1、Strem函数
Listlist = new ArrayList<>(); //根据age对list分组,得到map Map > groupByAge=list.stream().collect(Collectors.groupingBy(People::getAge)); //根据age进行排序(reserve倒序)得到排序后的List List peopleListSorted = list.stream().sorted(Comparator.comparing(People::getAge).reversed()).collect(Collectors.toList()); //提取age,去重后排序 List ageList = list.stream().map(People::getAge).distinct().sorted().collect(Collectors.toList()); //提取年龄大于20的people List olderThan20 = list.stream().filter(e->Integer.parseInt(e.getAge()) > 20).collect(Collectors.toList()); //累加List中的money BigDecimal totalMoney = list.stream().map(People::getMoney).reduce(BigDecimal.ZERO, BigDecimal::add); //查询 People people = list.stream().filter(e->e.getAge().equals("20")).findFirst().orElse(null); //List -> Map (name,people) //对象集合转化为map Map map = list.stream().collect(Collectors.toMap(People::getName,n->n)); //查找流中最大值和最小值 List personList = generatePersonList(); Person olderOne = personList.stream().max(Comparator.comparing(Person::getAge)).orElse(null); Person youngerOne = personList.stream().min(Comparator.comparing(Person::getAge)).orElse(null); //对象去重 ArrayList collect = personList.stream().collect( Collectors.collectingAndThen( Collectors.toCollection (() -> new TreeSet<>(Comparator.comparingInt(Person::getAge))),ArrayList::new) );
2、optinal判断空处理
对于深度嵌套的语句,可能需要多次判空,才能保证代码的健壮性,但是用if来实现,会有一堆的if语句,java8通过optinal比较优雅的解决了这个问题。
举个例子:
String isocode = user.getAddress().getCountry().getIsocode().toUpperCase();
通常if判断的做法
if (user != null) {
Address address = user.getAddress();
if (address != null) {
Country country = address.getCountry();
if (country != null) {
String isocode = country.getIsocode();
if (isocode != null) {
isocode = isocode.toUpperCase();
}
}
}
}
Optional的做法
String isocode = Optional.ofNullable(user)
.map(User::getAddress)
.map(Address::getCountry)
.map(Country::getIsocode)
.orElse("default");
3、Stream的groupby
group by生成一个拥有分组功能的Collector,有三个重载方法
- 需要一个参数:按照该参数进行分组。结果返回一个Map集合,每个Map的key默认是分组参数的类型,value是一个List集合。
Map> collect = users.stream().collect(Collectors.groupingBy(User: :getEdu));
- 需要两个参数:第二参数是Collector类型,可以对value进行处理。
可以对结果进行映射 Map> collect = users.stream().collect( Collectors.groupingBy(User: :getEdu, //第二个参数对Map的value进行处理(映射) Collectors.mapping(User: :getId, Collectors.toList())) ); 可以对结果进行求和 Map collect = users.stream().collect( Collectors.groupingBy(User: :getEdu, //对参数进行累计求和 Collectors.summingDouble(User: :getPrice)) ); 可以对结果进行统计 Map < String,Long > collect = users.stream().collect( Collectors.groupingBy(User: :getEdu, //获取count数量 Collectors.counting()) );
- 需要三个参数,第三个参数添加了对结果Map的生成方式,默认是HashMap
Mapcollect = users.stream().collect( Collectors.groupingBy(User: :getEdu, //决定map的生成方式,使用TreeMap TreeMap: :new, //对参数进行累计求和 Collectors.summingDouble(User: :getPrice)) );



