stream流

根据cardId分组，取最大时间
Map<String, UserInfo> collect = list.parallelStream().collect(
        Collectors.toMap(UserInfo::getCardId, Function.identity(), (c1, c2) -> c1.getCreateTime() > c2.getCreateTime() ? c1 : c2));

根据userid分组，values字段求和
list.stream().collect(Collectors.groupingBy(User::getUserId,
           Collectors.reducing(BigDecimal.ZERO, 
                User::getValues, BigDecimal::add)));

根据age取最大值   
 Optional<Person> cacl2 = persons.stream()
                .reduce((p1, p2) -> p1.getAge() > p2.getAge() ? p1 : p2);
        cacl2.ifPresent(person -> {
            System.out.println("reduce" + JSON.toJSONString(person));
            //   reduce{"age":56,"name":"老周"}
        });

单子段分组

personList.stream().collect(Collectors.groupingBy(Person::getGender));

多字段分组

// 定义一个函数Function，该函数将元素对象映射到一个键的集合里
        Function<Person, List<Object>> compositeKey = person ->
                Arrays.asList(person.getGender(), person.getAge(), person.getType());

        // 分组
        Map<List<Object>, List<Person>> groupingMap =
                personList.stream().collect(Collectors.groupingBy(compositeKey, Collectors.toList()));

 list转为map

     Map<String, UserBO> maps1 = userInfoList.stream().collect(
                Collectors.toMap(UserBO::getUserId, id -> id));