collectors常用方法-526互联

-- 伪数据
-- id,name,age,grade-- 年级,chineseScore-- 语文成绩,mathScore-- 数学成绩,englishScore-- 英语成绩
Student a = new Student(1, "a", 16, "高一", 120, 130, 125);
Student b = new Student(2, "b", 17, "高二", 80, 90, 80);
Student c = new Student(3, "c", 18, "高三", 130.1, 130, 100);
1.toCollection(collectionFactory)
@Test
public void toCollectionTest() {
//将学生年级放入集合
TreeSet<String> grades = students.stream()
.map(Student::getGrade).collect(Collectors.toCollection(TreeSet::new));
System.out.println(grades.toString());
}
//[高一, 高三, 高二]

2.toList()
@Test
public void toListTest() {
//将学生名字放入集合
List<String> names = students.stream()
.map(Student::getName).collect(Collectors.toList());
System.out.println(names.toString());
}

3.toSet()
@Test
public void toSetTest() {
//将学生语文成绩放入集合
Set<Double> chineseScores = students.stream()
.map(Student::getChineseScore).collect(Collectors.toSet());
System.out.println(chineseScores.toString());
}

4.toSet()
@Test
public void toSetTest() {
//将学生语文成绩放入集合
Set<Double> chineseScores = students.stream().map(Student::getChineseScore).collect(Collectors.toSet());
System.out.println(chineseScores.toString());
}

5.toMap(keyMapper, valueMapper, mergeFunction)
-- toConcurrentMap也一样！
@Test
public void toMapWithMergeTest() {
//将学生学号和班级放入map，当出现相同key时，用新值替换旧值
Map<Long, String> map = students.stream().collect(Collectors.toMap(student -> student.getId(), student -> student.getGrade(), (oldValue, newValue) -> newValue));
System.out.println(map.toString());
}

6.toMap(keyMapper, valueMapper, mergeFunction, mapSupplier)
@Test
public void toLinkedHashMapTest() {
//将学生学号和班级放入自定义的LinkedHashMap
LinkedHashMap<Long, String> map = students.stream().collect(Collectors.toMap(
student -> student.getId(),
student -> student.getGrade(),
(oldValue, newValue) -> newValue,
LinkedHashMap::new)
);
System.out.println(map.toString());
}

7.joining(delimiter, prefix, suffix)
@Test
public void joiningWithPrefixAndSuffixTest() {
//将学生姓名用逗号连接成一个字符串,并在字符串前加上^^^,在字符串后加上$$$
String names = students.stream().map(Student::getName).collect(Collectors.joining(",","^^^","$$$"));
System.out.println(names);
//结果：^^^a,b,c,d,e,f,g,h$$$
}

8.mapping( mapper, downstream)
@Test
public void mappingTest() {
//将学生映射成学生名字,并收集到list中
List<String> names = students.stream().collect(Collectors.mapping(Student::getName, Collectors.toList()));
System.out.println(names.toString());
}

9.collectingAndThen(downstream, finisher)
@Test
public void collectingAndThenTest() {
//先将学生年级收集到set中，再计算set的大小
Integer count = students.stream().map(Student::getGrade).collect(Collectors.collectingAndThen(Collectors.toSet(), grade -> grade.size()));
System.out.println(count);
}

10.counting()
@Test
public void countingTest() {
//计算学生的数量
Long count = students.stream().collect(Collectors.counting());
System.out.println(count);
}

11.maxBy(comparator)
@Test
public void maxByTest() {
//获取语文成绩最高分
Optional<Double> max = students.stream().map(Student::getChineseScore).collect(Collectors.maxBy(Double::compare));
System.out.println(max.get());
}

12.reducing(identity,mapper, op)
@Test
public void reducingTest() {
//获取所有学生语文成绩总分
Optional<Double> sum1 = students.stream().map(Student::getChineseScore).collect(Collectors.reducing(Double::sum));
Double sum2 = students.stream().map(Student::getChineseScore).collect(Collectors.reducing(0d, Double::sum));
Double sum3 = students.stream().collect(Collectors.reducing(0d, Student::getChineseScore, Double::sum));
System.out.println(sum1.get());

13.partitioningBy(predicate, downstream)
@Test
public void partitioningByTest() {
//按照年级分组后,再根据学生总成绩是否大于300分组
Map<String, Map<Boolean, List<Student>>> map = students.stream().collect(
//map<String,map> -- String对应年级 grade
Collectors.groupingBy(Student::getGrade,
//map<boolean,list<>>
Collectors.partitioningBy(
//list
student -> student.getChineseScore() + student.getEnglishScore() + student.getMathScore() > 300
)
)
);
map.forEach((grade, map1) -> map1.forEach((b, list) ->
list.stream().forEach(student -> System.out.println("grade: " + grade + " 是否大于300分: " + b + " id: " + student.getId())))
);
}

结果：
grade: 高三是否大于300分: true id: 3
grade: 高三是否大于300分: true id: 6
grade: 高二是否大于300分: false id: 2
grade: 高二是否大于300分: true id: 5
grade: 高二是否大于300分: true id: 8

----
计数： count
平均值： averagingInt、 averagingLong、 averagingDouble
最值： maxBy、 minBy
求和： summingInt、 summingLong、 summingDouble
统计以上所有： summarizingInt、 summarizingLong、 summarizingDouble
/**
* 统计员工人数、平均工资、工资总额、最高工资
*/
private static void test01(){
//统计员工人数
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("统计员工人数:"+count);
System.out.println("求平均工资:"+average);
System.out.println("求最高工资:"+max);
System.out.println("求工资之和:"+sum);
System.out.println("一次性统计所有信息:"+collect);
}

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原文链接：https://blog.csdn.net/weixin_49856866/article/details/129671816