Stream operation of JDK8

Everyone says I’m ugly, but I’m just not so beautiful--smilefyou

Stream related operations

characteristic

不是数据结构，没有内部存储。
不支持索引访问。
延迟计算
支持并行
很容易生成数据或集合
支持过滤，查找，转换，汇总，聚合等操作。

mechanism

1.Stream分为创建操作，中间操作，终止操作。
2.流的源可以是一个数组，集合，生成器方法，I/O通道等等
3.一个流可以有零个或多个中间操作，每一个中间操作都会返回一个新的流，供下一个操作使用，一个流只会有一个终止操作。
4.Stream只有遇到终止操作，它的源才会开始执行遍历操作。

Create operation

数组:Stream.of()
集合:stream()
通过Stream.generate方法来创建
通过Stram.iterate方法
其他

Intermediate operation

1.distinct to duplicate

List<Integer> list = Arrays.asList(1, 2, 1, 3, 3, 2, 4);
List<Integer> newList = list.stream().distinct().collect(Collectors.toList());

2.filter filter

list.stream().filter(i -> i % 2 == 0).collect(Collectors.toList());

3.sorted sort

list.stream().sorted().collect(Collectors.toList());//默认自然排序从小到大
list.stream().sorted(Comparator.reverseOrder()).collect(Collectors.toList());//倒序
list.stream().sorted(Comparator.comparing(User::getAge)).collect(Collectors.toList());

limit && skip

list.stream().limit(1).collect(Collectors.toList());
list.stream().skip(1).collect(Collectors.toList());

map induction

list.stream().map(object::getName).collect(Collectors.toList());

Terminate operation

collect

list.stream().limit(2).collect(Collectors.toList());
list.stream().limit(2).collect(Collectors.toSet());
list.stream().limit(2).collect(Collectors.toMap(Object::getName, Object::getAge));

Calculate min, max, count, average

Optional<Integer> min = list.stream().reduce(Integer::min);
Optional<Integer> max = list.stream().reduce(Integer::max);

anyMatch matches any one

boolean b = list.stream().anyMatch(Object::isDel);

allMatch matches all

boolean b = list.stream().allMatch(o -> o.getAge() < 30);

noneMatch does not match

boolean b = list.stream().noneMatch(o -> o.getAge() > 30);

findFirst

Optional<Object> optional = list.stream().filter(Object::isDel).findFirst();

findAny

Optional<Object> optional = list.stream().filter(Object::isDel).findAny();

reduce protocol

List<Integer> list = Arrays.asList(1, 2, 3, 6, 8);
Integer reduce = list.stream().reduce(0, (a, b) -> a + b);

Collectors

计算总和: int i = list.stream().collect(Collectors.summingInt(Object::getMath));

Comparator<Object> 比较器 = Comparator.comparingInt(Object::getAge);
流中最大值: Optional<Object> optional = list.stream().collect(Collectors.maxBy(比较器));
流中最小值: Optional<Object> optional = list.stream().collect(Collectors.minBy(比较器));

summingInt summary

int collect = list.stream().collect(Collectors.summingInt(Object::getNum));

averagingInt average

 Double average = list.stream().collect(Collectors.averagingInt(Object::getNum));

joining connection string

String names = dish.stream().map(Object::getName).collect(Collectors.joining());

String names = dish.stream().map(Object::getName).collect(Collectors.joining(","));

counting total

long sum = list.stream().collect(Collectors.counting());

grouping By

Map<Object.Type, List<Dish>> collect = list.stream().collect(Collectors.groupingBy(Object::getType));3

//自定义分组条件
Map<String, List<Person>> collect = list.stream().collect(Collectors.groupingBy(Person->{
        if (Person.getAge() <= 18) {
            return "未成年";
        } else if (Person.getAge() <= 40) {
            return "中年";
        } else {
            return "老年";
        }
    }));

Multi-level grouping

 Map<Person.Type, Map<String, List<Person>>> collect = list.stream().collect(Collectors.groupingBy(Person::getSex, Collectors.groupingBy(p -> {
        if (p.getAge() <= 18) {
            return "未成年";
        } else if (p.getAge() <= 40) {
            return "中年";
        } else {
            return "老年人";
        }
    })));

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