java8中用流收集数据
用流收集数据
汇总
long howManyDishes = menu.stream().collect(Collectors.counting());
int totalCalories = menu.stream().collect(summingInt(Dish::getCalories));
//求平均值
double avgCalories = menu.stream().collect(averagingInt(Dish::getCalories));
//summarizing操作可以得到总和.平均值.最大值.最小值
IntSummaryStatistics menuStatistics = menu.stream().collect(summarizingInt(Dish::getCalories));
//打印可得
IntSummaryStatistics{count= 9,sum=4300,min=120,average=477.777,max = 800};
查找最大值和最小值
Comparator<Dish> dishCaloriesComparator = Comparator.comparingInt(Dish::getCalories);
Optional<Dish> mostCalorieDish = menu.stream().collect(maxBy(dishCaloriesComparator));
连接字符串
//joining在内部使用了StringBuilder来把生成的字符串逐个追加起来
String shortMenu = menu.stream().map(Dish::getName).collect(joning());
//用逗号分隔
String shortMenu2 = menu.stream().map(Dish::getName).collect(joning(","));
广义的归约汇总
int totalCalories = menu.stream().collect(reducing(0,Dish::getCalories,(i,j)->j+i));
reducing需要说那个参数:
1.起始值
2.被操作的值
3.是一个BinaryOperator,将两个项目累计成一个同类型的值
同理,可以求最高热量的菜
Optional<Dish> mostCalorieDish = menu.stream().collect(reducing(d1,d2)->d1.getCalories()>d2.getCalories()?d1:d2));
分组
Map<Dish.Type,List<Dish> dishesByType = menu.stream().collect(groupingBy(Dish::getType));
复杂的分组
public enum CaloricLevel{DIET,NORMAL,FAT}
Map<CaloricLevel,List<Dish>> dishesByCaloricLevel = menu.stream().collect(
groupingBy(dish ->{
if(dish.getCalories()<=400) return CaloricLevel.DIET;
else if(dish.getCalories() <= 700) return CaloricLevel.NORMAL:
else return CaloricLevel.FAT;
})
);
按子组收集数据
Map<Dish.Type,Long> typesCount = menu.stream().collect(
groupingBy(Dish::getType,counting()));
1.查找每个子组中热量最高的Dish
Map<Dish.Type,Dish> mostCaloricByType = menu.stream().collect(groupingBy(Dish::getType,collectingAndThen(
maxBy(comparingInt(Dish::getCalories)),Optional::get)));
2.对每组进行求和
Map<Dish.Type,Integer> totalCaloriesByType = menu.stream().collect(groupingBy(Dish::getType,summingInt(Dish::getCalories)));
3.groupingBy和mapping收集器结合起来
Map<Dish.Type,Set<CaloricLevel>> caloricLevelsByType = menu.stream().collect(
groupingBy(Dish::getType,mapping(
dish -> {
if(dish.getCalories()<=400) return CaloricLevel.DIET;
else if (dish.getCalories <= 700) return CaloricLevel.NORMAL;
else return CaloricLevel.FAT,toSet()
}
))
);
分区:
Map<Boolean , List<Dish>> partitionedMenu = menu.stream().collect(partitioningBy(Dish::isVegetarian));
partitioningBy工厂方法有一个重载版本,可以传递第二收集器
Map<Boolean,Map<Dish.Type,List<Dish>>> vegetarianDishesByType = menu.stream().collect(
partitioningBy(Dish::isVegetarian,groupingBy(Dish::getType)));
还可以重用前面的代码来找到素食和非素食中热量最高的菜:
Map<Boolean, Dish> mostVegetarian = menu.stream().collect(
menu.stream().collect(
partitioningBy(Dish::isVegetarian,
collectingAndThe(
maxBy(comparingInt(Dish::getCalories)),
Optional::get))));
将数字按质数和非质数分区
public boolean isPrime(int candidate){
return IntStream.range(2,candidate)//产生一个自然数范围,从2开始,直至但不包括待测数
.noneMatch(i -> candidate % i ==0);//如果待测数字不能被流中任何数字整除则返回true
}
//一个简单的优化是仅测试小于等于待测数平方根因子
public boolean isPrime(int candidate) {
int candidateRoot = (int) Math.sqrt(candidate);
return IntStream.rangeClosed(2, candidate).noneMatch(i -> candidate % i == 0);
}
public Map<Boolean, List<Integer>> partitionPrimes(int n) {
return IntStream.rangeClosed(2, n).boxed().collect(partitioningBy(candidate -> isPrime(candidate)));
}
Collectors类的静态工厂方法
工厂方法 | 返回类型 | 用于 |
---|---|---|
toList | List< T > | 把流中所有项目收集到一个List |
List< Dish > dishes = menuStream.collect(toList()); | ||
toSset | Set< T > | 把流中所有项目收集到一个Set,删除重复项 |
Set< Dish > dishes = menuStream.collect(toSet()); | ||
toCollection | Collection< T > | 把流中所有项目收集到给定的供应源创建的集合 |
Collection< Dish > dishes = menuStream.collect(toCollection(),ArrayList::new); | ||
counting | Long | 计算流中元素的个数 |
long howManyDishes = menuStream.collect(counting()); | ||
summingInt | Integer | 对流中项目的一个整数属性求和 |
int totalCalories = menuStream.collect(summingInt(Dish::getCalories)); | ||
averagingInt | Double | 计算流中项目Integer属性的平均值 |
double avgCalories = menuStream.collect(averagingInt(Dish::getCalories)); | ||
summarizingInt | IntSummaryStatistics | 收集关于流中项目Integer属性的统计值,例如最大,最小,总和与平均值 |
IntSummaryStatistics menuStaticstics = menuStream.collect(summarizingInt(Dish::getCalories)); | ||
joining | String | 连接对流中每个项目调用toString方法生成的字符串 |
String shortMenu = menuStream.map(Dish::getName).collect(joining(", ")); | ||
maxBy | Optional< T > | 选出最大元素的Optional |
Optional< Dish > fattest = menuStream.collect(maxBy(comparingInt(Dish::getCalories))); | ||
minBy | Optional< T > | 最小元素 |
Optional< Dish > fattest = menuStream.collect(minBy(comparingInt(Dish::getCalories))); | ||
reducing | 归约操作产生的类型 | 利用BinaryOperator与流中的元素逐个结合,从而将流归约为单个值 |
int totalCalories = menuStream.collect(reducing(0,Dish::getCalories,Integer::sum)); | ||
collectingAndThen | 转换函数返回的类型 | 包裹另一个收集器,对其结果应用转换函数 |
int howManyDishes = menuStream.collect(collectingAndThe(toList(),List::size)); | ||
groupingBy | Map< K ,List< T > > | 根据项目的一个属性的值对流中的项目作问组,并将属性值作为结果Map的键 |
Map< Dish.Type,List< Dish>> dishesByType = menuStream.collect(groupingBy(Dish::getType)); | ||
partitioningBy | Map< Boolean,List< T>> | 分区 |
Map< Boolean, List< t>> vegetarianDishes = menuStream.collect(partitioningBy(Dish::isVegetarian)); | ||