java 8 lambda表达式list操作分组、过滤、求和、最值、排序、去重

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java8的lambda表达式提供了一些方便list操作的方法，主要涵盖分组、过滤、求和、最值、排序、去重。跟之前的传统写法对比，能少写不少代码。

新建实体类

package com.vvvtimes.vo;

import java.math.BigDecimal;
import java.util.Date;

public class User {

    private Long id;

    //姓名
    private String name;

    //年龄
    private int age;

    //工号
    private String jobNumber;

    //性别
    private String sex;

    //入职日期
    private Date entryDate;

    //家庭成员数量
    private BigDecimal familyMemberQuantity;

    public Long getId() {
        return id;
    }

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

    public String getName() {
        return name;
    }

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

    public int getAge() {
        return age;
    }

    public void setAge(int age) {
        this.age = age;
    }

    public String getJobNumber() {
        return jobNumber;
    }

    public void setJobNumber(String jobNumber) {
        this.jobNumber = jobNumber;
    }

    public String getSex() {
        return sex;
    }

    public void setSex(String sex) {
        this.sex = sex;
    }

    public Date getEntryDate() {
        return entryDate;
    }

    public void setEntryDate(Date entryDate) {
        this.entryDate = entryDate;
    }

    public BigDecimal getFamilyMemberQuantity() {
        return familyMemberQuantity;
    }

    public void setFamilyMemberQuantity(BigDecimal familyMemberQuantity) {
        this.familyMemberQuantity = familyMemberQuantity;
    }
}

1.分组

通过groupingBy可以分组指定字段

        //分组
        Map<String, List<User>> groupBySex = userList.stream().collect(Collectors.groupingBy(User::getSex));
        //遍历分组
        for (Map.Entry<String, List<User>> entryUser : groupBySex.entrySet()) {
            String key = entryUser.getKey();
            List<User> entryUserList = entryUser.getValue();
        }

上门的分组存在key空值安全问题，需要做过滤或封装处理

用Optional封装使用中会报No value present

 //分组添加累计
                Map<Optional<Long>, List<SalesOrderMonthlyStatementVo>> groupMap = list.stream().collect(Collectors.groupingBy(x -> Optional.ofNullable(x.getReviewerGroupId())));
                //遍历分组
                for (Map.Entry<Optional<Long>, List<SalesOrderMonthlyStatementVo>> entryGroup : groupMap.entrySet()) {
                    Optional<Long> key = entryGroup.getKey();
                    Long groupId = key.get();
                    List<SalesOrderMonthlyStatementVo> entryGroupList = entryGroup.getValue();
}

正确使用方法如下，自定义groupingBy_WithNullKeys

/** Like Collectors.groupingBy, but accepts null keys. */
    public static <T, A> Collector<T, ?, Map<A, List<T>>>
    groupingBy_WithNullKeys(Function<? super T, ? extends A> classifier) {
        return Collectors.toMap(
                classifier,
                Collections::singletonList,
                (List<T> oldList, List<T> newEl) -> {
                    List<T> newList = new ArrayList<>(oldList.size() + 1);
                    newList.addAll(oldList);
                    newList.addAll(newEl);
                    return newList;
                });
    }

然后调用

Map<Long, List<SalesOrderMonthlyStatementVo>> groupMap = list.stream().collect(groupingBy_WithNullKeys(x -> x.getReviewerGroupId()));

多字段分组

        Function<WarehouseReceiptLineBatch, List<Object>> compositeKey = wlb ->
                Arrays.<Object>asList(wlb.getWarehouseReceiptLineId(), wlb.getWarehouseAreaId(), wlb.getWarehouseLocationId());
        Map<Object, List<WarehouseReceiptLineBatch>> map =
                warehouseReceiptLineBatchList.stream().collect(Collectors.groupingBy(compositeKey, Collectors.toList()));
        //遍历分组
        for (Map.Entry<Object, List<WarehouseReceiptLineBatch>> entryUser : map.entrySet()) {
            List<Object> key = (List<Object>) entryUser.getKey();
            List<WarehouseReceiptLineBatch> entryUserList = entryUser.getValue();
            Long warehouseReceiptLineId = (Long) key.get(0);
            Long warehouseAreaId = (Long) key.get(1);
            Long warehouseLocationId = (Long) key.get(2);

        }

2.过滤

通过filter方法可以过滤某些条件

        //过滤
        //排除掉工号为201901的用户
        List<User> userCommonList = userList.stream().filter(a -> !a.getJobNumber().equals("201901")).collect(Collectors.toList());

3.求和

分基本类型和大数类型求和，基本类型先mapToInt，然后调用sum方法，大数类型使用reduce调用BigDecimal::add方法

        //求和
        //基本类型
        int sumAge = userList.stream().mapToInt(User::getAge).sum();
        //BigDecimal求和
        BigDecimal totalQuantity = userList.stream().map(User::getFamilyMemberQuantity).reduce(BigDecimal.ZERO, BigDecimal::add);

上面的求和不能过滤bigDecimal对象为null的情况，可能会报空指针，这种情况，我们可以用filter方法过滤，或者重写求和方法

重写求和方法

package com.vvvtimes.util;

import java.math.BigDecimal;

public class BigDecimalUtils {

    public static BigDecimal ifNullSet0(BigDecimal in) {
        if (in != null) {
            return in;
        }
        return BigDecimal.ZERO;
    }

    public static BigDecimal sum(BigDecimal ...in){
        BigDecimal result = BigDecimal.ZERO;
        for (int i = 0; i < in.length; i++){
            result = result.add(ifNullSet0(in[i]));
        }
        return result;
    }
}

使用重写的方法

BigDecimal totalQuantity2 = userList.stream().map(User::getFamilyMemberQuantity).reduce(BigDecimal.ZERO, BigDecimalUtils::sum);

判断对象空

stream.filter(x -> x!=null)

stream.filter(Objects::nonNull)

判断字段空

stream.filter(x -> x.getDateTime()!=null)

4.最值

求最小与最大，使用min max方法

        //最小
        Date minEntryDate = userList.stream().map(User::getEntryDate).min(Date::compareTo).get();

        //最大
        Date maxEntryDate = userList.stream().map(User::getEntryDate).max(Date::compareTo).get();

有时候我们需要知道最大最小对应的这个对象，我们可以通过如下方法获取

Comparator<LeasingBusinessContract> comparator = Comparator.comparing(LeasingBusinessContract::getLeaseEndDate);
LeasingBusinessContract maxObject = leasingBusinessContractList.stream().max(comparator).get();

5.List 转map

         /**
         * 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 ....
         *  user1,user2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<Long, User> userMap = userList.stream().collect(Collectors.toMap(User::getId, a -> a,(k1,k2)->k1));

list转map的时候有时候会将date类型作为key，实际情况中使用string的多，我们可以将某个字段转成string

Map<String, WorkCenterLoadVo> workCenterMap = list.stream().collect(Collectors.toMap(key->DateFormatUtils.format(key.getDate(), "yyyy-MM-dd"), a -> a,(k1,k2)->k1));

list转map有时候会用到多字段key的map结构，除了常用的key用字符串连接，也可以使用apache commons的多字段key形式的map结构MultiKeyMap

6.排序

可通过Sort对单字段多字段排序

        //排序
        //单字段排序，根据id排序
        userList.sort(Comparator.comparing(User::getId));
        //多字段排序，根据id，年龄排序
        userList.sort(Comparator.comparing(User::getId).thenComparing(User::getAge));

实际上这个写法存在空值安全问题，建议改成

userList.sort(Comparator.comparing(User::getId,Comparator.nullsLast(Comparator.naturalOrder())).thenComparing(User::getAge,Comparator.nullsLast(Comparator.naturalOrder())));

7.去重

可通过distinct方法进行去重

        //去重
        List<Long> idList = new ArrayList<Long>();
        idList.add(1L);
        idList.add(1L);
        idList.add(2L);
        List<Long> distinctIdList = idList.stream().distinct().collect(Collectors.toList());

针对属性去重

List<AddOutboundNoticeDetailsBatchVo> entryDetailsBatchDistinctBatchIdList = entryDetailsBatchList.stream().filter(distinctByKey(b -> b.getMaterialBatchNumberId())).collect(Collectors.toList());
                
//distinctByKey自己定义
    public static <T> Predicate<T> distinctByKey(Function<? super T, Object> keyExtractor) {
        Map<Object, Boolean> seen = new ConcurrentHashMap<>();
        return t -> seen.putIfAbsent(keyExtractor.apply(t), Boolean.TRUE) == null;
    }

8.获取list某个字段组装新list

        //获取list对象的某个字段组装成新list
        List<Long> userIdList = userList.stream().map(a -> a.getId()).collect(Collectors.toList());

9.批量设置list列表字段为同一个值

addList.stream().forEach(a -> a.setDelFlag("0"));

10.不同实体的list拷贝

List<TimePeriodDate> timePeriodDateList1 = calendarModelVoList.stream().map(p->{TimePeriodDate e = new TimePeriodDate(); e.setStartDate(p.getBegin());e.setEndDate(p.getEnd()); return e;}).collect(Collectors.toList());