Lambda--Optional、Collectors高级进阶方法

2 年前

Empirefree

Lambda--Collectors、optional高级使用

偶然看到了同事groupingBy用法，然后百度衍生出了optional，collectors，map等各种用法。突然发现自己之前写的代码又烂又复杂了，后面用optional可以防止空指针，collectors也可以极大简化代码量。

1.Optional

2.Collectors

1.Optional

optional里面有防止空指针的语句，但我觉得有些时候报空指针错更方便定位到问题。比如从库里查找出数据，没找到但是你初始化了一个默认值做了后续处理并返回给前端展示了，这其实就算是BUG了，当然有些时候避免空指针报错也是非常不错的选择。

1.1.Optional--基本方法

//of会报空指针，ofNullable不会(可以防止空指针)，而是重新new个optional
Optional.of()
Optional.ofNullable
//user不为空即输出 
Optional.ofNullable(user).ifPresent(System.out::println); 
//user为空则重新new一个
Optional.ofNullable(user).orElse(User.builder().build());
//user为空则报空指针错误(虽然ofNullable里面new了optional，但user依然会为空)
Optional.ofNullable(user).orElseThrow(() -> new NullPointerException());    
//user为空则重新new一个
Optional.ofNullable(user).orElseGet(() -> User.builder().build());
//初始化list数组
List<String> list = null;
List<String> newList = Optional.ofNullable(list).orElse(Lists.newArrayList());

1.2.Optional--filter、map

Optional中可以像stream流一样操作数据

/**
 * @program: springboot
 * @description:
 * @author: huyuqiao
 * @create: 2021/08/07 10:57
@Data
@Builder(toBuilder = true)
public class UserInfo {
    private String name;
    private String email;
    private Integer price;
@Test
public void optionalTest(){
    // Optional--操作对象：filter
    UserInfo userInfo = UserInfo.builder()
        .name("huyuqiao")
        .email("1842449680@qq.com")
        .price(100)
        .build();
    UserInfo newUserInfo = Optional.ofNullable(userInfo).filter(u -> u.getPrice() < 1000).orElse(UserInfo.builder().build());
    System.out.println(newUserInfo);
    // Optional--操作对象：map
    String name = Optional.ofNullable(userInfo).map(UserInfo::getName).orElse("自定义姓名");
    System.out.println(name);
    // Optional--操作对象：flatmap
    Optional.ofNullable(userInfo).flatMap(u -> Optional.ofNullable(u.getName()));
}

1.2.Optional--flatMap

flatMap:扁平化获取层级下的元素并组装成同一层级。

比如现有数组[[1],[2],[3]]，要提取里面所有元素并组装成[1,2,3]，可利用flatMap获取

@Test
    public void flatMapTest(){
        List<List<Integer>> outer = new ArrayList<>();
        List<Integer> inner1 = new ArrayList<>();
        inner1.add(1);
        inner1.add(9);
        List<Integer> inner2 = new ArrayList<>();
        inner2.add(2);
        List<Integer> inner3 = new ArrayList<>();
        inner3.add(3);
        List<Integer> inner4 = new ArrayList<>();
        inner4.add(4);
        List<Integer> inner5 = new ArrayList<>();
        inner5.add(5);
        outer.add(inner1);
        outer.add(inner2);
        outer.add(inner3);
        outer.add(inner4);
        outer.add(inner5);
        List<Integer> result = outer.stream().flatMap(inner -> inner.stream().map(i -> i + 1)).collect(Collectors.toList());
        System.out.println(result);
//[2, 10, 3, 4, 5, 6]

2.Collectors

会使用了optional基本语句后，后面就可以开始使用Collectors语句了，个人感觉对开发非常实用，可以极大简化代码开发量。先给出基本类，然后就可以使用了

/**
 * @program: springboot
 * @description:
 * @author: huyuqiao
 * @create: 2021/08/06 10:10
import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;
 * 学生信息
@Data
@AllArgsConstructor
@NoArgsConstructor
public class Student {
    /** 姓名 */
    private String name;
    /** 总分 */
    private int totalScore;
    /** 是否本地人 */
    private boolean local;
    /** 年级 */
    private GradeType gradeType;
     * 年级类型
    public enum GradeType {ONE,TWO,THREE}
}

2.1.averagingDouble--计算平均值

注意： double格式可以表示-253到253范围内的所有连续整数。如果管道有超过253的值，则平均计算中的除数将在253处饱和，从而导致额外的数值误差。（所以计算数多时需要专用BigDecimal进行计算）

//统计所有学生的平均总成绩
	@Test
    public void averagingDoubleTest(){
        Double avgScore = menu.stream().collect(Collectors.averagingDouble(Student::getTotalScore));
        Optional.ofNullable(avgScore).ifPresent(System.out::println);
    }

2.2.collectingAndThen--转换类型

collectingAndThen方法：调整Collector收集器以执行其它的结束转换

@Test
    public void collectingAndThenTest(){
        // unmodifiablelist:不能add,set。arrays.aslist可以set，但是不能add
        List<Student> studentList = menu.stream().collect(Collectors.collectingAndThen(Collectors.toList(), Collections::unmodifiableList));
        System.out.println(studentList);
        //collectingandthen:计算总平均值并转换成自定义字符串返回
        Optional.ofNullable(menu.stream().collect(
                Collectors.collectingAndThen(Collectors.averagingInt(Student::getTotalScore), a -> "the average totalscore is" + a)
        )).ifPresent(System.out::println);
    }

2.3.counting--类似count()

counting方法：统计collectors收集器元素

@Test
    public void countingTest(){
        Optional.of(menu.stream().collect(Collectors.counting())).ifPresent(System.out::println);
// 7

2.4.groupingBy*、groupingByConcurrent--分组（重点）

groupingBy方法：分组并返回到map中（个人感觉非常好用,对商品进行分组返回给前端，大大简化了代码量）。

groupingByConcurrent：并发分组，无法保证返回数据类型的顺序或线程安全性

//按对象某一属性进行分组
    @Test
    public void groupByTest(){
        Map<Student.GradeType, List<Student>> collect = menu.stream().collect(Collectors.groupingBy(Student::getGradeType));
        Optional.ofNullable(collect).ifPresent(System.out::println);
        //{THREE=[Student(name=刘一, totalScore=721, local=true, gradeType=THREE), Student(name=陈二, totalScore=637, local=true, gradeType=THREE), Student(name=张三, totalScore=666, local=true, gradeType=THREE), Student(name=王五, totalScore=483, local=false, gradeType=THREE), Student(name=赵六, totalScore=367, local=true, gradeType=THREE)], TWO=[Student(name=李四, totalScore=531, local=true, gradeType=TWO)], ONE=[Student(name=孙七, totalScore=499, local=false, gradeType=ONE)]}
        //分组后统计每组的平均分数值，并对每组key升序排列
        Map<Student.GradeType, Double> map = menu.stream().collect(Collectors.groupingBy(Student::getGradeType, TreeMap::new , Collectors.averagingInt(Student::getTotalScore)));
        Optional.ofNullable(map).ifPresent(System.out::println);
        //{ONE=499.0, TWO=531.0, THREE=574.8}
    }

GroupingBy其他功能：按单个属性、多个属性，条件分组、多级分组、分组后组装成其他集合

package com.empirefree.springboot;
import com.alibaba.fastjson.JSON;
import lombok.Data;
import lombok.extern.slf4j.Slf4j;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.test.context.junit4.SpringRunner;
import java.math.BigDecimal;
import java.util.*;
import java.util.stream.Collectors;
 * @program: springboot
 * @description:
 * @author: huyuqiao
 * @create: 2021/08/05 09:47
@RunWith(SpringRunner.class)
@SpringBootTest
@Slf4j
public class CollectorsTest {
    @Data
    public class Product {
        private final Long id;
        private final Integer num;
        private final BigDecimal price;
        private final String name;
        private final String category;
    @Test
    public void testanything(){
        // 参考文章：https://blog.csdn.net/u014231523/article/details/102535902
        Product prod1 = new Product(1L, 1, new BigDecimal("15.5"), "面包", "零食");
        Product prod1_1 = new Product(11L, 11, new BigDecimal("15.5"), "面包", "零食");
        Product prod2 = new Product(2L, 2, new BigDecimal("20"), "饼干", "零食");
        Product prod3 = new Product(3L, 3, new BigDecimal("30"), "月饼", "零食");
        Product prod4 = new Product(4L, 3, new BigDecimal("10"), "青岛啤酒", "啤酒");
        Product prod5 = new Product(5L, 10, new BigDecimal("15"), "百威啤酒", "啤酒");
        List<Product> prodList = Arrays.asList(prod1, prod1_1, prod2, prod3, prod4, prod5);
        Object object7 = prodList.stream().collect(Collectors.collectingAndThen(Collectors.maxBy(Comparator.comparingInt(Product::getNum)), Optional::get));
        System.out.println(object7);
        // 1、按某个属性分组
        Map<String, List<Product>> productMap = prodList.stream().collect(Collectors.groupingBy(Product::getCategory));
        System.out.println(JSON.toJSONString(productMap));
        // 2、按多个属性分组
        Map<String, List<Product>> productMap2 = prodList.stream().collect(Collectors.groupingBy(item -> item.getCategory() + "_" + item.getName()));
        System.out.println(JSON.toJSONString(productMap2));
        // 3、按条件分组
        Map<String, List<Product>> productMap3 = prodList.stream().collect(Collectors.groupingBy(item ->{
            if (item.getNum() < 3){
                return "3";
            } else {
                return "other";
        System.out.println(JSON.toJSONString(productMap3));
        // 4、多级分组
        Map<String, Map<String, List<Product>>> productMap4 = prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.groupingBy(item ->{
            if (item.getNum() < 3){
                return "3";
            } else {
                return "other";
        })));
        System.out.println(JSON.toJSONString(productMap4));
        // 5、分组求总数、求和
        Map<String, Long> productMap5 = prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.counting()));
        Map<String, Integer> productMap6 = prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.summingInt(Product::getNum)));
        System.out.println(JSON.toJSONString(productMap5));
        System.out.println(JSON.toJSONString(productMap6));
        // 6、分组后只获取最大值
        Map<String, Product> prodMap7 = prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.collectingAndThen(Collectors.maxBy(Comparator.comparingInt(Product::getNum)), Optional::get)));
        System.out.println(prodMap7);
        // 7、分组后组装成其他集合
        Map<String, Set<String>> productMap8 = prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.mapping(Product::getName, Collectors.toSet())));
        System.out.println(JSON.toJSONString(productMap8));
}

2.5.partitioningBy--分区

partitioningBy方法：分区计算。返回map的可序列化和线程安全性无法保证

partitioningBy：返回map的key是Boolean。无法保证线程安全性

groupingBy：返回map的key是分组的值。可以保证线程安全性

@Test
    public void partitioningByTest(){
        Map<Boolean, Double> collect = menu.stream().collect(Collectors.partitioningBy(Student::isLocal, Collectors.averagingInt(Student::getTotalScore)));
        Optional.ofNullable(collect).ifPresent(System.out::println);
    }

2.6.joining--拼接元素

joining方法：连接colletors的每个元素

@Test
    public void joiningTest(){
        Optional.ofNullable(menu.stream().map(Student::getName).collect(Collectors.joining(",", "[", "]"))).ifPresent(System.out::println);
        //[刘一,陈二,张三,李四,王五,赵六,孙七]
    }

2.7.mapping--类似map

mapping方法：类似于map()。

@Test
    public void mappingTest(){
        Optional.ofNullable(menu.stream().collect(Collectors.mapping(Student::getName, Collectors.joining(",", "[", "]")))).ifPresent(System.out::println);
    }

2.8.maxBy、minBy--类型max(),min()

maxBy、minBy方法：获取比较器最大和最小值。返回的是Optional

@Test
    public void maxOrMinByTest(){
        menu.stream().collect(Collectors.maxBy(Comparator.comparing(Student::getTotalScore))).ifPresent(System.out::println);
        menu.stream().collect(Collectors.minBy(Comparator.comparing(Student::getTotalScore))).ifPresent(System.out::println);
    }

2.9.reducing--类型reduce()

reducing方法：对收集器元素计算

@Test
    public void reducingTest(){
        Integer result = menu.stream().map(Student::getTotalScore).collect(Collectors.reducing(0, (a, b) -> a + b));
        System.out.println(result);
    }

2.10.summarizingDouble*--汇总max,min,count,sum,avg(妙点)

summarizingDouble方法：汇总list中某属性的所有汇总值(最大、最小、总数，总和,平均值)

@Test
    public void summarizingInt(){
        DoubleSummaryStatistics result = menu.stream().collect(Collectors.summarizingDouble(Student::getTotalScore));
        Optional.ofNullable(result).ifPresent(System.out::println);
    }

2.11.toCollection--转换成集合

toCollection方法：转换收集器的集合类型

//转换成LinkedList
	@Test
    public void toCollectionTest(){
        Optional.of(menu.stream().filter(s -> s.getTotalScore() > 600).collect(Collectors.toCollection(LinkedList::new))).ifPresent(s -> {
            System.out.println(s.getClass());
            System.out.println(s);
    }

2.12.toMap--转换成list

toMap方法：可以将list转换成map(但要注意key值重复与value为空情况)

@Test
    public void listToMapTest(){
        // 1 list to map -- obj
        List<User> users = Arrays.asList(
                new User(101, "Jack"),
                new User(102, "Kreas"),
                new User(103, "Marry"),
//                new User(103, "Marry2"),
                new User(104, "Timi"),
                new User(105, "Alice")
//                new User(105, null)
        // key不能有重复
        Map<Long, User> map = users.stream().collect(Collectors.toMap(User::getId, o -> o));
        System.out.println(JSON.toJSONString(map));
        // 1.2 list to map -- 属性
        Map<Long, String> map2 = users.stream().collect(Collectors.toMap(User::getId, User::getName));
        System.out.println(JSON.toJSONString(map2));
        // 3 list to map -- 解决key重复  value为空则报空指针
        Map<Long, String> map3 = users.stream().collect(Collectors.toMap(User::getId, User::getName, (o1, o2) -> o1));
        System.out.println(JSON.toJSONString(map3));
        Map<Long, String> map4 = users.stream().collect(Collectors.toMap(User::getId, User::getName, (o1, o2) -> o2));
        System.out.println(JSON.toJSONString(map4));
        Map<Long, String> map5 = users.stream().collect(Collectors.toMap(User::getId, User::getName, (o1, o2) -> o1 + "," + o2));
        System.out.println(JSON.toJSONString(map5));
        // 4 list to map -- 解决value为空，但不能解决key值重复
        Map<Long, String> map6 = users.stream().collect(Collectors.toMap(User::getId, o -> o.getName() == null ? "" : o.getName()));
        System.out.println(JSON.toJSONString(map6));
    }

注意：当有key重复以及value为null情况时，个人建议还是直接用put/putIfAbsent。

Map<Long, String> map7 = new HashMap<>();
users.stream().forEach(user -> map7.put(user.getId(), user.getName()));
System.out.println(map7);

3.总结

个人认为：
Optional.ofNullable(对象).orElse(对象.builder().build())：防止空指针非常实用
Collectors里面最重要的当属groupingBy与summarizingDouble。其他的个人觉得知道要能看得懂是干什么用的，毕竟很多都可以直接在stream里面直接处理好，没必要在collect里面处理。
另外：
map中重复值+1操作：computeIfAbsent可以实现
提取List成list<>：flatMap可以实现
List转map：map的put/putifAbsent即可

Collectors参考链接： https:// blog.csdn.net/sl1992/ar ticle/details/98900343

toMap参考链接： https://zyqok.blog.csdn.net/article/details/108646765?utm_medium=distribute.pc_relevant.none-task-blog-2%7Edefault%7EsearchFromBaidu%7Edefault-1.pc_relevant_baidujshouduan&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2%7Edefault%7EsearchFromBaidu%7Edefault-1.pc_relevant_baidujshouduan

4.补充

4.1.Map操作--compute计算

Map：判断list值，没有就添加，有就value+1

@Test
    public void mapTest(){
        * compute：计算并更新值(但是可能会空指针)
            computeIfAbsent：Value不存在时才计算
            computeIfPresent：Value存在时才计算
        HashMap<String, Integer> prices = new HashMap<>();
        // 往HashMap中添加映射关系
        prices.put("Shoes", 180);
        prices.put("Bag", 300);
        prices.put(null, 150);
        prices.put(null, 250);
        System.out.println("HashMap: " + prices);
        //有就不put，没有才put
        prices.putIfAbsent("Shoes", 1810);
        //有才put，没有不put
        prices.computeIfPresent("Shoes3", (key, value) -> value + 100);
        //有就不put
        prices.computeIfAbsent("Shoes4", key -> 18120);
        //无论有无都put计算
        prices.compute("Shoes2", (key, value) -> 1810);
        prices.compute("Shoes2", (key, value) -> 1820);
        System.out.println(prices);
        //给map中put值，有就 + 1，没有就添加初始化为0
        Map<String, AtomicInteger> countTagClientMap = new LinkedHashMap<>();
        countTagClientMap.computeIfAbsent("a", value -> new AtomicInteger()).incrementAndGet();     //这个可以实现为空就put，否则 + 1
        countTagClientMap.computeIfAbsent("a", value -> new AtomicInteger());
        System.out.println(countTagClientMap);
        countTagClientMap.computeIfPresent("a", (key, value) -> new AtomicInteger(value.incrementAndGet()));
        countTagClientMap.compute("a", (key, value) -> value == null ? new AtomicInteger(1) : new AtomicInteger(value.incrementAndGet())); //这个可以实现为空就put，否则 + 1
        System.out.println(countTagClientMap);
    }

4.2.TreeMap--排序操作

treeMap：treeMap默认是对key值升序排序

@Test
    public void treeMap() {
        // 对key值排序
        TreeMap<Integer, Integer> map1 = new TreeMap<Integer, Integer>();  //默认的TreeMap升序排列
        TreeMap<Integer, Integer> map2 = new TreeMap<Integer, Integer>(Comparator.reverseOrder());
        map2.put(1, 2);
        map2.put(2, 4);
        map2.put(7, 1);
        map2.put(5, 2);
        System.out.println("Map2=" + map2);