1. 集合的Lambda --forEach 使用

package com.wudl.java8.lambda;

import com.wudl.java8.bean.User;

import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

/**
 * @ClassName : LambaMethod
 * @Description :  Lamba 方法的使用
 * @Author :wudl
 * @Date: 2021-08-17 22:35
 */

public class LambaMethod {

    public static void main(String[] args) {

        //1.list ForEach 的输出
        LambaMethod.LambaList();
        //2.Map 的输出
        LambaMethod.LambaMap();
        //3. List 集合排序
        LambaMethod.getListSort();
    }

    public static void LambaList()
    {
        List<String> list = new ArrayList<String>();
        list.add("java");
        list.add("hive");
        list.add("Flink");

        list.forEach((num) -> {
            System.out.println(num);
        });
    }

    public static void LambaMap()
    {
        Map<String,Object> map = new HashMap<>();
        map.put("java","java-version");
        map.put("hive","hive-version");
        map.put("Flink","Flink-version");

        map.forEach((num,value) -> {
            System.out.println(num +"---"+ value);
        });
    }


}

// 输出的结果
"C:\Program Files\Java\jdk1.8.0_241\bin\java.exe" -Dvisualvm.id=4964856337000 "-javaagent:D:\Program Files\JetBrains\IntelliJ IDEA 
-----------------LambaList--------------
java
hive
Flink
-----------------LambaMap--------------
hive---hive-version
java---java-version
Flink---Flink-version

1.1 集合的排序实例

package com.wudl.java8.lambda;

import com.wudl.java8.bean.User;

import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

/**
 * @ClassName : LambaMethod
 * @Description :  Lamba 方法的使用
 * @Author :wudl
 * @Date: 2021-08-17 22:35
 */

public class LambaMethod {

    public static void main(String[] args) {
        //3. List 集合排序
        LambaMethod.getListSort();
    }


    public  static  void  getListSort()
    {
        System.out.println("-----------------getListSort--------------");
        List<User> list = new ArrayList<>();
        list.add(new User("java",18));
        list.add(new User("spark",10));
        list.add(new User("doris",15));
        list.add(new User("flink",20));

        list.sort((key1,value1) ->
            key1.getAge() - value1.getAge()
        );

        list.forEach(value1 ->{
            System.out.println(value1);
        });
    }
}
// 输入的结果
-----------------getListSort--------------
User(name=spark, age=10)
User(name=doris, age=15)
User(name=java, age=18)
User(name=flink, age=20)

Process finished with exit code 0

2.Java8 的Stream 的使用

    java8 引入的流主要是针对集合的操作： 类似Sql 查询数据库

功能 :Stream ：非常方便精简的形式遍历集合实现 过滤、排序等。

Stram 操作.png

2.1 Stream 流的创建方式

1. parallelStream为并行流采用多线程执行
2.Stream采用单线程执行
3.parallelStream效率比Stream要高。

  List<User> userEntities = new ArrayList<>();
        userEntities.add(new User("mayikt", 20));
        userEntities.add(new User("meite", 28));
        userEntities.add(new User("zhangsan", 35));
        userEntities.add(new User("xiaowei", 16));
        userEntities.add(new User("xiaowei", 16));

        userEntities.stream();
        Stream<User> userStream = userEntities.parallelStream();

2.2 将创建的流转化为Set 集合并且打印出来

package com.wudl.java8.stream;

import com.wudl.java8.bean.User;

import java.util.ArrayList;
import java.util.List;
import java.util.Set;
import java.util.stream.Collectors;
import java.util.stream.Stream;

/**
 * @ClassName : UserStream
 * @Description : Stream  的使用
 * @Author :wudl
 * @Date: 2021-08-17 22:59
 */

public class UseStream {

    public static void main(String[] args) {
    //
        UseStream.StreamToSet();
    }

    /**
     * 流的创建
     * @return
     */
    public static Stream<User> CreateStream()
    {
        List<User> userEntities = new ArrayList<>();
        userEntities.add(new User("mayikt", 20));
        userEntities.add(new User("meite", 28));
        userEntities.add(new User("zhangsan", 35));
        userEntities.add(new User("xiaowei", 16));
        userEntities.add(new User("xiaowei", 16));

        userEntities.stream();
        Stream<User> userStream = userEntities.parallelStream();
        return userStream;
    }

    /**
     * 将lIST 转为流 在通过流转化为Set 集合
     */
    public static void StreamToSet()
    {
        Stream<User> userStream = UseStream.CreateStream();
        Set<User> userSet = userStream.collect(Collectors.toSet());
        System.out.println("----------------StreamToSet---------------");
        System.out.println(userSet);
    }
}

// 打印结果
Connected to the target VM, address: '127.0.0.1:52982', transport: 'socket'
----------------StreamToSet---------------
[User(name=meite, age=28), User(name=zhangsan, age=35), User(name=xiaowei, age=16), User(name=mayikt, age=20)]


Process finished with exit code 0

************************************** 后期追加*************************************

1.将list 转为流， 在通过流转化为map 集合

   /**
     * 1.将list 转为流， 在通过流转化为map 集合
     */
    public static void StreamToMap() {
        Stream<User> userStream = UseStream.CreateStream();
        Map<String, User> userMap = userStream.collect(Collectors.toMap(new Function<User, String>() {
                   @Override
                   public String apply(User userEntity) {
                       return userEntity.getName();
                   }
               }, new Function<User, User>() {

                   @Override
                   public User apply(User User) {
                       return User;
                   }
               }
        ));
        userMap.forEach(new BiConsumer<String, User>() {
            @Override
            public void accept(String s, User user) {
                System.out.println(s + "====" + user.toString());
            }
        });
    }

2.通过流就和 resuce

 /**
     * 2.通过流就和 resuce
     */
    public static void StreamToReduceToSum() {
        Stream<Integer> stream = Stream.of(1, 2, 5, 6, 8);
        // 第一种求和实现
//        Optional<Integer> reduce = stream.reduce((a1, a2) -> a1 + a2);
        // 第二种求和实现
        Optional<Integer> reduce = stream.reduce(new BinaryOperator<Integer>() {
            @Override
            public Integer apply(Integer o, Integer o2) {
                return o + o2;
            }
        });
        System.out.println(reduce);
    }

3.通过流求出两个流的最大值和最小值 max 和 min

    /**
     * 3.通过流求出两个流的最大值和最小值  max  和 min
     */
    public static void StreamMaxAndMin() {
        // 求最小值
        Stream<User> userStream = UseStream.CreateStream();
        Optional<User> max = userStream.max((a1, a2) -> {
            return a1.getAge() - a2.getAge();
        });
        System.out.println("max---" + max);

        // 求最小值
        Stream<User> userStreamMin = UseStream.CreateStream();
        Optional<User> min = userStreamMin.min((a1, a2) -> {
            return a1.getAge() - a2.getAge();
        });
        System.out.println("min--" + min);
    }

4. Match 元素返回true 和false

4.1 anyMatch表示，判断的条件里，任意一个元素成功，返回true
4.2 allMatch表示，判断条件里的元素，所有的都是，返回true
4.3 noneMatch跟allMatch相反，判断条件里的元素，所有的都不是，返回true

 /**
     * 4. 根据流匹配一个值 返回  true or false
     *      anyMatch表示，判断的条件里，任意一个元素成功，返回true
     *      allMatch表示，判断条件里的元素，所有的都是，返回true
     *      noneMatch跟allMatch相反，判断条件里的元素，所有的都不是，返回true
     */
    public static void StreamMatch() {
        Stream<User> userStream = UseStream.CreateStream();
        boolean b = userStream.noneMatch(new Predicate<User>() {
            @Override
            public boolean test(User user) {
                return user.getAge() > 50;
            }
        });

        //  5. allMatch  全匹配
        Stream<User> userStream2 = UseStream.CreateStream();
        boolean flink = userStream2.allMatch(new Predicate<User>() {
            @Override
            public boolean test(User user) {
                return user.getAge()<20;
            }
        });
        System.out.println("allMatch--"+flink);

        System.out.println(b);
    }

6. 流的循环

    /**
     *  6. 流的循环
     */
    public static void MyStreamFor()
    {
        Stream<User> userStream = UseStream.CreateStream();
        userStream.forEach(new Consumer<User>() {
            @Override
            public void accept(User user) {
                System.out.println(user.getAge() +"--"+user.getName());
            }
        });

        Stream<User> userStreamForeach = UseStream.CreateStream();
        userStreamForeach.forEach((user ->{
            System.out.println("2--"+user.getAge() +"--"+user.getName());
        }));

    }

7.Stream过滤器

    /**
     *  7.Stream过滤器
     */
    public  static void StreamFilter()
    {
        Stream<User> userStream = UseStream.CreateStream();
        Stream<User> flink = userStream.filter(new Predicate<User>() {
            @Override
            public boolean test(User user) {
                return user.getAge() > 20;
            }
        }).filter(new Predicate<User>() {
            @Override
            public boolean test(User user) {
                return user.getName().equals("Flink");
            }
        });
        flink.forEach(user ->{
            System.out.println(user.toString());
        });
    }

8.流的排序

 /**
     *  8.流的排序
     */

    public static  void StreamTOSort()
    {
        List<User> userEntities = new ArrayList<>();
        userEntities.add(new User("mayikt", 20));
        userEntities.add(new User("meite", 28));
        userEntities.add(new User("zhangsan", 35));
        userEntities.add(new User("xiaowei", 16));
        userEntities.add(new User("Flink", 22));
        userEntities.add(new User("hdfs", 18));
        List<User> collect = userEntities.stream().sorted(Comparator.comparing(User::getAge)).collect(Collectors.toList());
        collect.forEach(new Consumer<User>() {
            @Override
            public void accept(User user) {
                System.out.println(user.toString());
            }
        });
    }

9. Stream Skip 和Limit

    /**
     *  9. Stream Skip  和Limit
     */
    public static void StreamLimitAndSkip()
    {
        List<User> userEntities = new ArrayList<>();
        userEntities.add(new User("mayikt", 20));
        userEntities.add(new User("meite", 28));
        userEntities.add(new User("zhangsan", 35));
        userEntities.add(new User("xiaowei", 16));
        userEntities.add(new User("Flink", 22));
        userEntities.add(new User("hdfs", 18));

        Stream<User> stream = userEntities.stream();
        stream.skip(2).limit(3).forEach(u ->{
            System.out.println(u.toString());
        });

    }