Java8之Stream的学习

一、概念理解

Stream可以由数组或集合创建，对流的操作分为两种：

1. 中间操作，每次返回一个新的流，可以有多个。
2. 终端操作，每个流只能进行一次终端操作，终端操作结束后流无法再次使用。终端操作会产生一个新的集合或值。

二、Stream的创建

public class StreamDemo {
    public static void main(String[] args) {
        // 集合
        List<Integer> list = Arrays.asList(1, 2, 3);
        // 集合创建一个顺序流
        Stream<Integer> stream = list.stream();
        // 集合创建一个并行流
        Stream<Integer> parallelStream = list.parallelStream();
 
 
        // 数组
        int[] array = {1, 3, 5, 6, 8};
        // 数组创建流方式
        IntStream intStream = Arrays.stream(array);
        
    }
}

stream和parallelStream的简单区分： stream是顺序流，由主线程按顺序对流执行操作，而parallelStream是并行流，内部以多线程并行执行的方式对流进行操作，但前提是流中的数据处理没有顺序要求。

三、方法学习

1、遍历/匹配（foreach/find/match）

import java.util.*;
 
/**
 * @author qinxun
 * @date 2023-06-02
 * @Descripion: 职工测试类
 */
public class EmployeeDemo {
    public static void main(String[] args) {
        List<Integer> list = Arrays.asList(1, 2, 3, 4, 5);
        // foreach
        list.forEach(System.out::println);
 
        System.out.println("----------");
 
        //find
        Optional<Integer> firstData = list.stream().findFirst();
        System.out.println(firstData.get());
 
        System.out.println("----------");
 
        //match: anyMatch有一个匹配就返回true noneMatch没有任何匹配才返回true allMatch所有匹配才返回true
        System.out.println(list.stream().anyMatch(x -> x > 4));
    }
 
    /**
     * 初始化职工列表数据
     */
    private static List<Employee> initEmployee() {
        List<Employee> employeeList = new ArrayList<>();
        employeeList.add(new Employee("张三", 8, 3000.0));
        employeeList.add(new Employee("李四", 18, 5000.0));
        employeeList.add(new Employee("王五", 28, 7000.0));
        employeeList.add(new Employee("孙六", 38, 9000.0));
        return employeeList;
    }
}

执行程序控制台显示

1
2
3
4
5
----------
1
----------
true

2、按条件匹配filter 

import java.util.*;
import java.util.stream.Collectors;
 
/**
 * @author qinxun
 * @date 2023-06-02
 * @Descripion: 职工测试类
 */
public class EmployeeDemo {
    public static void main(String[] args) {
        List<Employee> employeeList = initEmployee();
        // 筛选年纪大于18岁的职工
        List<Employee> employees = employeeList.stream().filter(s -> s.getAge() > 18).collect(Collectors.toList());
        System.out.println(employees);
    }
 
    /**
     * 初始化职工列表数据
     */
    private static List<Employee> initEmployee() {
        List<Employee> employeeList = new ArrayList<>();
        employeeList.add(new Employee("张三", 8, 3000.0));
        employeeList.add(new Employee("李四", 18, 5000.0));
        employeeList.add(new Employee("王五", 28, 7000.0));
        employeeList.add(new Employee("孙六", 38, 9000.0));
        return employeeList;
    }
}

执行程序控制台显示

[Employee{name='王五', age=28, salary=7000.0}, Employee{name='孙六', age=38, salary=9000.0}]

3、聚合max、min、count

import java.util.*;
 
/**
 * @author qinxun
 * @date 2023-06-02
 * @Descripion: 职工测试类
 */
public class EmployeeDemo {
    public static void main(String[] args) {
        List<Employee> employeeList = initEmployee();
        // 获取薪水最高的职工
        Optional<Employee> employeeOptional = employeeList.stream().max(Comparator.comparing(Employee::getSalary, Double::compareTo));
        System.out.println(employeeOptional.get());
 
        // 获取年级最小的职工
        Optional<Employee> employeeOptional1 = employeeList.stream().min(Comparator.comparing(Employee::getAge, Integer::compareTo));
        System.out.println(employeeOptional1.get());
 
        // 获取年级大于18的职工数量
        long count = employeeList.stream().filter(s -> s.getAge() > 18).count();
        System.out.println(count);
    }
 
    /**
     * 初始化职工列表数据
     */
    private static List<Employee> initEmployee() {
        List<Employee> employeeList = new ArrayList<>();
        employeeList.add(new Employee("张三", 8, 3000.0));
        employeeList.add(new Employee("李四", 18, 5000.0));
        employeeList.add(new Employee("王五", 28, 7000.0));
        employeeList.add(new Employee("孙六", 38, 9000.0));
        return employeeList;
    }
}

执行程序后控制台显示

Employee{name='孙六', age=38, salary=9000.0}
Employee{name='张三', age=8, salary=3000.0}
2

4、map与flatMap 数据转换和数据合并

/**
 * @author qinxun
 * @date 2023-06-02
 * @Descripion: 职工测试类
 */
public class EmployeeDemo {
    public static void main(String[] args) {
        List<String> list = Arrays.asList("a","b","c");
        // map中把小写字母转换成大写
        List<String> stringList = list.stream().map(String::toUpperCase).collect(Collectors.toList());
        // 输出[A, B, C]
        System.out.println(stringList);
    }
}

/**
 * @author qinxun
 * @date 2023-06-02
 * @Descripion: 职工测试类
 */
public class EmployeeDemo {
    public static void main(String[] args) {
        String[] arr = {"z-h-a-n-g", "s-a-n"};
        List<String> list = Arrays.asList(arr);
        System.out.println(list);
        // 将两个字符数组合并成一个新的字符数组
        List<String> collect = list.stream().flatMap(x -> {
            String[] array = x.split("-");
            return Arrays.stream(array);
        }).collect(Collectors.toList());
        System.out.println(collect);
    }
}

flatMap把两个数据流合并成一个数据流

[z-h-a-n-g, s-a-n]
[z, h, a, n, g, s, a, n]

5、规约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。

import java.util.*;
 
/**
 * @author qinxun
 * @date 2023-06-02
 * @Descripion: 职工测试类
 */
public class EmployeeDemo {
    public static void main(String[] args) {
        List<Employee> list = initEmployee();
        // 求所有工资的和
        Double sum = list.stream().map(Employee::getSalary).reduce(0.0, Double::sum);
        System.out.println(sum);
 
        // 求职工工资最大值
        Optional<Double> max = list.stream().map(Employee::getSalary).reduce((a, b) -> a > b ? a : b);
        System.out.println(max.get());
    }
 
    /**
     * 初始化职工列表数据
     */
    private static List<Employee> initEmployee() {
        List<Employee> employeeList = new ArrayList<>();
        employeeList.add(new Employee("张三", 8, 3000.0));
        employeeList.add(new Employee("李四", 18, 5000.0));
        employeeList.add(new Employee("王五", 28, 7000.0));
        employeeList.add(new Employee("孙六", 38, 9000.0));
        return employeeList;
    }
}

执行程序后控制台显示

24000.0
9000.0

6、数据收集（toList、toSet、toMap）

import java.util.*;
import java.util.stream.Collectors;
 
/**
 * @author qinxun
 * @date 2023-06-02
 * @Descripion: 职工测试类
 */
public class EmployeeDemo {
    public static void main(String[] args) {
        List<Employee> list = initEmployee();
        // 返回名字做为key,工资做为value的map数据
        Map<String, Double> employeeMap = list.stream().collect(Collectors.toMap(Employee::getName, Employee::getSalary));
        System.out.println(employeeMap);
 
        // 职工名字集合
        List<String> employeeNameList = list.stream().map(Employee::getName).collect(Collectors.toList());
        System.out.println(employeeNameList);
 
        // 职工年龄集合
        Set<Integer> ageSet = list.stream().map(s -> s.getAge()).collect(Collectors.toSet());
        System.out.println(ageSet);
    }
 
    /**
     * 初始化职工列表数据
     */
    private static List<Employee> initEmployee() {
        List<Employee> employeeList = new ArrayList<>();
        employeeList.add(new Employee("张三", 8, 3000.0));
        employeeList.add(new Employee("李四", 18, 5000.0));
        employeeList.add(new Employee("王五", 28, 7000.0));
        employeeList.add(new Employee("孙六", 38, 9000.0));
        return employeeList;
    }
}

执行程序后控制台显示

{李四=5000.0, 张三=3000.0, 王五=7000.0, 孙六=9000.0}
[张三, 李四, 王五, 孙六]
[18, 38, 8, 28]

7、collect

Collectors提供了一系列用于数据统计的静态方法：

Collectors提供了一系列用于数据统计的静态方法：

计数：count

平均值：averagingInt、averagingLong、averagingDouble

最值：maxBy、minBy

求和：summingInt、summingLong、summingDouble

统计以上所有：summarizingInt、summarizingLong、summarizingDouble

import java.util.*;
import java.util.stream.Collectors;
 
/**
 * @author qinxun
 * @date 2023-06-02
 * @Descripion: 职工测试类
 */
public class EmployeeDemo {
    public static void main(String[] args) {
        List<Employee> employeeList = initEmployee();
 
        // 统计职工人数
        Long count = employeeList.stream().collect(Collectors.counting());
        System.out.println(count);
 
        // 获取职工最高工资
        Optional<Double> salaryOptional = employeeList.stream().map(Employee::getSalary).collect(Collectors.maxBy((s1, s2) -> s1.compareTo(s2)));
        System.out.println(salaryOptional);
 
        // 获取职工平均工资
        Double averageSalary = employeeList.stream().collect(Collectors.averagingDouble(Employee::getSalary));
        System.out.println(averageSalary);
 
        //一次性统计职工所有工资信息
        DoubleSummaryStatistics summaryStatistics = employeeList.stream().collect(Collectors.summarizingDouble(Employee::getSalary));
        System.out.println(summaryStatistics);
    }
 
    /**
     * 初始化职工列表数据
     */
    private static List<Employee> initEmployee() {
        List<Employee> employeeList = new ArrayList<>();
        employeeList.add(new Employee("张三", 8, 3000.0));
        employeeList.add(new Employee("李四", 18, 5000.0));
        employeeList.add(new Employee("王五", 28, 7000.0));
        employeeList.add(new Employee("孙六", 38, 9000.0));
        return employeeList;
    }
}

执行程序后控制台显示

4
Optional[9000.0]
6000.0
DoubleSummaryStatistics{count=4, sum=24000.000000, min=3000.000000, average=6000.000000, max=9000.000000}

8、分组(partitioningBy/groupingBy)

import java.util.*;
import java.util.stream.Collectors;
 
/**
 * @author qinxun
 * @date 2023-06-02
 * @Descripion: 职工测试类
 */
public class EmployeeDemo {
    public static void main(String[] args) {
        List<Employee> employeeList = initEmployee();
 
        // 将员工按薪资是否高于7000分组
        Map<Boolean, List<Employee>> map = employeeList.stream().collect(Collectors.partitioningBy(s -> s.getSalary() > 7000));
        System.out.println(map);
 
        // 将职工按性别分组
        Map<String, List<Employee>> employeeMap = employeeList.stream().collect(Collectors.groupingBy(Employee::getSex));
        System.out.println(employeeMap);
    }
 
    /**
     * 初始化职工列表数据
     */
    private static List<Employee> initEmployee() {
        List<Employee> employeeList = new ArrayList<>();
        employeeList.add(new Employee("张三", 8, "男", 3000.0));
        employeeList.add(new Employee("李四", 18, "女", 5000.0));
        employeeList.add(new Employee("王五", 28, "男", 7000.0));
        employeeList.add(new Employee("孙六", 38, "女", 9000.0));
        return employeeList;
    }
}

{false=[Employee{name='张三', age=8, salary=3000.0}, Employee{name='李四', age=18, salary=5000.0}, Employee{name='王五', age=28, salary=7000.0}], true=[Employee{name='孙六', age=38, salary=9000.0}]}
{女=[Employee{name='李四', age=18, salary=5000.0}, Employee{name='孙六', age=38, salary=9000.0}], 男=[Employee{name='张三', age=8, salary=3000.0}, Employee{name='王五', age=28, salary=7000.0}]}

9、数据拼接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。

import java.util.*;
import java.util.stream.Collectors;
 
/**
 * @author qinxun
 * @date 2023-06-02
 * @Descripion: 职工测试类
 */
public class EmployeeDemo {
    public static void main(String[] args) {
        List<Employee> employeeList = initEmployee();
 
        // 将职工姓名用逗号拼接返回
        String nameData = employeeList.stream().map(Employee::getName).collect(Collectors.joining(","));
        System.out.println(nameData);
    }
 
    /**
     * 初始化职工列表数据
     */
    private static List<Employee> initEmployee() {
        List<Employee> employeeList = new ArrayList<>();
        employeeList.add(new Employee("张三", 8, "男", 3000.0));
        employeeList.add(new Employee("李四", 18, "女", 5000.0));
        employeeList.add(new Employee("王五", 28, "男", 7000.0));
        employeeList.add(new Employee("孙六", 38, "女", 9000.0));
        return employeeList;
    }
}

张三,李四,王五,孙六

10、排序sorted

import java.util.*;
import java.util.stream.Collectors;
 
/**
 * @author qinxun
 * @date 2023-06-02
 * @Descripion: 职工测试类
 */
public class EmployeeDemo {
    public static void main(String[] args) {
        List<Employee> employeeList = initEmployee();
 
        // 将职工工资升序排序
        List<Employee> employees = employeeList.stream().sorted(Comparator.comparing(Employee::getSalary)).collect(Collectors.toList());
        System.out.println(employees);
 
        // 将职工工资降序排序
        List<Employee> list = employeeList.stream().sorted(Comparator.comparing(Employee::getSalary).reversed()).collect(Collectors.toList());
        System.out.println(list);
    }
 
    /**
     * 初始化职工列表数据
     */
    private static List<Employee> initEmployee() {
        List<Employee> employeeList = new ArrayList<>();
        employeeList.add(new Employee("张三", 8, "男", 3000.0));
        employeeList.add(new Employee("李四", 18, "女", 5000.0));
        employeeList.add(new Employee("王五", 28, "男", 7000.0));
        employeeList.add(new Employee("孙六", 38, "女", 9000.0));
        return employeeList;
    }
}

[Employee{name='张三', age=8, salary=3000.0}, Employee{name='李四', age=18, salary=5000.0}, Employee{name='王五', age=28, salary=7000.0}, Employee{name='孙六', age=38, salary=9000.0}]
[Employee{name='孙六', age=38, salary=9000.0}, Employee{name='王五', age=28, salary=7000.0}, Employee{name='李四', age=18, salary=5000.0}, Employee{name='张三', age=8, salary=3000.0}]

11、提取/组合(distinct/limit/skip)

import java.util.*;
import java.util.stream.Collectors;
import java.util.stream.Stream;
 
/**
 * @author qinxun
 * @date 2023-06-02
 * @Descripion: 职工测试类
 */
public class EmployeeDemo {
    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);
 
        // 合并流
        List<String> newList = Stream.concat(stream1, stream2).distinct().collect(Collectors.toList());
        System.out.println(newList);
 
        // 限制从流中获得前1个数据
        System.out.println(Stream.of(arr1).limit(1).collect(Collectors.toList()));
 
        // 跳过前2个数据
        System.out.println(Stream.of(arr1).skip(2).collect(Collectors.toList()));
    }
}

[a, b, c, d, e, f, g]
[a]
[c, d]