发布于2021-06-12 13:55 阅读(676) 评论(0) 点赞(16) 收藏(3)
Stream的三个操作步骤
- 创建Stream
- 中间操作
- 终止操作(终端操作)
创建stream的四种方式
stream()
方法或parallelStream()
List<String> list = new ArrayList<>();
Stream<String> stream1 = list.stream();
Stream<String> stream2 = list.parallelStream();
Employee[] employees = new Employee[10];
Stream<Employee> stream2 = Arrays.stream(employees);
Stream<String> stream3 = Stream.of("aa","bb","cc","dd");
// 4.1迭代 : 传一个起始值和一个一元运算
Stream<Integer> stream4 = Stream.iterate(0, (x) -> x + 2);
/// 中间操作 终止操作
stream4.limit(10).forEach(System.out::println);
// 4.2生成(无限生成随机数)
Stream.generate(()->Math.random()).forEach(System.out::println);
中间操作:不会执行任何操作,终止操作:一次性执行全部内容,即“惰性求值”
方法 | 描述 |
---|---|
filter | 接收Lambda,从流中排除某些元素 |
limit | 截断流,使其元素不超过给定数量 |
skip(n) | 跳过元素,返回一个扔掉了前n个元素的流,若流中元素不足n个,则返回一个空流,与limit(n)互补 |
distinct | 筛选,通过流所生成元素的hashCode() 和 equals() 去除重复元素 |
例子:
@Data
@NoArgsConstructor
@AllArgsConstructor
@EqualsAndHashCode()
public class Employee {
private int id;
private String name;
private int age;
private double salary;
private Status status;
public enum Status {
BUSY,FREE,VOCATION;
}
public Employee(int id, String name, int age, double salary) {
this.id = id;
this.name = name;
this.age = age;
this.salary = salary;
}
}
List<Employee> employees = Arrays.asList(
new Employee(1, "张三", 18, 1111.11),
new Employee(2, "李四", 49, 2222.22),
new Employee(3, "赵六", 57, 3333.33),
new Employee(4, "田七", 35, 4444.44),
new Employee(4, "田七", 35, 4444.44)
);
/**
* 中间操作:不会执行任何操作,终止操作:一次性执行全部内容,即“惰性求值”
* 1.筛选与切片:filter
*/
@Test
public void test1() {
// 内部迭代:迭代操作由Stream API完成
employees.stream()
.filter(e -> e.getAge() > 35)
.forEach(System.out::println);
// 外部迭代
Iterator<Employee> it = employees.iterator();
while (it.hasNext()) {
System.out.println(it.next());
}
}
package cn.luis.stream.intermediate;
import cn.luis.stream.Employee;
import org.junit.jupiter.api.Test;
import java.util.Arrays;
import java.util.Iterator;
import java.util.List;
public class LimitTest {
List<Employee> employees = Arrays.asList(
new Employee(1, "张三", 18, 1111.11),
new Employee(3, "赵六", 57, 3333.33),
new Employee(4, "田七", 35, 4444.44),
new Employee(2, "李四", 49, 2222.22),
new Employee(5, "田七", 35, 4444.44)
);
/**
* 中间操作:不会执行任何操作,终止操作:一次性执行全部内容,即“惰性求值”
* 2.筛选与切片:limit
*/
@Test
public void test2() {
// limit;短路,找到两个符合的就终止了
employees.stream()
.filter(e -> {
//System.out.println("不符合条件的或者直接抛弃了!" + e);
return e.getAge() > 20;
})
.limit(2)
.forEach(System.out::println);
}
}
package cn.luis.stream.intermediate.shanxuanqiepian;
import cn.luis.stream.common.Employee;
import org.junit.jupiter.api.Test;
import java.util.Arrays;
import java.util.List;
public class SkipTest {
List<Employee> employees = Arrays.asList(
new Employee(1, "张三", 18, 1111.11),
new Employee(2, "李四", 49, 2222.22),
new Employee(3, "赵六", 57, 3333.33),
new Employee(4, "田七", 35, 4444.44),
new Employee(5, "田七", 35, 4444.44)
);
/**
* 中间操作:不会执行任何操作,终止操作:一次性执行全部内容,即“惰性求值”
* 1.筛选与切片:skip
*/
@Test
public void test3() {
// limit;跳过前两个
employees.stream()
.filter(e -> e.getAge() > 18)
.skip(2)
.forEach(System.out::println);
}
}
package cn.luis.stream.intermediate.shanxuanqiepian;
import cn.luis.stream.common.Employee;
import org.junit.jupiter.api.Test;
import java.util.Arrays;
import java.util.List;
public class DistinctTest {
List<Employee> employees = Arrays.asList(
new Employee(1, "张三", 18, 1111.11),
new Employee(2, "李四", 49, 2222.22),
new Employee(3, "赵六", 57, 3333.33),
new Employee(4, "田七", 35, 4444.44),
new Employee(5, "田七", 35, 4444.44)
);
/**
* 筛选与切片:distinct : 筛选,通过流所生成元素的hashCode() 和 equals() 去除重复元素
*/
@Test
public void test4() {
// distinct;去重 【employees要重写hashcode和equals】
employees.stream()
.filter(e -> {
return e.getAge() > 25;
})
.distinct()
.forEach(System.out::println);
}
}
map里传入Function函数型接口,传入一个参数返回一个值
方法 | 描述 |
---|---|
map | 接收lambda,将元素转换成其他形式或提取信息,接收一个函数作为参数,该函数会被应用到每个元素上,并将其映射成一个新的元素。 |
flatMap | 接收一个函数作为参数,将该流中的每一个值都换成另一个流,然后把所有流连成一个流 |
例子:
package cn.luis.stream.intermediate.yingshe;
import org.junit.jupiter.api.Test;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.stream.Stream;
public class MapTest {
List<String> list = Arrays.asList("aaa", "bbb", "ccc", "ddd");
/**
* map
*/
@Test
public void test1() {
list.stream()
.map(s -> s.toUpperCase())
.forEach(System.out::println);
System.out.println("--------------------------");
// 这种套娃式可以用flatMap替代 (见test2)
Stream<Stream<Character>> stream = list.stream().map(MapTest::filterCharacter);
stream.forEach(sm -> {
sm.forEach(System.out::println);
});
}
/**
* flatMap: 扁平化map
*/
@Test
public void test2() {
// 扁平化map:原来把流放入map流,现在是直接将流中的元素放入flatmap流中
// 把{a,a,a},{b,b,b} ... 转换成了 {a,a,a,b,b,b,c,c,c}
Stream<Character> characterStream = list.stream()
.flatMap(MapTest::filterCharacter);
characterStream.forEach(System.out::println);
}
/**
* 将字符串拆分
* @param str
* @return
*/
public static Stream<Character> filterCharacter(String str) {
List<Character> list = new ArrayList<>();
for (Character ch : str.toCharArray()) {
list.add(ch);
}
return list.stream();
}
}
方法 | 描述 |
---|---|
sorted() | 自然排序(Comparable) |
sorted(Comparator com) | 定制排序(Comparator) |
例子:
package cn.luis.stream.intermediate.sort;
import cn.luis.stream.common.Employee;
import org.junit.jupiter.api.Test;
import java.util.Arrays;
import java.util.List;
import java.util.stream.Stream;
public class SortedTest {
List<Employee> employees = Arrays.asList(
new Employee(1, "张三", 18, 1111.11),
new Employee(2, "李四", 49, 2222.22),
new Employee(3, "赵六", 57, 3333.33),
new Employee(4, "田七", 35, 4444.44),
new Employee(5, "田七", 35, 4444.44)
);
/**
* 3. 排序
* sorted() -- 自然排序(Comparable)
* sorted(Comparator) -- 定制排序(Comparator)
*/
@Test
public void test1() {
// 自然排序ba
Stream<Employee> sorted = employees.stream().sorted();
// 按年龄排序,年龄相同按名字排序
employees.stream()
.sorted((e1, e2) -> {
if (e1.getAge() == e2.getAge()) {
return e1.getName().compareTo(e2.getName());
} else {
Integer x = e1.getAge();
return x.compareTo(e2.getAge());
}
}).forEach(System.out::println);
}
}
方法 | 描述 |
---|---|
allMatch | 检查是否匹配所有元素 |
anyMatch | 检查是否至少匹配一个元素 |
noneMatch | 检查是否没有匹配所有元素 |
findFirst | 返回第一个元素 |
findAny | 返回当前流中的任意元素 |
count | 返回流中元素的总个数 |
max | 返回流中的最大值 |
min | 返回流中的最小值 |
例子:
List<Employee> employees = Arrays.asList(
new Employee(1, "张三", 18, 1111.11, Status.BUSY),
new Employee(2, "李四", 49, 2222.22, Status.FREE),
new Employee(3, "赵六", 57, 3333.33, Status.BUSY),
new Employee(4, "田七", 35, 4444.44, Status.VOCATION),
new Employee(2, "李十四", 49, 2222.22, Status.FREE),
new Employee(2, "李十四", 49, 2222.22, Status.FREE),
new Employee(2, "李十四", 49, 2222.22, Status.FREE)
);
@Test
public void matchTest() {
// 检查是否匹配所有元素
boolean b = employees.stream()
.allMatch(e -> Employee.Status.BUSY.equals(e.getStatus()));
System.out.println(b);
// 检查是否至少匹配一个元素
boolean b2 = employees.stream()
.anyMatch(e -> Employee.Status.BUSY.equals(e.getStatus()));
System.out.println(b2);
// 检查是否没有匹配所有元素
boolean b3 = employees.stream()
.noneMatch(e -> Employee.Status.BUSY.equals(e.getStatus()));
System.out.println(b3);
}
@Test
public void findTest() {
// 返回第一个元素
Optional<Employee> first = employees.stream()
.sorted(Comparator.comparingDouble(Employee::getSalary))
.findFirst();
System.out.println(first.get());
// 返回当前流中的任意元素
Optional<Employee> any = employees.stream()
.filter(e -> Employee.Status.FREE.equals(e.getStatus()))
.findAny();
System.out.println(any.get());
// 【并行】 返回当前流中的任意元素
Optional<Employee> any2 = employees.parallelStream()
.filter(e -> Employee.Status.FREE.equals(e.getStatus()))
.findAny();
System.out.println(any2.get());
}
@Test
public void numTest() {
// 返回流中元素的总个数
long count = employees.stream()
.count();
System.out.println(count);
// 返回流中的最大值
Optional<Employee> max = employees.stream()
.max(Comparator.comparingDouble(Employee::getAge));
System.out.println(max.get());
// 返回流中的最小值
Optional<Double> min = employees.stream()
.map(Employee::getSalary)
.min(Double::compare);
System.out.println(min.get());
}
方法 | 描述 |
---|---|
reduce | 可以将流中的元素反复结合起来,得到一个值 |
public class EmpData {
public static List<Employee> findAllEmployee() {
return Arrays.asList(
new Employee(1, "张三", 18, 1111.11, Employee.Status.BUSY),
new Employee(2, "李四", 49, 2222.22, Employee.Status.FREE),
new Employee(3, "赵六", 57, 3333.33, Employee.Status.BUSY),
new Employee(4, "田七", 35, 4444.44, Employee.Status.VOCATION),
new Employee(2, "李十四", 49, 2222.22, Employee.Status.FREE),
new Employee(2, "李十四", 49, 2222.22, Employee.Status.FREE),
new Employee(2, "李十四", 49, 2222.22, Employee.Status.FREE)
);
}
}
/**
* 规约
*/
public class ReduceTest {
List<Employee> employees = EmpData.findAllEmployee();
/**
* reduce(起始值,二元运算): 规约
*/
@Test
public void test3() {
List<Integer> list = Arrays.asList(1, 2, 3, 4, 5);
Integer a = list.stream()
.reduce(0, (x, y) -> x + y);
System.out.println(a);
Integer b = list.stream()
.reduce(0, Integer::sum);
System.out.println(b);
// 优化写法(map-reduce模式)
Optional<Integer> c = list.stream()
.reduce(Integer::sum);
System.out.println(c.get());
// 优化写法(map-reduce模式) + orElse
Integer d = list.stream()
.reduce(Integer::sum).orElse(0);
System.out.println(d);
}
}
包括集合、计算、分组、分区
方法 | 描述 |
---|---|
collect | 将流转换为其他形式,接收一个Collectot接口的实现,用于给Stream中的元素汇总的方法 |
方法 | 描述 |
---|---|
Collectors.toList() | 转成 List |
Collectors.toSet() | 转成 Set |
Collectors.toCollection(HashSet::new) | 放到其他类型集合 |
@Test
public void test4() {
List<String> nameList = employees.stream()
.map(Employee::getName)
.collect(Collectors.toList());
nameList.forEach(System.out::println);
System.out.println("-----------过滤重复数据--------------");
Set<String> nameSet = employees.stream()
.map(Employee::getName)
.collect(Collectors.toSet());
nameSet.forEach(System.out::println);
System.out.println("-----------放到其他类型集合--------------");
HashSet<String> nameHashSet = employees.stream()
.map(Employee::getName)
.collect(Collectors.toCollection(HashSet::new));
nameHashSet.forEach(System.out::println);
}
方法 | 描述 |
---|---|
Collectors.counting() | 总数 |
Collectors.averagingDouble() | 平均值 |
Collectors.maxBy() | 最大值 |
Collectors.minBy() | 最小值 |
Collectors.summingDouble() | 总和 |
Collectors.summarizingDouble() | 得到的对象可以用来继续计算(getAverage(),getMax(),getCount()) |
@Test
public void test5() {
// 总数
Long collect = employees.stream()
.collect(Collectors.counting());
System.out.println(collect);
// 平均值
Double avg = employees.stream()
.collect(Collectors.averagingDouble(Employee::getSalary));
System.out.println(avg);
// 最大值
Optional<Double> max = employees.stream()
.map(Employee::getSalary)
.collect(Collectors.maxBy(Double::compare));
System.out.println(max.get());
// 最小值
Optional<Double> min = employees.stream()
.map(Employee::getSalary)
.collect(Collectors.minBy(Double::compare));
System.out.println(min.get());
// 总和
Double sum = employees.stream()
.collect(Collectors.summingDouble(Employee::getSalary));
System.out.println(sum);
// Double:强大计算
DoubleSummaryStatistics salary = employees.stream()
.collect(Collectors.summarizingDouble(Employee::getSalary));
System.out.println(salary.getAverage());
System.out.println(salary.getMax());
System.out.println(salary.getCount());
}
方法 | 描述 |
---|---|
Collectors.groupingBy() | 分组 |
Collectors.partitioningBy() | 分区 |
List<Employee> employees = EmpData.findAllEmployee();
/**
* collect 之 分组
*/
@Test
public void groupTest1() {
// 分组
Map<Employee.Status, List<Employee>> statusListMap = employees.stream()
.collect(Collectors.groupingBy(Employee::getStatus));
statusListMap.keySet().forEach(System.out::println);
statusListMap.entrySet().forEach(System.out::println);
System.out.println(statusListMap);
}
VOCATION
BUSY
FREE
VOCATION=[Employee(id=4, name=田七, age=35, salary=4444.44, status=VOCATION)]
BUSY=[Employee(id=1, name=张三, age=18, salary=1111.11, status=BUSY), Employee(id=3, name=赵六, age=57, salary=3333.33, status=BUSY)]
FREE=[Employee(id=2, name=李四, age=49, salary=2222.22, status=FREE), Employee(id=2, name=李十四, age=49, salary=2222.22, status=FREE), Employee(id=2, name=李十四, age=49, salary=2222.22, status=FREE), Employee(id=2, name=李十四, age=49, salary=2222.22, status=FREE)]
{VOCATION=[Employee(id=4, name=田七, age=35, salary=4444.44, status=VOCATION)], BUSY=[Employee(id=1, name=张三, age=18, salary=1111.11, status=BUSY), Employee(id=3, name=赵六, age=57, salary=3333.33, status=BUSY)], FREE=[Employee(id=2, name=李四, age=49, salary=2222.22, status=FREE), Employee(id=2, name=李十四, age=49, salary=2222.22, status=FREE), Employee(id=2, name=李十四, age=49, salary=2222.22, status=FREE), Employee(id=2, name=李十四, age=49, salary=2222.22, status=FREE)]}
List<Employee> employees = EmpData.findAllEmployee();
@Test
public void groupTest2() {
// 多级分组
Map<String, List<Employee>> emMap = employees.stream()
.collect(Collectors.groupingBy((employee) -> {
if (employee.getAge() <= 35) {
return "青年";
} else if (employee.getAge() > 20) {
return "老年";
} else {
return "少年";
}
}));
// 查看分组(第一种方式)
emMap.keySet().forEach(key -> {
System.out.println("======" + key + "======");
emMap.get(key).forEach(System.out::println);
});
// 查看分组(第二种方式)
emMap.forEach((k, v) -> {
System.out.println("======" + k + "======");
v.forEach(map -> {
System.out.println(map);
});
});
}
======青年======
Employee(id=1, name=张三, age=18, salary=1111.11, status=BUSY)
Employee(id=4, name=田七, age=35, salary=4444.44, status=VOCATION)
======老年======
Employee(id=2, name=李四, age=49, salary=2222.22, status=FREE)
Employee(id=3, name=赵六, age=57, salary=3333.33, status=BUSY)
Employee(id=2, name=李十四, age=49, salary=2222.22, status=FREE)
Employee(id=2, name=李十四, age=49, salary=2222.22, status=FREE)
Employee(id=2, name=李十四, age=49, salary=2222.22, status=FREE)
/**
* collect 之 分区
*/
@Test
public void area1() {
// 分区: 满足条件的分一个区,不满足的分一个区
Map<Boolean, List<Employee>> emMap = employees.stream()
.collect(Collectors.partitioningBy(e -> e.getSalary() > 2000.0));
// 查看分组(第二种方式)
emMap.forEach((k, v) -> {
System.out.println("======" + k + "======");
v.forEach(map -> {
System.out.println(map);
});
});
}
======false======
Employee(id=1, name=张三, age=18, salary=1111.11, status=BUSY)
======true======
Employee(id=2, name=李四, age=49, salary=2222.22, status=FREE)
Employee(id=3, name=赵六, age=57, salary=3333.33, status=BUSY)
Employee(id=4, name=田七, age=35, salary=4444.44, status=VOCATION)
Employee(id=2, name=李十四, age=49, salary=2222.22, status=FREE)
Employee(id=2, name=李十四, age=49, salary=2222.22, status=FREE)
Employee(id=2, name=李十四, age=49, salary=2222.22, status=FREE)
方法 | 描述 |
---|---|
Collectors.joining(",") | 字符串拼接 |
@Test
public void str() {
// 字符串拼接
String str = employees.stream()
.map(Employee::getName)
.collect(Collectors.joining(","));
System.out.println(str);
}
张三,李四,赵六,田七,李十四,李十四,李十四
原文链接:https://blog.csdn.net/qq_39720594/article/details/117747963
作者:狗蛋来了
链接:http://www.javaheidong.com/blog/article/222197/8b009a7c970cd6585b06/
来源:java黑洞网
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