import lombok.extern.slf4j.Slf4j;
import java.util.*;
import java.util.stream.Collectors;
import java.util.stream.Stream;
@Slf4j
public class StreamTest {
public static void main(String[] args) {
List<Integer> list = Arrays.asList(7, 6, 9, 3, 8, 2, 1,6,6,8);
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"));
personList.add(new Person("koukay", 9500, 26, "male", "New York"));
personList.add(new Person("houkay", 7800, 28, "male", "New York"));
/*maxLength();
more6Print(list, 6);
findFirst(list);
more6(list);
less6(list);
more7();
findPerson(personList);
maxValue();
maxSalary(personList);
more6Count(list);
upperCaseAdd3();
addSalary(personList);
splitList();
calculate();
sumAndMax(personList);
collectTo(list,personList);
operate(personList);
group(personList);
join(personList);
collectReducing(personList);
sort(personList);
*/
distinctAndSkip();
listMapOrder();
}
/**
* mapList排序
*/
private static void listMapOrder(){
List<Map<String,Double>> comments= new ArrayList<>();
for (int i = 0; i <10; i++) {
Map<String,Double> map= new HashMap<>();
map.put("DateStr",Math.random());
comments.add(map);
}
List<Map<String, Double>> collect = comments.stream().sorted(Comparator.comparing(StreamTest::comparingByData)).collect(Collectors.toList());
for (Map<String, Double> stringObjectMap : collect) {
System.out.println(stringObjectMap.get("DateStr"));
}
}
private static Double comparingByData(Map<String,Double> map){
return map.get("DateStr");
}
/**
* 流合并、去重、限制、跳过等操作。
*/
private static void distinctAndSkip(){
String[] arr1 = { "a", "b", "c", "d" };
String[] arr2 = { "d", "e", "f", "g" };
Stream<String> stream1 = Arrays.stream(arr1);
Stream<String> stream2 = Arrays.stream(arr2);
// concat:合并两个流 distinct：去重
List<String> collect1 = Stream.concat(stream1, stream2).distinct().collect(Collectors.toList());
// limit：限制从流中获得前n个数据
List<Integer> collect2 = Stream.iterate(1, x -> x + 2).limit(5).collect(Collectors.toList());
// skip：跳过前n个数据
List<Integer> collect3 = Stream.iterate(1, x -> x + 2).skip(2).limit(5).collect(Collectors.toList());
System.out.println("合并去重的结果为: "+collect1);
System.out.println("取出前五个数据: "+collect2);
System.out.println("跳过前两个数据: "+collect3);
}
/**
* 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
*/
private static void sort(List<Person> personList){
// 按工资增序排序
List<String> collect1 = personList.stream().sorted(Comparator.comparing(Person::getSalary)).map(Person::getName).collect(Collectors.toList());
// 按工资倒序排序
List<String> collect2 = personList.stream().sorted(Comparator.comparing(Person::getSalary).reversed()).map(Person::getName).collect(Collectors.toList());
// 先按工资再按年龄自然排序（从小到大）
List<String> collect3 = 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（从大到小）
List<String> collect4 = 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());
//先按工资再按年龄倒序
List<String> collect5 = 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（从大到小）
System.out.println("按工资增序排序: "+collect1);
System.out.println("按工资倒序排序: "+collect2);
System.out.println("先按工资再按年龄自然排序（从小到大）: "+collect3);
System.out.println("先按工资再按年龄自定义排序（从大到小）: "+collect4);
System.out.println("先按工资再按年龄倒序: "+collect5);
}
/**
* 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。
*/
private static void collectReducing(List<Person> personList){
// 每个员工减去起征点后的薪资之和
Optional<Integer> reduce = personList.stream().map(p -> p.getSalary() - 5000).reduce(Integer::sum);
Integer collect = personList.stream().collect(Collectors.reducing(0, Person::getSalary, (x, y) -> (x + y - 5000)));
System.out.println("员工扣税薪资总和1：" + reduce.get());
System.out.println("员工扣税薪资总和2：" + collect);
}
/**
* 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。
*/
private static void join(List<Person> personList){
String collect = personList.stream().map(Person::getName).collect(Collectors.joining("--"));
System.out.println("所有成员姓名为: "+collect);
List<String> list = Arrays.asList("A", "B", "C");
String collect1 = list.stream().collect(Collectors.joining("*"));
System.out.println("拼接后的字符串为: "+collect1);
}
/**
* 将员工按薪资是否高于8000分为两部分；将员工按性别和地区分组
*/
private static void group(List<Person> personList){
// 将员工按薪资是否高于8000分组
Map<Boolean, List<Person>> collect = personList.stream().collect(Collectors.partitioningBy(p -> p.getSalary() > 8000));
Map<Boolean, List<Person>> collect3 = personList.stream().collect(Collectors.groupingBy(p -> p.getSalary() > 8000));
// 将员工按性别分组
Map<String, List<Person>> collect1 = 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>>> collect2 = 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：" + collect);
System.out.println("员工按薪资是否大于8000分组情况：" + collect3);
System.out.println("员工按性别分组情况：" + collect1);
System.out.println("员工按性别、地区：" + collect2);
}
/**
* 统计员工人数、平均工资、工资总额、最高工资。
*/
private static void operate(List<Person> personList){
//员工人数
Long collect = personList.stream().collect(Collectors.counting());
//平均工资
Double collect1 = personList.stream().collect(Collectors.averagingDouble(p -> p.getSalary()));
//工资总额
Double collect2 = personList.stream().collect(Collectors.summingDouble(Person::getSalary));
//最高工资
Optional<Integer> collect3 = personList.stream().map(Person::getSalary).collect(Collectors.maxBy(Integer::compare));
DoubleSummaryStatistics collect4 = personList.stream().collect(Collectors.summarizingDouble(Person::getSalary));
log.info("员工人数为: {}, 平均工资为: {}, 工资总额为: {}, 最高工资为: {}, 查询工资所有为: {}",collect,collect1,collect2,collect3,collect4);
}
private static void collectTo(List<Integer> list, List<Person> personList){
List<Integer> collect1 = list.stream().filter(x -> x % 2 == 0).collect(Collectors.toList());
Set<Integer> collect2 = list.stream().filter(x -> x % 2 == 0).collect(Collectors.toSet());
Map<String, Person> collect = personList.stream().filter(p -> p.getSalary() > 8000).collect(Collectors.toMap(Person::getName, p -> p));
System.out.println(collect1);
System.out.println(collect2);
System.out.println(collect);
}
/**
* 求所有员工的工资之和和最高工资。
*/
private static void sumAndMax(List<Person> personList){
//员工工资之和方式一
Optional<Integer> reduce = personList.stream().map(Person::getSalary).reduce((p1, p2) -> p1 + p2);
//员工工资之和方式二
Integer reduce1 = personList.stream().reduce(0, (sum, p) -> sum += p.getSalary(), (sum1, sum2) -> sum1 + sum2);
//员工工资之和方式三
Optional<Integer> reduce2 = personList.stream().map(Person::getSalary).reduce(Integer::sum);
//员工工资之和方式四
Integer reduce3 = personList.stream().reduce(0, (sum, p) -> sum += p.getSalary(), Integer::sum);
//员工工资最高值一
Optional<Integer> reducemax1 = personList.stream().map(Person::getSalary).reduce(Integer::max);
//员工工资最高值二
Optional<Integer> reducemax2 = personList.stream().map(Person::getSalary).reduce((s1,s2)->s1>s2?s1:s2);
//员工工资最高值三
Integer reduce4 = personList.stream().reduce(0, (max, p) -> max > p.getSalary() ? max : p.getSalary(), Integer::max);
Integer reduce5 = personList.stream().reduce(0, (max, p) -> max > p.getSalary() ? max : p.getSalary() ,(max1,max2)->max1>max2?max1:max2);
log.info("员工工资之和1为: {},员工工资之和2为: {},员工工资之和3为: {},员工工资之和4为: {}",reduce.get(),reduce1,reduce2.get(),reduce3);
log.info("员工工资最高值1: {},员工工资最高值2: {},员工工资最高值3: {},员工工资最高值4: {}",reducemax1.get(),reducemax2.get(),reduce4,reduce5);
}
/**
* 求Integer集合的元素之和、乘积和最大值。
*/
private static void calculate(){
List<Integer> list = Arrays.asList(1, 3, 2, 8, 11, 4);
// 求和方式1
Optional<Integer> reduce = list.stream().reduce((x, y) -> x + y);
// 求和方式2
Optional<Integer> reduce1 = list.stream().reduce(Integer::sum);
// 求和方式3
Integer reduce2 = list.stream().reduce(0, Integer::sum);
log.info("求和方式1: {}, 方式2: {}, 方式3: {}",reduce.get(),reduce1.get(),reduce2);
// 求乘积
Optional<Integer> reduce3 = list.stream().reduce((x, y) -> x * y);
log.info("求乘积为: {}",reduce3.get());
// 求最大值方式1
Optional<Integer> reduce4 = list.stream().reduce((x, y) -> x > y ? x : y);
// 求最大值方式1
Optional<Integer> reduce5 = list.stream().reduce(Integer::max);
log.info("求最大值方法1: {},方式2: {}",reduce4.get(),reduce5.get());
}
/**
* 将两个字符数组合并成一个新的字符数组。
*/
private static void splitList(){
List<String> list = Arrays.asList("m,k,l,a", "1,3,5,7");
List<String> collect = list.stream().flatMap(str -> {
String[] split = str.split(",");
return Arrays.stream(split);
}).collect(Collectors.toList());
System.out.println(list);
System.out.println(collect);
}
/**
* 将员工的薪资全部增加1000。
* @param personList
*/
private static void addSalary(List<Person> personList){
List<Person> collect = personList.stream().map((person) -> {
person.setSalary(person.getSalary() + 1000);
return person;
}).collect(Collectors.toList());
collect.forEach(person -> {
log.info("{}调薪后的工资为{}",person.getName(),person.getSalary());
});
}
/**
* 英文字符串数组的元素全部改为大写。整数数组每个元素+3。
*/
private static void upperCaseAdd3(){
String[] strArr = { "abcd", "bcdd", "defde", "fTr" };
List<Integer> intList = Arrays.asList(1, 3, 5, 7, 9, 11);
List<String> collect1 = Arrays.stream(strArr).map(String::toUpperCase).collect(Collectors.toList());
List<Integer> collect = intList.stream().map(x -> x + 3).collect(Collectors.toList());
collect1.forEach(a->{
log.info("每个元素大写-> "+a);
});
collect.forEach(a->{
log.info("每个元素+3-> "+a);
});
}
private static void more6Count(List<Integer> list){
long count = list.stream().filter(x -> x > 6).count();
log.info("大于6的元素有{}个",count);
}
private static void maxSalary( List<Person> personList ){
Optional<Person> max = personList.stream().max(Comparator.comparing(Person::getSalary));
System.out.println("姓名: "+max.get().getName()+"--------工资 "+max.get().getSalary());
}
private static void maxValue(){
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> max1 = list.stream().max(new Comparator<Integer>() {
@Override
public int compare(Integer o1, Integer o2) {
return o2.compareTo(o1);
}
});
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：" + max1.get());
}
/**
* 获取String集合中最长的元素
*/
private static void maxLength(){
List<String> list = Arrays.asList("adnm", "admmt", "potjhgfdsatfd", "xbangd", "weoujgsd");
Optional<String> max = list.stream().max(Comparator.comparing(String::length));
System.out.println(max.get());
}
/**
* 遍历输出符合条件的元素 大于6
* @param list
* @param i
*/
private static void more6Print(List<Integer> list, int i) {
list.stream().filter(x -> x > i).forEach(System.out::println);
}
/**
* 匹配第一个
* @param list
*/
private static void findFirst(List<Integer> list) {
Optional<Integer> first = list.stream().filter(x -> x > 6).findFirst();
System.out.println("匹配第一个大于6的数-> "+first.get());
}
/**
* // 匹配任意（适用于并行流）大于6
* @param list
*/
private static void more6(List<Integer> list) {
Optional<Integer> any = list.parallelStream().filter(x -> x > 6).findAny();
System.out.println("匹配任意（适用于并行流）大于6-> "+any.get());
}
/**
* // 是否包含符合特定条件的元素 小于6
* @param list
*/
private static void less6(List<Integer> list) {
boolean b = list.stream().anyMatch(x -> x < 6);
System.out.println("是否包含小于6的元素-> "+b);
}
/**
* //筛选出Integer集合中大于7的元素，并打印出来
*/
private static void more7() {
List<Integer> list2 = Arrays.asList(6, 7, 3, 8, 1, 2, 9);
more6Print(list2, 7);
}
/**
* 筛选员工中工资高于8000的人，并形成新的集合
*/
public static void findPerson(List<Person> personList){
personList.stream().filter(p -> p.getSalary() > 8000).collect(Collectors.toList()).forEach((t)->{
System.out.println("姓名: "+t.getName()+"--------工资 "+t.getSalary());
});
}
}