Lambda学习

从List的对象获取一个属性转换新的集合
将List userList转换为List userIdList

List<Integer> userIds = userList.stream().map(u -> u.getId()).collect(Collectors.toList());

List集合的去重

List<String> ppqIdList = Splitter.on(",").trimResults().omitEmptyStrings().splitToList(ppqDataId).stream().distinct().collect(Collectors.toList());

List集合的去空

List<String> idCardList = interviewerList.stream().map(inter -> inter.getIdCard()).collect(Collectors.toList());
List<String> idCardListNotNull = idCardList.stream().filter(Objects::nonNull).collect(Collectors.toList());

java8中使用Lambda表达式将list中实体类的两个字段转Map

Map<String, String> checkDictMap = List<Dict>.stream().collect(Collectors.toMap(Dict::getCode, Dict::getDescription, (key1, key2) -> key2));

java8 list统计（求和、最大、最小、平均）

list.stream().mapToDouble(User::getHeight).sum()//和
list.stream().mapToDouble(User::getHeight).max()//最大
list.stream().mapToDouble(User::getHeight).min()//最小
list.stream().mapToDouble(User::getHeight).average()//平均值

当然，除了统计double类型，还有int和long

bigdecimal需要用到reduce求和

Double示例：

public class HelloWorld {
    private static final DecimalFormat df = new DecimalFormat("0.00");//保留两位小数点
    public static void main(String[] args) {
        Random random = new Random();
        List<User> list = new ArrayList<>();
        for(int i=1;i<=5;i++) {
            double weight = random.nextDouble() * 100 + 100;//随机身高：100-200
            User u = new User(i, "用户-" + i, weight);
            list.add(u);
        }
        System.out.println("用户：" + list);
        double sum = list.stream().mapToDouble(User::getHeight).sum();
        System.out.println("身高 总和：" + df.format(sum));
        double max = list.stream().mapToDouble(User::getHeight).max().getAsDouble();
        System.out.println("身高 最大：" + df.format(max));
        double min = list.stream().mapToDouble(User::getHeight).min().getAsDouble();
        System.out.println("身高 最小：" + df.format(min));
        double average = list.stream().mapToDouble(User::getHeight).average().getAsDouble();
        System.out.println("身高 平均：" + df.format(average));

    }
    private static class User{
        Integer id;
        String name;
        double height;//身高

        public User(Integer id, String name, double height) {
            this.id = id;
            this.name = name;
            this.height = height;
        }

        public Integer getId() {
            return id;
        }

        public void setId(Integer id) {
            this.id = id;
        }

        public String getName() {
            return name;
        }

        public void setName(String name) {
            this.name = name;
        }

        public double getHeight() {
            return height;
        }

        public void setHeight(double height) {
            this.height = height;
        }

        @Override
        public String toString() {
            return "User{" +
                    "id=" + id +
                    ", name='" + name + '\'' +
                    ", height=" + height +
                    '}';
        }
    }

}

执行结果：

用户：
    [User{id=1, name='用户-1', height=192.15677342306662}, 
     User{id=2, name='用户-2', height=196.35056058694772}, 
     User{id=3, name='用户-3', height=101.96271958293853}, 
     User{id=4, name='用户-4', height=110.83134063008366}, 
     User{id=5, name='用户-5', height=106.27720636757154}]
身高 总和：707.58
身高 最大：196.35
身高 最小：101.96
身高 平均：141.52

BigDecimal示例：

public class HelloWorld {
    private static final DecimalFormat df = new DecimalFormat("0.00");//保留两位小数点
    public static void main(String[] args) {
        Random random = new Random();
        List<User> list = new ArrayList<>();
        for(int i=1;i<=5;i++) {
            double weight = random.nextDouble() * 100 + 100;//随机身高：100-200
            list.add(new User(i, new BigDecimal(weight).setScale(BigDecimal.ROUND_HALF_UP, 2)));
        }
        System.out.println("list：" + list);
        BigDecimal add = list.stream().map(User::getHeight).reduce(BigDecimal.ZERO, BigDecimal::add);
        System.out.println("身高 总和：" + df.format(add));
        Optional<User> max = list.stream().max((u1, u2) -> u1.getHeight().compareTo(u2.getHeight()));
        System.out.println("身高 最大：" + df.format(max.get().getHeight()));
        Optional<User> min = list.stream().min((u1, u2) -> u1.getHeight().compareTo(u2.getHeight()));
        System.out.println("身高 最小：" + df.format(min.get().getHeight()));

    }
    private static class User{
        Integer id;
        BigDecimal height;//身高

        public User(Integer id, BigDecimal height) {
            this.id = id;
            this.height = height;
        }

        public Integer getId() {
            return id;
        }

        public void setId(Integer id) {
            this.id = id;
        }

        public BigDecimal getHeight() {
            return height;
        }

        public void setHeight(BigDecimal height) {
            this.height = height;
        }

        @Override
        public String toString() {
            return "User{" +
                    "id=" + id +
                    ", height=" + height +
                    '}';
        }
    }

}

执行结果：

list：
    [User{id=1, height=141.5472}, 
　　　　User{id=2, height=133.1609}, 
　　　　User{id=3, height=101.5403}, 
　　　　User{id=4, height=157.8470}, 
　　　　User{id=5, height=177.7596}]
身高 总和：711.8550
身高 最大：177.76
身高 最小：101.54

其他案例：

public class Apple {
    private Integer id;
    private String name;
    private BigDecimal money;
    private Integer num;
    public Apple(Integer id, String name, BigDecimal money, Integer num) {
        this.id = id;
        this.name = name;
        this.money = money;
        this.num = num;
    }
}

List<Apple> appleList = new ArrayList<>();//存放apple对象集合

Apple apple1 =  new Apple(1,"苹果1",new BigDecimal("3.25"),10);
Apple apple12 = new Apple(1,"苹果2",new BigDecimal("1.35"),20);
Apple apple2 =  new Apple(2,"香蕉",new BigDecimal("2.89"),30);
Apple apple3 =  new Apple(3,"荔枝",new BigDecimal("9.99"),40);

appleList.add(apple1);
appleList.add(apple12);
appleList.add(apple2);
appleList.add(apple3);

1. List转Map
id为key，apple对象为value，可以这么做：
/**
 * List -> Map
 * 需要注意的是：
 * toMap 如果集合对象有重复的key，会报错Duplicate key ....
 *  apple1,apple12的id都为1。
 *  可以用 (k1,k2)->k1 来设置，如果有重复的key,则保留key1,舍弃key2
 */
Map<Integer, Apple> appleMap = appleList.stream().collect(Collectors.toMap(Apple::getId, a -> a,(k1,k2)->k1));
打印appleMap：
{1=Apple{id=1, name='苹果1', money=3.25, num=10}, 2=Apple{id=2, name='香蕉', money=2.89, num=30}, 3=Apple{id=3, name='荔枝', money=9.99, num=40}}

 2. 分组
 List里面的对象元素，以某个属性来分组，例如，以id分组，将id相同的放在一起：
//List 以ID分组 Map<Integer,List<Apple>>
Map<Integer, List<Apple>> groupBy = appleList.stream().collect(Collectors.groupingBy(Apple::getId));

System.err.println("groupBy:"+groupBy);
{1=[Apple{id=1, name='苹果1', money=3.25, num=10}, Apple{id=1, name='苹果2', money=1.35, num=20}], 2=[Apple{id=2, name='香蕉', money=2.89, num=30}], 3=[Apple{id=3, name='荔枝', money=9.99, num=40}]}

3. 过滤filter: 从集合中过滤出来符合条件的元素(map只是覆盖属性，filter根据判断属性来collect宿主bean)：
//过滤出符合条件的数据
List<Apple> filterList = appleList.stream().filter(a -> a.getName().equals("香蕉")).collect(Collectors.toList());

System.err.println("filterList:"+filterList);
[Apple{id=2, name='香蕉', money=2.89, num=30}]

4. 求和: 将集合中的数据按照某个属性求和:
BigDecimal:
//计算 总金额
BigDecimal totalMoney = appleList.stream().map(Apple::getMoney).reduce(BigDecimal.ZERO, BigDecimal::add);
System.err.println("totalMoney:"+totalMoney); //totalMoney:17.48

Integer:
//计算 数量
int sum = appleList.stream().mapToInt(Apple::getNum).sum();
System.err.println("sum:"+sum); //sum:100

List<Integer> cc = new ArrayList<>();
cc.add(1);cc.add(2);cc.add(3);
int sum = cc.stream().mapToInt(Integer::intValue).sum();//6

★5    Collectors.groupingBy进行分组、排序等操作:
import javaX.Model.Student;

import java.util.Arrays;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.function.Function;
import java.util.stream.Collectors;

public class FunctionX {
    public static void main(String[] args) {
        //1.分组计数
        List<Student> list1= Arrays.asList(new Student(1,"one","zhao"),new Student(2,"one","qian"),new Student(3,"two","sun"));
        //1.1根据某个属性分组计数
        Map<String,Long> result1=list1.stream().collect(Collectors.groupingBy(Student::getGroupId,Collectors.counting()));
        System.out.println(result1);
        //1.2根据整个实体对象分组计数,当其为String时常使用
        Map<Student,Long> result2=list1.stream().collect(Collectors.groupingBy(Function.identity(),Collectors.counting()));
        System.out.println(result2);
        //1.3根据分组的key值对结果进行排序、放进另一个map中并输出
        Map<String,Long> xMap=new HashMap<>();
        result1.entrySet().stream().sorted(Map.Entry.<String,Long>comparingByKey().reversed()) //reversed不生效
                .forEachOrdered(x->xMap.put(x.getKey(),x.getValue()));
        System.out.println(xMap);

        //2.分组，并统计其中一个属性值得sum或者avg:id总和
        Map<String,Integer> result3=list1.stream().collect(
                Collectors.groupingBy(Student::getGroupId,Collectors.summingInt(Student::getId))
        );
        System.out.println(result3);

    }
}