<Person> parallelStream = list.parallelStream();  //遍历并行流(多线程,输出顺序会不一样)  parallelStream.forEach(System.out::println);

找出流中第一个元素

  Optional<Person> first = stream.findFirst();      System.out.println(first.get());

流的筛选(filter)

案例1:集合中大于5的元素,并打印出来

  List<Integer> list = Arrays.asList(7, 6, 9, 3, 8, 2, 1);      Stream<Integer> stream = list.stream();      //1:集合中大于5的元素,并打印出来      stream.filter(el->el>5).forEach(System.out::println);

案例2:筛选年龄大于25岁的人,并形成一个只有name的新的集合

  List<Person> personList = new ArrayList<Person>();      personList.add(new Person("z1",2000.0,18));      personList.add(new Person("z2",3200.0,15));      personList.add(new Person("z3",1500.0,27));      personList.add(new Person("z4",7000.0,36));      personList.add(new Person("z5",5000.0,22));      personList.add(new Person("z6",4200.0,42));      Stream<Person> personStream = personList.stream();      List<String> collect = personStream.filter(person -> person.getAge() > 25)     //只筛选出name,如果直接collect则返回的是person对象.map(Person::getName) .collect(Collectors.toList());      collect.forEach(System.out::println);

聚合(max、min、count)

案例3:获取String集合中最长的元素

 List<String> list1 = Arrays.asList("qdiq", "sdji", "aaa", "ihduxdswaa", "qwer");      Stream<String> stream1 = list1.stream();      Optional<String> maxString = stream1.max(Comparator.comparing(String::length));      System.out.println("maxString="+maxString.get());

案例4:比较集合中数字最大的并输出

  List<Integer> integerList = Arrays.asList(20, 10, 30, 52, 42, 15, 11, 13, 19, 30);      Stream<Integer> integerStream = integerList.stream();      Optional<Integer> optionalInteger = integerStream.max(Comparator.comparing(Integer::intValue));      System.out.println(optionalInteger.get());

案例5:计算Integer集合中大于6的元素的个数

  List<Integer> list2 = Arrays.asList(7, 6, 4, 8, 2, 11, 9);      long count = list2.stream().filter(integer -> integer > 6).count();      System.out.println("集合中大于6的个数="+count);

映射(map)

  • 可以直接操作每一个流的元素
  • 凡是需要操作流中元素的都用map,filter只是起到筛选的作用

案例6:英文字符串数组的元素全部改为大写

  Stream<String> stream = Arrays.stream(strArr);      //s就是每一个元素      List<String> collect = stream.map(s -> s.toUpperCase()).collect(Collectors.toList());      collect.forEach(System.out::println);

案例7:整数数组每个元素+3

  List<Integer> intList = Arrays.asList(1, 3, 5, 7, 9, 11);      Stream<Integer> stream1 = intList.stream();      stream1.map(integer -> integer+=3).collect(Collectors.toList()).forEach(System.out::println);

案例8:将员工的薪资全部增加1000

  List<Person> personList = new ArrayList<Person>();      personList.add(new Person("z1",2000.0,18));      personList.add(new Person("z2",3200.0,15));      personList.add(new Person("z3",1500.0,27));      personList.add(new Person("z4",7000.0,36));      personList.add(new Person("z5",5000.0,22));      personList.add(new Person("z6",4200.0,42));      Stream<Person> personStream = personList.stream();      personStream.map(person -> {   double old = person.getSalary();   person.setSalary(old+1000); //增加1000   return person; //返回原对象      }).collect(Collectors.toList()).forEach(System.out::println);

归约(reduce)

  • 把一个流缩减成一个值
  • 作用:实现一个流的加法、乘法、求最值等计算

整个流的加法、乘法、最大值

  List<Integer> list = Arrays.asList(1, 3, 2, 8, 11, 4);      Stream<Integer> stream = list.stream();      //整个流的加法      Optional<Integer> add = stream.reduce((x, y) -> x + y);      System.out.println(add.get());      //整个流的乘法      Optional<Integer> num = stream.reduce((x, y) -> x * y);      System.out.println(num.get());      //最大值      Optional<Integer> maxNumber = stream.reduce((x, y) -> x > y ? x : y);      System.out.println(maxNumber.get());

案例9:求所有员工的工资之和。

  List<Person> personList = new ArrayList<Person>();      personList.add(new Person("z1",2000.0,18));      personList.add(new Person("z2",3200.0,15));      personList.add(new Person("z3",1500.0,27));      personList.add(new Person("z4",7000.0,36));      personList.add(new Person("z5",5000.0,22));      personList.add(new Person("z6",4200.0,42));  Stream<Person> personStream1 = personList.parallelStream();      Optional<Double> sum = personStream1//指定选择操作薪资.map(person -> person.getSalary()).reduce((x, y) -> x + y);      System.out.println(sum.get());

案例10:最高工资

  List<Person> personList = new ArrayList<Person>();      personList.add(new Person("z1",2000.0,18));      personList.add(new Person("z2",3200.0,15));      personList.add(new Person("z3",1500.0,27));      personList.add(new Person("z4",7000.0,36));      personList.add(new Person("z5",5000.0,22));      personList.add(new Person("z6",4200.0,42));  Stream<Person> personStream2 = personList.parallelStream();      Optional<Double> max = personStream2//指定操作salary.map(person -> person.getSalary()).reduce((x, y) -> x > y ? x : y);      System.out.println(max.get());

收集(collect)

Stream流转List(toList)

List<Integer> list = Arrays.asList(1, 6, 3, 4, 6, 7, 9, 6, 20);    Stream<Integer> parallel1 = list.stream().parallel();List<Integer> list1 = parallel1.collect(Collectors.toList());    list1.forEach(System.out::println);

Stream流转Set(toSet)

List<Integer> list = Arrays.asList(1, 6, 3, 4, 6, 7, 9, 6, 20);    Stream<Integer> parallel1 = list.stream().parallel();Set<Integer> set = parallel2.collect(Collectors.toSet());    set.forEach(System.out::println);

Stream流转Map(toMap)

List<Person> personList = new ArrayList<Person>();    personList.add(new Person("z1", 2000.0, 18));    personList.add(new Person("z2", 3200.0, 15));    personList.add(new Person("z3", 1500.0, 27));    personList.add(new Person("z4", 7000.0, 36));    personList.add(new Person("z5", 5000.0, 22));    personList.add(new Person("z6", 4200.0, 42));    Stream<Person> personStream = personList.stream().parallel();    Map<String, Person> map = personStream     // toMap(k, v)     .collect(Collectors.toMap(x -> x.getName(), y -> y));// lambda遍历map    map.forEach( (k, v) -> {   System.out.println("key=" + k + ",v=" + v); });

案例11:求流的平均值

List<Integer> list2 = Arrays.asList(1, 2, 3, 4, 10);    Stream<Integer> integerStream = list2.stream();    Double averag = integerStream.collect(Collectors.averagingInt(x -> x));    System.out.println(averag);

排序(sorted)

排序注意点

  • 排序不能用并行流,否则将失效

案例12:对纯数字进行排序

  List<Integer> list = Arrays.asList(12, 5, 6, 3, 2, 9, 22, 17, 15, 13, 6, 5, 1);      Stream<Integer> integerStream1 = list.stream();      //1:对纯数字进行排序      integerStream1.sorted(Comparator.comparingInt(x->x)).forEach(System.out::println);

案例13:将对象的薪资属性进行排序

  List<Person> personList = new ArrayList<Person>();      personList.add(new Person("z1",2000.0,18));      personList.add(new Person("z2",3200.0,15));      personList.add(new Person("z3",1500.0,27));      personList.add(new Person("z4",7000.0,36));      personList.add(new Person("z5",5000.0,22));      personList.add(new Person("z6",4200.0,42));      Stream<Person> stream = personList.stream();      stream.sorted(Comparator.comparing(el->el.getSalary())).forEach(System.out::println);

去重和限制(distinct、limit)

  List<Integer> list = Arrays.asList(3, 6, 6, 2, 3, 1, 2, 9, 12, 15);      Stream<Integer> stream = list.stream();      stream//去重.distinct()//分页,限制最多输出前几个.limit(3).forEach(System.out::println);