1、filer
public void test01() {
List<Integer> list = Arrays.asList(7, 6, 9, 3, 8, 2, 1);
// 遍历输出符合条件的元素
list.stream().filter(x -> x > 6).forEach(System.out::println);
// 匹配第一个
Optional<Integer> findFirst = list.stream().filter(x -> x > 6).findFirst();
// 匹配任意（适用于并行流）
// 串行流：适合存在线程安全问题、阻塞任务、重量级任务，以及需要使用同一事务的逻辑。
// 并行流：适合没有线程安全问题、较单纯的数据处理任务。
Optional<Integer> findAny = list.parallelStream().filter(x -> x > 6).findAny();
// 是否包含符合特定条件的元素
boolean anyMatch = list.stream().anyMatch(x -> x < 6);
System.out.println("匹配第一个值：" + findFirst.get());
System.out.println("匹配任意一个值：" + findAny.get());
System.out.println("是否存在大于6的值：" + anyMatch);
}
2、to list
public class Person {
private String name; // 姓名
private int salary; // 薪资
private int age; // 年龄
private String sex; // 性别
private String area; // 地区
}
public void test03() {
List<Person> personList = new ArrayList<Person>();
personList.add(new Person("Tom", 8900, 23, "male", "New York"));
personList.add(new Person("Jack", 7000, 25, "male", "Washington"));
personList.add(new Person("Lily", 7800, 21, "female", "Washington"));
personList.add(new Person("Anni", 8200, 24, "female", "New York"));
personList.add(new Person("Owen", 9500, 25, "male", "New York"));
personList.add(new Person("Alisa", 7900, 26, "female", "New York"));
List<String> fiterList = personList.stream().filter(x -> x.getSalary() > 8000).map(Person::getName)
.collect(Collectors.toList());
System.out.print("高于8000的员工姓名：" + fiterList);
}
3、max
public void test04() {
List<String> list = Arrays.asList("adnm", "admmt", "pot", "xbangd", "weoujgsd");
Optional<String> max = list.stream().max(Comparator.comparing(String::length));
System.out.println("最长的字符串：" + max.get());
}
4、sort
public void test05() {
List<Integer> list = Arrays.asList(7, 6, 9, 4, 11, 6);
// 自然排序
Optional<Integer> max = list.stream().max(Integer::compareTo);
// 自定义排序
Optional<Integer> max2 = list.stream().max(new Comparator<Integer>() {
@Override
public int compare(Integer o1, Integer o2) {
return o1.compareTo(o2);
}
});
System.out.println("自然排序的最大值：" + max.get());
System.out.println("自定义排序的最大值：" + max2.get());
}
public void test06() {
List<Person> personList = new ArrayList<Person>();
personList.add(new Person("Tom", 8900, 23, "male", "New York"));
personList.add(new Person("Jack", 7000, 25, "male", "Washington"));
personList.add(new Person("Lily", 7800, 21, "female", "Washington"));
personList.add(new Person("Anni", 8200, 24, "female", "New York"));
personList.add(new Person("Owen", 9500, 25, "male", "New York"));
personList.add(new Person("Alisa", 7900, 26, "female", "New York"));
Optional<Person> max = personList.stream().max(Comparator.comparingInt(Person::getSalary));
System.out.println("员工工资最大值：" + max.get().getSalary());
}
5、count
public void test07() {
List<Integer> list = Arrays.asList(7, 6, 4, 8, 2, 11, 9);
long count = list.stream().filter(x -> x > 6).count();
System.out.println("list中大于6的元素个数：" + count);
}
6、对象转换
public void test09() {
List<Person> personList = new ArrayList<Person>();
personList.add(new Person("Tom", 8900, 23, "male", "New York"));
personList.add(new Person("Jack", 7000, 25, "male", "Washington"));
personList.add(new Person("Lily", 7800, 21, "female", "Washington"));
personList.add(new Person("Anni", 8200, 24, "female", "New York"));
personList.add(new Person("Owen", 9500, 25, "male", "New York"));
personList.add(new Person("Alisa", 7900, 26, "female", "New York"));
// 不改变原来员工集合的方式
List<Person> personListNew = personList.stream().map(person -> {
Person personNew = new Person(person.getName(), 0, 0, null, null);
personNew.setSalary(person.getSalary() + 10000);
return personNew;
}).collect(Collectors.toList());
System.out.println("一次改动前：" + personList.get(0).getName() + "-->" + personList.get(0).getSalary());
System.out.println("一次改动后：" + personListNew.get(0).getName() + "-->" + personListNew.get(0).getSalary());
// 改变原来员工集合的方式
List<Person> personListNew2 = personList.stream().map(person -> {
person.setSalary(person.getSalary() + 10000);
return person;
}).collect(Collectors.toList());
System.out.println("二次改动前：" + personList.get(0).getName() + "-->" + personListNew.get(0).getSalary());
System.out.println("二次改动后：" + personListNew2.get(0).getName() + "-->" + personListNew.get(0).getSalary());
}
一次改动前：Tom-->8900
一次改动后：Tom-->18900
二次改动前：Tom-->18900
二次改动后：Tom-->18900
7、转stream
public void test10() {
List<String> list = Arrays.asList("m,k,l,a", "1,3,5,7");
List<String> listNew = list.stream().flatMap(s -> {
// 将每个元素转换成一个stream
String[] split = s.split(",");
Stream<String> s2 = Arrays.stream(split);
return s2;
}).collect(Collectors.toList());
System.out.println("处理前的集合：" + list);
System.out.println("处理后的集合：" + listNew);
}
8、规约
归约，也称缩减，顾名思义，是把一个流缩减成一个值，能实现对集合求和、求乘积和求最值操作。
public void test11() {
List<Integer> list = Arrays.asList(1, 3, 2, 8, 11, 4);
// 求和方式1
Optional<Integer> sum = list.stream().reduce((x, y) -> x + y);
// 求和方式2
Optional<Integer> sum2 = list.stream().reduce(Integer::sum);
// 求和方式3
Integer sum3 = list.stream().reduce(0, Integer::sum);
// 求乘积
Optional<Integer> product = list.stream().reduce((x, y) -> x * y);
// 求最大值方式1
Optional<Integer> max = list.stream().reduce((x, y) -> x > y ? x : y);
// 求最大值写法2
Integer max2 = list.stream().reduce(12, Integer::max);
System.out.println("list求和：" + sum.get() + "," + sum2.get() + "," + sum3);
System.out.println("list求积：" + product.get());
System.out.println("list求和：" + max.get() + "," + max2);
}
public void test12() {
List<Person> personList = new ArrayList<Person>();
personList.add(new Person("Tom", 8900, 23, "male", "New York"));
personList.add(new Person("Jack", 7000, 25, "male", "Washington"));
personList.add(new Person("Lily", 7800, 21, "female", "Washington"));
personList.add(new Person("Anni", 8200, 24, "female", "New York"));
personList.add(new Person("Owen", 9500, 25, "male", "New York"));
personList.add(new Person("Alisa", 7900, 26, "female", "New York"));
// 求工资之和方式1：
Optional<Integer> sumSalary = personList.stream().map(Person::getSalary).reduce(Integer::sum);
// 求工资之和方式2：
Integer sumSalary2 = personList.stream().reduce(0, (sum, p) -> sum += p.getSalary(),
(sum1, sum2) -> sum1 + sum2);
// 求工资之和方式3：
Integer sumSalary3 = personList.stream().reduce(0, (sum, p) -> sum += p.getSalary(), Integer::sum);
// 求最高工资方式1：
Integer maxSalary = personList.stream().reduce(0, (max, p) -> max > p.getSalary() ? max : p.getSalary(),
Integer::max);
// 求最高工资方式2：
Integer maxSalary2 = personList.stream().reduce(0, (max, p) -> max > p.getSalary() ? max : p.getSalary(),
(max1, max2) -> max1 > max2 ? max1 : max2);
System.out.println("工资之和：" + sumSalary.get() + "," + sumSalary2 + "," + sumSalary3);
System.out.println("最高工资：" + maxSalary + "," + maxSalary2);
}
9、归集
即toList/toSet/toMap
public void test13() {
List<Integer> list = Arrays.asList(1, 6, 3, 4, 6, 7, 9, 6, 20);
List<Integer> listNew = list.stream().filter(x -> x % 2 == 0).collect(Collectors.toList());
Set<Integer> set = list.stream().filter(x -> x % 2 == 0).collect(Collectors.toSet());
List<Person> personList = new ArrayList<Person>();
personList.add(new Person(null, 8900, 23, "male", "New York"));
personList.add(new Person("Jack", 7000, 25, "male", null));
personList.add(new Person("Lily", 7800, 21, "female", "Washington"));
personList.add(new Person("Anni", 8200, 24, "female", "New York"));
Map<?, Person> map = personList.stream().filter(p -> p.getSalary() > 8000)
.collect(Collectors.toMap(Person::getName, p -> p));
System.out.println("toList:" + listNew);
System.out.println("toSet:" + set);
System.out.println("toMap:" + map);
Map<String, String> collect2 = personList.stream().collect(Collectors.toMap(Person::getName, Person::getArea));
System.out.println(collect2);
Map<String, String> collect = personList.stream().collect(Collectors.toMap(Person::getName, Person::getArea));
System.out.println(collect);
}
10、统计
count/averaging
public void test14() {
List<Person> personList = new ArrayList<Person>();
personList.add(new Person("Tom", 8900, 23, "male", "New York"));
personList.add(new Person("Jack", 7000, 25, "male", "Washington"));
personList.add(new Person("Lily", 7800, 21, "female", "Washington"));
// 求总数
Long count = personList.stream().collect(Collectors.counting());
// 求平均工资
Double average = personList.stream().collect(Collectors.averagingDouble(Person::getSalary));
// 求最高工资
Optional<Integer> max = personList.stream().map(Person::getSalary).collect(Collectors.maxBy(Integer::compare));
// 求工资之和
Integer sum = personList.stream().collect(Collectors.summingInt(Person::getSalary));
// 一次性统计所有信息
DoubleSummaryStatistics collect = personList.stream().collect(Collectors.summarizingDouble(Person::getSalary));
System.out.println("员工总数：" + count);
System.out.println("员工平均工资：" + average);
System.out.println("员工工资总和：" + sum);
System.out.println("员工工资所有统计：" + collect);
}
11、分组
partitioningBy/groupingBy
public void test15() {
List<Person> personList = new ArrayList<Person>();
personList.add(new Person("Tom", 8900, 18, "male", "New York"));
personList.add(new Person("Jack", 7000, 18, "male", "Washington"));
personList.add(new Person("Lily", 7800, 18, "female", "Washington"));
personList.add(new Person("Anni", 8200, 18, "female", "New York"));
personList.add(new Person("Owen", 9500, 18, "male", "New York"));
personList.add(new Person("Alisa", 7900, 18, "female", "New York"));
// 将员工按薪资是否高于8000分组
Map<Boolean, List<Person>> part = personList.stream().collect(Collectors.partitioningBy(x -> x.getSalary() > 8000));
// 将员工按性别分组
Map<String, List<Person>> group = personList.stream().collect(Collectors.groupingBy(Person::getSex));
// 将员工先按性别分组，再按地区分组
Map<String, Map<String, List<Person>>> group2 = personList.stream().collect(Collectors.groupingBy(Person::getSex, Collectors.groupingBy(Person::getArea)));
System.out.println("员工按薪资是否大于8000分组情况：" + part);
System.out.println("员工按性别分组情况：" + group);
System.out.println("员工按性别、地区：" + group2);
}
12、joining
joining可以将stream中的元素用特定的连接符（没有的话，则直接连接）连接成一个字符串。
public void test16() {
List<Person> personList = new ArrayList<Person>();
personList.add(new Person("Tom", 8900, 23, "male", "New York"));
personList.add(new Person("Jack", 7000, 25, "male", "Washington"));
personList.add(new Person("Lily", 7800, 21, "female", "Washington"));
String names = personList.stream().map(p -> p.getName()).collect(Collectors.joining(","));
System.out.println("所有员工的姓名：" + names);
List<String> list = Arrays.asList("A", "B", "C");
String string = list.stream().collect(Collectors.joining("-"));
System.out.println("拼接后的字符串：" + string);
}
13、reducing
Collectors类提供的reducing方法，相比于stream本身的reduce方法，增加了对自定义归约的支持。
public void test17() {
List<Person> personList = new ArrayList<Person>();
personList.add(new Person("Tom", 8900, 23, "male", "New York"));
personList.add(new Person("Jack", 7000, 25, "male", "Washington"));
personList.add(new Person("Lily", 7800, 21, "female", "Washington"));
// 每个员工减去起征点后的薪资之和（这个例子并不严谨，但一时没想到好的例子）
Integer sum = personList.stream().collect(Collectors.reducing(0, Person::getSalary, (i, j) -> (i + j - 5000)));
System.out.println("员工扣税薪资总和：" + sum);
// stream的reduce
Optional<Integer> sum2 = personList.stream().map(Person::getSalary).reduce(Integer::sum);
System.out.println("员工薪资总和：" + sum2.get());
}
14、排序
sorted，中间操作。有两种排序：
sorted()：自然排序，流中元素需实现Comparable接口。
sorted(Comparator com)：Comparator排序器自定义排序。
public void test18() {
List<Person> personList = new ArrayList<Person>();
personList.add(new Person("Sherry", 9000, 24, "female", "New York"));
personList.add(new Person("Tom", 8900, 22, "male", "Washington"));
personList.add(new Person("Jack", 9000, 25, "male", "Washington"));
personList.add(new Person("Lily", 8800, 26, "male", "New York"));
personList.add(new Person("Alisa", 9000, 26, "female", "New York"));
long count = personList.stream().map(Person::getSalary).distinct().count();
System.out.println(count);
personList.stream().sorted(Comparator.comparing(Person::getSalary)).map(Person::getName);
// 按工资升序排序（自然排序）
List<String> newList = personList.stream().sorted(Comparator.comparing(Person::getSalary)).map(Person::getName)
.collect(Collectors.toList());
// 按工资倒序排序
List<String> newList2 = personList.stream().sorted(Comparator.comparing(Person::getSalary).reversed())
.map(Person::getName).collect(Collectors.toList());
// 先按工资再按年龄升序排序
List<String> newList3 = personList.stream()
.sorted(Comparator.comparing(Person::getSalary).thenComparing(Person::getAge)).map(Person::getName)
.collect(Collectors.toList());
// 先按工资再按年龄自定义排序（降序）
List<String> newList4 = personList.stream().sorted((p1, p2) -> {
if (p1.getSalary() == p2.getSalary()) {
return p2.getAge() - p1.getAge();
} else {
return p2.getSalary() - p1.getSalary();
}
}).map(Person::getName).collect(Collectors.toList());
System.out.println("按工资升序排序：" + newList);
System.out.println("按工资降序排序：" + newList2);
System.out.println("先按工资再按年龄升序排序：" + newList3);
System.out.println("先按工资再按年龄自定义降序排序：" + newList4);
}
15、提取/组合
流也可以进行合并、去重、限制、跳过等操作。
public void test19() {
String[] arr1 = {"a", "b", "c", "d"};
String[] arr2 = {"d", "e", "f", "g"};
Stream<String> stream1 = Stream.of(arr1);
Stream<String> stream2 = Stream.of(arr2);
// concat:合并两个流 distinct：去重
List<String> newList = Stream.concat(stream1, stream2).distinct().collect(Collectors.toList());
// limit：限制从流中获得前n个数据
List<Integer> collect = Stream.iterate(1, x -> x + 2).limit(10).collect(Collectors.toList());
// skip：跳过前n个数据
List<Integer> collect2 = Stream.iterate(1, x -> x + 2).skip(1).limit(5).collect(Collectors.toList());
System.out.println("流合并：" + newList);
System.out.println("limit：" + collect);
System.out.println("skip：" + collect2);
}
16、collect详解
public class CollectTest {
/**
* stream.collect() 的本质由三个参数构成,
* 1. Supplier 生产者, 返回最终结果
* 2. BiConsumer<R, ? super T> accumulator 累加器
* 第一个参数是要返回的集合, 第二个参数是遍历过程中的每个元素,
* 将流中每个被遍历的元素添加到集合中
* 3. BiConsumer<R, R> combiner 合并器, 在有并行流的时候才会有用, 一个流时代码不会走到这里
* 将第二步遍历得到的所有流形成的list都添加到最终的list中,
* 最后返回list1
*/
@Test
public void Test() {
Stream<String> stream = Stream.of("hello", "world", "helloworld");
// 最原始和基础的方式
/*
List<String> list = stream.collect(
()->new ArrayList(),
(theList, item) -> theList.add(item),
(list1, list2) -> list1.addAll(list2)
);
*/
// 打印出更详尽的过程
List<String> listDetail = stream.collect(
() -> {
ArrayList<String> arrayList = new ArrayList<>();
System.out.println("第一个list诞生, size: " + arrayList.size());
return arrayList;
},
(theList, item) -> {
System.out.println("第二个list的size: " + theList.size());
theList.add(item);
},
(list1, list2) -> {
System.out.println("第三个list1的size: " + list1.size());
System.out.println("第四个list2的size: " + list2.size());
list1.addAll(list2);
}
);
/* 输出
第一个list诞生, size: 0
第二个list的size: 0
第二个list的size: 1
第二个list的size: 2
* */
// 使用方法引用来传递行为, 更加清晰易懂, new(新建) -> add(累加) -> addAll(合并)
List<String> list2 = stream.collect(LinkedList::new, LinkedList::add, LinkedList::addAll);
String concat = stream.collect(StringBuilder::new, StringBuilder::append, StringBuilder::append).toString();
System.out.println(concat);
}
@Test
public void Test2() {
Stream<String> stream = Stream.of("hello", "world", "helloworld");
// 这样的写法兼具灵活和简单
ArrayList<String> list = stream.collect(Collectors.toCollection(ArrayList::new));
TreeSet<String> treeSet = stream.collect(Collectors.toCollection(TreeSet::new));
String s = stream.collect(Collectors.joining()); // 拼接成字符串
HashMap<String, String> map = stream.collect(HashMap::new, (x, y) -> {
x.put(y, y); // 自己做自己的key
}, HashMap::putAll);
}
}
17、flatMap
public void test() {
List<String> teamIndia = Arrays.asList("Virat", "Dhoni", "Jadeja");
List<String> teamAustralia = Arrays.asList("Warner", "Watson", "Smith");
List<String> teamEngland = Arrays.asList("Alex", "Bell", "Broad");
List<List<String>> playersInWorldCup2016 = new ArrayList<>();
playersInWorldCup2016.add(teamIndia);
playersInWorldCup2016.add(teamAustralia);
playersInWorldCup2016.add(teamEngland);
// Let's print all players before Java 8
List<String> listOfAllPlayers = new ArrayList<>();
for (List<String> team : playersInWorldCup2016) {
for (String name : team) {
listOfAllPlayers.add(name);
}
}
System.out.println("Players playing in world cup 2016");
System.out.println(listOfAllPlayers);
// Now let's do this in Java 8 using FlatMap
List<String> flatMapList = playersInWorldCup2016.stream()
// .flatMap(pList -> pList.stream())
.flatMap(List::stream)
.collect(Collectors.toList());
System.out.println("List of all Players using Java 8");
System.out.println(flatMapList);
}
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