Java8中引入了一个新的操作符 “->” 该操作符称为箭头操作符或 Lambda 操作符
箭头操作符将 Lambda 表达式拆分成两部分:
左侧:Lambda 表达式的参数列表
右侧:Lambda 表达式中所需执行的功能, 即 Lambda 体
顺口溜
上联:左右遇一括号省
下联:左侧推断类型省
横批:能省则省
实现类
package com.atguigu.java8;
import java.util.ArrayList;
import java.util.Comparator;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.function.Consumer;
import org.junit.Test;
public class TestLambda2 {
@Test
public void test1(){
int num = 0;//jdk 1.7 前,必须是 final
Runnable r = new Runnable() {
@Override
public void run() {
System.out.println("Hello World!" + num);
}
};
r.run();
System.out.println("-------------------------------");
Runnable r1 = () -> System.out.println("Hello Lambda!");
r1.run();
}
@Test
public void test2(){
Consumer<String> con = x -> System.out.println(x);
con.accept("我大尚硅谷威武!");
}
@Test
public void test3(){
Comparator<Integer> com = (x, y) -> {
System.out.println("函数式接口");
return Integer.compare(x, y);
};
}
@Test
public void test4(){
Comparator<Integer> com = (x, y) -> Integer.compare(x, y);
}
@Test
public void test5(){
// String[] strs;
// strs = {"aaa", "bbb", "ccc"};
List<String> list = new ArrayList<>();
show(new HashMap<>());
}
public void show(Map<String, Integer> map){
}
//需求:对一个数进行运算
@Test
public void test6(){
Integer num = operation(100, (x) -> x * x);
System.out.println(num);
System.out.println(operation(200, (y) -> y + 200));
}
public Integer operation(Integer num, MyFun mf){
return mf.getValue(num);
}
}
接口类
package com.atguigu.java8;
@FunctionalInterface
public interface MyPredicate<T> {
public boolean test(T t);
}
①方法引用所引用的方法的参数列表与返回值类型,需要与函数式接口中抽象方法的参数列表和返回值类型保持一致!
②若Lambda 的参数列表的第一个参数,是实例方法的调用者,第二个参数(或无参)是实例方法的参数时,格式: ClassName::MethodName
package com.atguigu.java8;
import java.io.PrintStream;
import java.util.Comparator;
import java.util.function.BiFunction;
import java.util.function.BiPredicate;
import java.util.function.Consumer;
import java.util.function.Function;
import java.util.function.Supplier;
import org.junit.Test;
public class TestMethodRef {
//数组引用
@Test
public void test8(){
Function<Integer, String[]> fun = (args) -> new String[args];
String[] strs = fun.apply(10);
System.out.println(strs.length);
System.out.println("--------------------------");
Function<Integer, Employee[]> fun2 = Employee[] :: new;
Employee[] emps = fun2.apply(20);
System.out.println(emps.length);
}
//构造器引用
@Test
public void test7(){
Function<String, Employee> fun = Employee::new;
BiFunction<String, Integer, Employee> fun2 = Employee::new;
}
@Test
public void test6(){
Supplier<Employee> sup = () -> new Employee();
System.out.println(sup.get());
System.out.println("------------------------------------");
Supplier<Employee> sup2 = Employee::new;
System.out.println(sup2.get());
}
//类名 :: 实例方法名
@Test
public void test5(){
BiPredicate<String, String> bp = (x, y) -> x.equals(y);
System.out.println(bp.test("abcde", "abcde"));
System.out.println("-----------------------------------------");
BiPredicate<String, String> bp2 = String::equals;
System.out.println(bp2.test("abc", "abc"));
System.out.println("-----------------------------------------");
Function<Employee, String> fun = (e) -> e.show();
System.out.println(fun.apply(new Employee()));
System.out.println("-----------------------------------------");
Function<Employee, String> fun2 = Employee::show;
System.out.println(fun2.apply(new Employee()));
}
//类名 :: 静态方法名
@Test
public void test4(){
Comparator<Integer> com = (x, y) -> Integer.compare(x, y);
System.out.println("-------------------------------------");
Comparator<Integer> com2 = Integer::compare;
}
@Test
public void test3(){
BiFunction<Double, Double, Double> fun = (x, y) -> Math.max(x, y);
System.out.println(fun.apply(1.5, 22.2));
System.out.println("--------------------------------------------------");
BiFunction<Double, Double, Double> fun2 = Math::max;
System.out.println(fun2.apply(1.2, 1.5));
}
//对象的引用 :: 实例方法名
@Test
public void test2(){
Employee emp = new Employee(101, "张三", 18, 9999.99);
Supplier<String> sup = () -> emp.getName();
System.out.println(sup.get());
System.out.println("----------------------------------");
Supplier<String> sup2 = emp::getName;
System.out.println(sup2.get());
}
@Test
public void test1(){
PrintStream ps = System.out;
Consumer<String> con = (str) -> ps.println(str);
con.accept("Hello World!");
System.out.println("--------------------------------");
Consumer<String> con2 = ps::println;
con2.accept("Hello Java8!");
Consumer<String> con3 = System.out::println;
}
}
函数式接口:接口中只有一个抽象方法的接口,称为函数式接口
。 可以使用注解 @FunctionalInterface 修饰
可以检查是否是函数式接口
示例代码
public class TestLambda3 {
//Predicate 断言型接口:
@Test
public void test4(){
List<String> list = Arrays.asList("Hello", "atguigu", "Lambda", "www", "ok");
List<String> strList = filterStr(list, (s) -> s.length() > 3);
for (String str : strList) {
System.out.println(str);
}
}
//需求:将满足条件的字符串,放入集合中
public List<String> filterStr(List<String> list, Predicate<String> pre){
List<String> strList = new ArrayList<>();
for (String str : list) {
if(pre.test(str)){
strList.add(str);
}
}
return strList;
}
//Function 函数型接口:
@Test
public void test3(){
String newStr = strHandler("\t\t\t 我大尚硅谷威武 ", (str) -> str.trim());
System.out.println(newStr);
String subStr = strHandler("我大尚硅谷威武", (str) -> str.substring(2, 5));
System.out.println(subStr);
}
//需求:用于处理字符串
public String strHandler(String str, Function<String, String> fun){
return fun.apply(str);
}
//Supplier 供给型接口 :
@Test
public void test2(){
List<Integer> numList = getNumList(10, () -> (int)(Math.random() * 100));
for (Integer num : numList) {
System.out.println(num);
}
}
//需求:产生指定个数的整数,并放入集合中
public List<Integer> getNumList(int num, Supplier<Integer> sup){
List<Integer> list = new ArrayList<>();
for (int i = 0; i < num; i++) {
Integer n = sup.get();
list.add(n);
}
return list;
}
//Consumer 消费型接口 :
@Test
public void test1(){
happy(10000, (m) -> System.out.println("你们刚哥喜欢大宝剑,每次消费:" + m + "元"));
}
public void happy(double money, Consumer<Double> con){
con.accept(money);
}
}
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
package com.atguigu.java8;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Iterator;
import java.util.List;
import java.util.stream.Stream;
import org.junit.Test;
/*
* 一、Stream API 的操作步骤:
*
* 1. 创建 Stream
*
* 2. 中间操作
*
* 3. 终止操作(终端操作)
*/
public class TestStreamaAPI {
//1. 创建 Stream
@Test
public void test1(){
//1. Collection 提供了两个方法 stream() 与 parallelStream()
List<String> list = new ArrayList<>();
Stream<String> stream = list.stream(); //获取一个顺序流
Stream<String> parallelStream = list.parallelStream(); //获取一个并行流
//2. 通过 Arrays 中的 stream() 获取一个数组流
Integer[] nums = new Integer[10];
Stream<Integer> stream1 = Arrays.stream(nums);
//3. 通过 Stream 类中静态方法 of()
Stream<Integer> stream2 = Stream.of(1,2,3,4,5,6);
//4. 创建无限流
//迭代
Stream<Integer> stream3 = Stream.iterate(0, (x) -> x + 2).limit(10);
stream3.forEach(System.out::println);
//生成
Stream<Double> stream4 = Stream.generate(Math::random).limit(2);
stream4.forEach(System.out::println);
}
//2. 中间操作
List<Employee> emps = Arrays.asList(
new Employee(102, "李四", 59, 6666.66),
new Employee(101, "张三", 18, 9999.99),
new Employee(103, "王五", 28, 3333.33),
new Employee(104, "赵六", 8, 7777.77),
new Employee(104, "赵六", 8, 7777.77),
new Employee(104, "赵六", 8, 7777.77),
new Employee(105, "田七", 38, 5555.55)
);
/*
筛选与切片
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
*/
//内部迭代:迭代操作 Stream API 内部完成
@Test
public void test2(){
//所有的中间操作不会做任何的处理
Stream<Employee> stream = emps.stream()
.filter((e) -> {
System.out.println("测试中间操作");
return e.getAge() <= 35;
});
//只有当做终止操作时,所有的中间操作会一次性的全部执行,称为“惰性求值”
stream.forEach(System.out::println);
}
//外部迭代
@Test
public void test3(){
Iterator<Employee> it = emps.iterator();
while(it.hasNext()){
System.out.println(it.next());
}
}
@Test
public void test4(){
emps.stream()
.filter((e) -> {
System.out.println("短路!"); // && ||
return e.getSalary() >= 5000;
}).limit(3)
.forEach(System.out::println);
}
@Test
public void test5(){
emps.parallelStream()
.filter((e) -> e.getSalary() >= 5000)
.skip(2)
.forEach(System.out::println);
}
@Test
public void test6(){
emps.stream()
.distinct()
.forEach(System.out::println);
}
}
package com.atguigu.java8;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.stream.Stream;
import org.junit.Test;
//1. 创建 Stream
public class TestStreamAPI1 {
List<Employee> emps = Arrays.asList(
new Employee(102, "李四", 59, 6666.66),
new Employee(101, "张三", 18, 9999.99),
new Employee(103, "王五", 28, 3333.33),
new Employee(104, "赵六", 8, 7777.77),
new Employee(104, "赵六", 8, 7777.77),
new Employee(104, "赵六", 8, 7777.77),
new Employee(105, "田七", 38, 5555.55)
);
//2. 中间操作
/*
映射
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。【Stream> stream2】
flatMap——接收一个函数作为参数,将流中的每个值都换成另一个流,然后把所有流连接成一个流【Stream stream3】
*/
@Test
public void test1(){
Stream<String> str = emps.stream()
.map((e) -> e.getName());
System.out.println("-------------------------------------------");
List<String> strList = Arrays.asList("aaa", "bbb", "ccc", "ddd", "eee");
Stream<String> stream = strList.stream()
.map(String::toUpperCase);
stream.forEach(System.out::println);
Stream<Stream<Character>> stream2 = strList.stream()
.map(TestStreamAPI1::filterCharacter);
stream2.forEach((sm) -> {
sm.forEach(System.out::println);
});
System.out.println("---------------------------------------------");
Stream<Character> stream3 = strList.stream()
.flatMap(TestStreamAPI1::filterCharacter);
stream3.forEach(System.out::println);
}
public static Stream<Character> filterCharacter(String str){
List<Character> list = new ArrayList<>();
for (Character ch : str.toCharArray()) {
list.add(ch);
}
return list.stream();
}
/*
sorted()——自然排序
sorted(Comparator com)——定制排序
*/
@Test
public void test2(){
emps.stream()
.map(Employee::getName)
.sorted()
.forEach(System.out::println);
System.out.println("------------------------------------");
emps.stream()
.sorted((x, y) -> {
if(x.getAge() == y.getAge()){
return x.getName().compareTo(y.getName());
}else{
return Integer.compare(x.getAge(), y.getAge());
}
}).forEach(System.out::println);
}
}
package com.atguigu.java8;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.stream.Stream;
import org.junit.Test;
//1. 创建 Stream
public class TestStreamAPI1 {
List<Employee> emps = Arrays.asList(
new Employee(102, "李四", 59, 6666.66),
new Employee(101, "张三", 18, 9999.99),
new Employee(103, "王五", 28, 3333.33),
new Employee(104, "赵六", 8, 7777.77),
new Employee(104, "赵六", 8, 7777.77),
new Employee(104, "赵六", 8, 7777.77),
new Employee(105, "田七", 38, 5555.55)
);
/*
sorted()——自然排序
sorted(Comparator com)——定制排序
*/
@Test
public void test2(){
emps.stream()
.map(Employee::getName)
.sorted()
.forEach(System.out::println);
System.out.println("------------------------------------");
emps.stream()
.sorted((x, y) -> {
if(x.getAge() == y.getAge()){
return x.getName().compareTo(y.getName());
}else{
return Integer.compare(x.getAge(), y.getAge());
}
}).forEach(System.out::println);
}
}
package com.atguigu.java8;
import java.util.Arrays;
import java.util.List;
import java.util.Optional;
import java.util.stream.Stream;
import org.junit.Test;
import com.atguigu.java8.Employee.Status;
public class TestStreamAPI2 {
List<Employee> emps = Arrays.asList(
new Employee(102, "李四", 59, 6666.66, Status.BUSY),
new Employee(101, "张三", 18, 9999.99, Status.FREE),
new Employee(103, "王五", 28, 3333.33, Status.VOCATION),
new Employee(104, "赵六", 8, 7777.77, Status.BUSY),
new Employee(104, "赵六", 8, 7777.77, Status.FREE),
new Employee(104, "赵六", 8, 7777.77, Status.FREE),
new Employee(105, "田七", 38, 5555.55, Status.BUSY)
);
// 终止操作
@Test
public void test1(){
// allMatch——检查是否匹配所有元素
boolean bl = emps.stream()
.allMatch((e) -> e.getStatus().equals(Status.BUSY));
System.out.println(bl);
// anyMatch——检查是否至少匹配一个元素
boolean bl1 = emps.stream()
.anyMatch((e) -> e.getStatus().equals(Status.BUSY));
System.out.println(bl1);
// 检查是否没有匹配的元素
boolean bl2 = emps.stream()
.noneMatch((e) -> e.getStatus().equals(Status.BUSY));
System.out.println(bl2);
}
@Test
public void test2(){
Optional<Employee> op = emps.stream()
.sorted((e1, e2) -> Double.compare(e1.getSalary(), e2.getSalary()))
.findFirst();
System.out.println(op.get());
System.out.println("--------------------------------");
//parallelStream多个线程并行获取
Optional<Employee> op2 = emps.parallelStream()
.filter((e) -> e.getStatus().equals(Status.FREE))
.findAny();
System.out.println(op2.get());
}
@Test
public void test3(){
long count = emps.stream()
.filter((e) -> e.getStatus().equals(Status.FREE))
.count();
System.out.println(count);
Optional<Double> op = emps.stream()
.map(Employee::getSalary)
.max(Double::compare);
System.out.println(op.get());
Optional<Employee> op2 = emps.stream()
.min((e1, e2) -> Double.compare(e1.getSalary(), e2.getSalary()));
System.out.println(op2.get());
}
//注意:流进行了终止操作后,不能再次使用
@Test
public void test4(){
Stream<Employee> stream = emps.stream()
.filter((e) -> e.getStatus().equals(Status.FREE));
long count = stream.count();
stream.map(Employee::getSalary)
.max(Double::compare);
}
}
map-reduce模式应用广泛
,如Google进行网络搜索的大数据应用分组、多级分组、分区
package com.atguigu.java8;
import java.util.Arrays;
import java.util.DoubleSummaryStatistics;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Optional;
import java.util.Set;
import java.util.stream.Collectors;
import org.junit.Test;
import com.atguigu.java8.Employee.Status;
public class TestStreamAPI3 {
List<Employee> emps = Arrays.asList(
new Employee(102, "李四", 79, 6666.66, Status.BUSY),
new Employee(101, "张三", 18, 9999.99, Status.FREE),
new Employee(103, "王五", 28, 3333.33, Status.VOCATION),
new Employee(104, "赵六", 8, 7777.77, Status.BUSY),
new Employee(104, "赵六", 8, 7777.77, Status.FREE),
new Employee(104, "赵六", 8, 7777.77, Status.FREE),
new Employee(105, "田七", 38, 5555.55, Status.BUSY)
);
//3. 终止操作
/*
归约
reduce(T identity, BinaryOperator) / reduce(BinaryOperator) ——可以将流中元素反复结合起来,得到一个值。
*/
@Test
public void test1(){
List<Integer> list = Arrays.asList(1,2,3,4,5,6,7,8,9,10);
Integer sum = list.stream()
.reduce(0, (x, y) -> x + y);
System.out.println(sum);
System.out.println("----------------------------------------");
Optional<Double> op = emps.stream()
.map(Employee::getSalary)
.reduce(Double::sum);
System.out.println(op.get());
}
//需求:搜索名字中 “六” 出现的次数
@Test
public void test2(){
Optional<Integer> sum = emps.stream()
.map(Employee::getName)
.flatMap(TestStreamAPI1::filterCharacter)
.map((ch) -> {
if(ch.equals('六'))
return 1;
else
return 0;
}).reduce(Integer::sum);
System.out.println(sum.get());
}
//collect——将流转换为其他形式。接收一个 Collector接口的实现,用于给Stream中元素做汇总的方法
@Test
public void test3(){
List<String> list = emps.stream()
.map(Employee::getName)
.collect(Collectors.toList());
list.forEach(System.out::println);
System.out.println("----------------------------------");
Set<String> set = emps.stream()
.map(Employee::getName)
.collect(Collectors.toSet());
set.forEach(System.out::println);
System.out.println("----------------------------------");
HashSet<String> hs = emps.stream()
.map(Employee::getName)
.collect(Collectors.toCollection(HashSet::new));
hs.forEach(System.out::println);
}
@Test
public void test4(){
Optional<Double> max = emps.stream()
.map(Employee::getSalary)
.collect(Collectors.maxBy(Double::compare));
System.out.println(max.get());
Optional<Employee> op = emps.stream()
.collect(Collectors.minBy((e1, e2) -> Double.compare(e1.getSalary(), e2.getSalary())));
System.out.println(op.get());
Double sum = emps.stream()
.collect(Collectors.summingDouble(Employee::getSalary));
System.out.println(sum);
Double avg = emps.stream()
.collect(Collectors.averagingDouble(Employee::getSalary));
System.out.println(avg);
Long count = emps.stream()
.collect(Collectors.counting());
System.out.println(count);
System.out.println("--------------------------------------------");
DoubleSummaryStatistics dss = emps.stream()
.collect(Collectors.summarizingDouble(Employee::getSalary));
System.out.println(dss.getMax());
}
//分组
@Test
public void test5(){
Map<Status, List<Employee>> map = emps.stream()
.collect(Collectors.groupingBy(Employee::getStatus));
System.out.println(map);
}
//多级分组
@Test
public void test6(){
Map<Status, Map<String, List<Employee>>> map = emps.stream()
.collect(Collectors.groupingBy(Employee::getStatus, Collectors.groupingBy((e) -> {
if(e.getAge() >= 60)
return "老年";
else if(e.getAge() >= 35)
return "中年";
else
return "成年";
})));
System.out.println(map);
}
//分区
@Test
public void test7(){
Map<Boolean, List<Employee>> map = emps.stream()
.collect(Collectors.partitioningBy((e) -> e.getSalary() >= 5000));
System.out.println(map);
}
//
@Test
public void test8(){
String str = emps.stream()
.map(Employee::getName)
.collect(Collectors.joining("," , "----", "----"));
System.out.println(str);
}
@Test
public void test9(){
Optional<Double> sum = emps.stream()
.map(Employee::getSalary)
.collect(Collectors.reducing(Double::sum));
System.out.println(sum.get());
}
}
Optional 容器类:用于尽量避免空指针异常
最常用的写法
ofNullable-可以是null,可以不是,所以使用前需要先isPresent()判断一下。 实际上ofNullable()是of(value) 与empty()的结合体
// ofNullable-可以是null,可以不是,所以使用前需要先isPresent()判断一下。 实际上ofNullable()是of(value) 与empty()的结合体
Optional<Employee> op = Optional.ofNullable(new Employee());
if(op.isPresent()){
System.out.println(op.get());
}
示例代码
package com.atguigu.java8;
import java.util.Optional;
import org.junit.Test;
public class TestOptional {
@Test
public void test4(){
Optional<Employee> op = Optional.of(new Employee(101, "张三", 18, 9999.99));
Optional<String> op2 = op.map(Employee::getName);
System.out.println(op2.get());
Optional<String> op3 = op.flatMap((e) -> Optional.of(e.getName()));
System.out.println(op3.get());
}
@Test
public void test3(){
Optional<Employee> op = Optional.ofNullable(new Employee());
if(op.isPresent()){
System.out.println(op.get());
}
Employee emp = op.orElse(new Employee("张三"));
System.out.println(emp);
Employee emp2 = op.orElseGet(() -> new Employee());
System.out.println(emp2);
}
@Test
public void test2(){
/*Optional op = Optional.ofNullable(null);
System.out.println(op.get());*/
// Optional op = Optional.empty();
// System.out.println(op.get());
}
@Test
public void test1(){
Optional<Employee> op = Optional.of(new Employee());
Employee emp = op.get();
System.out.println(emp);
}
@Test
public void test5(){
Man man = new Man();
String name = getGodnessName(man);
System.out.println(name);
}
//需求:获取一个男人心中女神的名字
public String getGodnessName(Man man){
if(man != null){
Godness g = man.getGod();
if(g != null){
return g.getName();
}
}
return "苍老师";
}
//运用 Optional 的实体类
@Test
public void test6(){
Optional<Godness> godness = Optional.ofNullable(new Godness("林志玲"));
Optional<NewMan> op = Optional.ofNullable(new NewMan(godness));
String name = getGodnessName2(op);
System.out.println(name);
}
public String getGodnessName2(Optional<NewMan> man){
return man.orElse(new NewMan())
.getGodness()
.orElse(new Godness("苍老师"))
.getName();
}
}
Godness实体类
package com.atguigu.java8;
public class Godness {
private String name;
public Godness() {
}
public Godness(String name) {
this.name = name;
}
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
@Override
public String toString() {
return "Godness [name=" + name + "]";
}
}
man实体类
package com.atguigu.java8;
public class Man {
private Godness god;
public Man() {
}
public Man(Godness god) {
this.god = god;
}
public Godness getGod() {
return god;
}
public void setGod(Godness god) {
this.god = god;
}
@Override
public String toString() {
return "Man [god=" + god + "]";
}
}
java8 并行流 parallel()底层是Fork/Join 框架,其CPU利用率极高!
Fork/Join 框架:就是在必要的情况下,将一个大任务,进行拆分(fork)成若干个 小任务(拆到不可再拆时),再将一个个的小任务运算的结果进行 join 汇总。
调用类
package com.atguigu.java8;
import java.util.concurrent.ForkJoinPool;
import java.util.concurrent.ForkJoinTask;
import java.util.stream.LongStream;
import org.junit.Test;
public class TestForkJoin {
@Test
public void test1(){
long start = System.currentTimeMillis();
// 线程池调用
ForkJoinPool pool = new ForkJoinPool();
ForkJoinTask<Long> task = new ForkJoinCalculate(0L, 10000000000L);
long sum = pool.invoke(task);
System.out.println(sum);
long end = System.currentTimeMillis();
System.out.println("耗费的时间为: " + (end - start)); //112-1953-1988-2654-2647-20663-113808
}
@Test
public void test2(){
long start = System.currentTimeMillis();
long sum = 0L;
//普通for循环方式对比
for (long i = 0L; i <= 10000000000L; i++) {
sum += i;
}
System.out.println(sum);
long end = System.currentTimeMillis();
System.out.println("耗费的时间为: " + (end - start)); //34-3174-3132-4227-4223-31583
}
@Test
public void test3(){
long start = System.currentTimeMillis();
// java8 并行流 parallel()
Long sum = LongStream.rangeClosed(0L, 10000000000L)
.parallel()
.sum();
System.out.println(sum);
long end = System.currentTimeMillis();
System.out.println("耗费的时间为: " + (end - start)); //2061-2053-2086-18926
}
}
实现类
package com.atguigu.java8;
import java.util.concurrent.RecursiveTask;
public class ForkJoinCalculate extends RecursiveTask<Long>{
private static final long serialVersionUID = 13475679780L;
private long start;
private long end;
private static final long THRESHOLD = 10000L; //临界值
public ForkJoinCalculate(long start, long end) {
this.start = start;
this.end = end;
}
@Override
protected Long compute() {
long length = end - start;
if(length <= THRESHOLD){
long sum = 0;
for (long i = start; i <= end; i++) {
sum += i;
}
return sum;
}else{
long middle = (start + end) / 2;
ForkJoinCalculate left = new ForkJoinCalculate(start, middle);
left.fork(); //拆分,并将该子任务压入线程队列
ForkJoinCalculate right = new ForkJoinCalculate(middle+1, end);
right.fork();
return left.join() + right.join();
}
}
}
注:ISO-8601日历系统是国际标准化组织制定的现代公民的日期和时间的表示法
package com.atguigu.java8;
import java.time.DayOfWeek;
import java.time.Duration;
import java.time.Instant;
import java.time.LocalDate;
import java.time.LocalDateTime;
import java.time.OffsetDateTime;
import java.time.Period;
import java.time.ZoneId;
import java.time.ZoneOffset;
import java.time.ZonedDateTime;
import java.time.format.DateTimeFormatter;
import java.time.temporal.TemporalAdjusters;
import java.util.Set;
import org.junit.Test;
public class TestLocalDateTime {
//6.ZonedDate、ZonedTime、ZonedDateTime : 带时区的时间或日期
@Test
public void test7(){
LocalDateTime ldt = LocalDateTime.now(ZoneId.of("Asia/Shanghai"));
System.out.println(ldt);
ZonedDateTime zdt = ZonedDateTime.now(ZoneId.of("US/Pacific"));
System.out.println(zdt);
}
@Test
public void test6(){
Set<String> set = ZoneId.getAvailableZoneIds();
set.forEach(System.out::println);
}
//5. DateTimeFormatter : 解析和格式化日期或时间
@Test
public void test5(){
// DateTimeFormatter dtf = DateTimeFormatter.ISO_LOCAL_DATE;
DateTimeFormatter dtf = DateTimeFormatter.ofPattern("yyyy年MM月dd日 HH:mm:ss E");
LocalDateTime ldt = LocalDateTime.now();
String strDate = ldt.format(dtf);
System.out.println(strDate);
LocalDateTime newLdt = ldt.parse(strDate, dtf);
System.out.println(newLdt);
}
//4. TemporalAdjuster : 时间校正器
@Test
public void test4(){
LocalDateTime ldt = LocalDateTime.now();
System.out.println(ldt);
LocalDateTime ldt2 = ldt.withDayOfMonth(10);
System.out.println(ldt2);
LocalDateTime ldt3 = ldt.with(TemporalAdjusters.next(DayOfWeek.SUNDAY));
System.out.println(ldt3);
//自定义:下一个工作日
LocalDateTime ldt5 = ldt.with((l) -> {
LocalDateTime ldt4 = (LocalDateTime) l;
DayOfWeek dow = ldt4.getDayOfWeek();
if(dow.equals(DayOfWeek.FRIDAY)){
return ldt4.plusDays(3);
}else if(dow.equals(DayOfWeek.SATURDAY)){
return ldt4.plusDays(2);
}else{
return ldt4.plusDays(1);
}
});
System.out.println(ldt5);
}
//3.
//Duration : 用于计算两个“时间”间隔
//Period : 用于计算两个“日期”间隔
@Test
public void test3(){
Instant ins1 = Instant.now();
System.out.println("--------------------");
try {
Thread.sleep(1000);
} catch (InterruptedException e) {
}
Instant ins2 = Instant.now();
System.out.println("所耗费时间为:" + Duration.between(ins1, ins2));
System.out.println("----------------------------------");
LocalDate ld1 = LocalDate.now();
LocalDate ld2 = LocalDate.of(2011, 1, 1);
Period pe = Period.between(ld2, ld1);
System.out.println(pe.getYears());
System.out.println(pe.getMonths());
System.out.println(pe.getDays());
}
//2. Instant : 时间戳。 (使用 Unix 元年 1970年1月1日 00:00:00 所经历的毫秒值)
@Test
public void test2(){
Instant ins = Instant.now(); //默认使用 UTC 时区
System.out.println(ins);
OffsetDateTime odt = ins.atOffset(ZoneOffset.ofHours(8));
System.out.println(odt);
System.out.println(ins.getNano());
Instant ins2 = Instant.ofEpochSecond(5);
System.out.println(ins2);
}
//1. LocalDate、LocalTime、LocalDateTime
@Test
public void test1(){
LocalDateTime ldt = LocalDateTime.now();
System.out.println(ldt);
LocalDateTime ld2 = LocalDateTime.of(2016, 11, 21, 10, 10, 10);
System.out.println(ld2);
LocalDateTime ldt3 = ld2.plusYears(20);
System.out.println(ldt3);
LocalDateTime ldt4 = ld2.minusMonths(2);
System.out.println(ldt4);
System.out.println(ldt.getYear());
System.out.println(ldt.getMonthValue());
System.out.println(ldt.getDayOfMonth());
System.out.println(ldt.getHour());
System.out.println(ldt.getMinute());
System.out.println(ldt.getSecond());
}
}
TemporalAdjusters
: 该类通过静态方法提供了大量的常 用 TemporalAdjuster 的实现。java.time.format.DateTimeFormatter 类:该类提供了三种 格式化方法:
Java8 中加入了对时区的支持,带时区的时间为分别为:
ZonedDate、ZonedTime、ZonedDateTime
其中每个时区都对应着 ID,地区ID都为 “{区域}/{城市}”的格式 ; 例如 :Asia/Shanghai 等
获取所有时区信息
Set<String> set = ZoneId.getAvailableZoneIds();
set.forEach(System.out::println);
指定一个时区获取时间
LocalDateTime ldt = LocalDateTime.now(ZoneId.of("Asia/Shanghai"));
阿里巴巴2020.04.22发布的 java开发手册泰山版-下载 中对日期也做了特殊要求:详细内容大家可点击上方下载查看手册(五) 日期时间章节,关于闰年闰月部分特殊,我已摘出来如下:
// 获取今年的天数
int daysOfThisYear = LocalDate.now().lengthOfYear(); // 获取指定某年的天数
LocalDate.of(2011, 1, 1).lengthOfYear();
反例: // 第一种情况:在闰年 366 天时,出现数组越界异常
int[] dayArray = new int[365];
// 第二种情况:一年有效期的会员制,今年 1 月 26 日注册,硬编码 365 返回的却是 1 月 25 日
Calendar calendar = Calendar.getInstance(); calendar.set(2020, 1, 26);
calendar.add(Calendar.DATE, 365);
package com.atguigu.java8;
import java.time.DayOfWeek;
import java.time.Duration;
import java.time.Instant;
import java.time.LocalDate;
import java.time.LocalDateTime;
import java.time.OffsetDateTime;
import java.time.Period;
import java.time.ZoneId;
import java.time.ZoneOffset;
import java.time.ZonedDateTime;
import java.time.format.DateTimeFormatter;
import java.time.temporal.TemporalAdjusters;
import java.util.Set;
import org.junit.Test;
public class TestLocalDateTime {
//6.ZonedDate、ZonedTime、ZonedDateTime : 带时区的时间或日期
@Test
public void test7(){
LocalDateTime ldt = LocalDateTime.now(ZoneId.of("Asia/Shanghai"));
System.out.println(ldt);
ZonedDateTime zdt = ZonedDateTime.now(ZoneId.of("US/Pacific"));
System.out.println(zdt);
}
@Test
public void test6(){
Set<String> set = ZoneId.getAvailableZoneIds();
set.forEach(System.out::println);
}
//5. DateTimeFormatter : 解析和格式化日期或时间
@Test
public void test5(){
// DateTimeFormatter dtf = DateTimeFormatter.ISO_LOCAL_DATE;
DateTimeFormatter dtf = DateTimeFormatter.ofPattern("yyyy年MM月dd日 HH:mm:ss E");
LocalDateTime ldt = LocalDateTime.now();
String strDate = ldt.format(dtf);
System.out.println(strDate);
LocalDateTime newLdt = ldt.parse(strDate, dtf);
System.out.println(newLdt);
}
//4. TemporalAdjuster : 时间校正器
@Test
public void test4(){
LocalDateTime ldt = LocalDateTime.now();
System.out.println(ldt);
LocalDateTime ldt2 = ldt.withDayOfMonth(10);
System.out.println(ldt2);
LocalDateTime ldt3 = ldt.with(TemporalAdjusters.next(DayOfWeek.SUNDAY));
System.out.println(ldt3);
//自定义:下一个工作日
LocalDateTime ldt5 = ldt.with((l) -> {
LocalDateTime ldt4 = (LocalDateTime) l;
DayOfWeek dow = ldt4.getDayOfWeek();
if(dow.equals(DayOfWeek.FRIDAY)){
return ldt4.plusDays(3);
}else if(dow.equals(DayOfWeek.SATURDAY)){
return ldt4.plusDays(2);
}else{
return ldt4.plusDays(1);
}
});
System.out.println(ldt5);
}
//3.
//Duration : 用于计算两个“时间”间隔
//Period : 用于计算两个“日期”间隔
@Test
public void test3(){
Instant ins1 = Instant.now();
System.out.println("--------------------");
try {
Thread.sleep(1000);
} catch (InterruptedException e) {
}
Instant ins2 = Instant.now();
System.out.println("所耗费时间为:" + Duration.between(ins1, ins2));
System.out.println("----------------------------------");
LocalDate ld1 = LocalDate.now();
LocalDate ld2 = LocalDate.of(2011, 1, 1);
Period pe = Period.between(ld2, ld1);
System.out.println(pe.getYears());
System.out.println(pe.getMonths());
System.out.println(pe.getDays());
}
//2. Instant : 时间戳。 (使用 Unix 元年 1970年1月1日 00:00:00 所经历的毫秒值)
@Test
public void test2(){
Instant ins = Instant.now(); //默认使用 UTC 时区
System.out.println(ins);
OffsetDateTime odt = ins.atOffset(ZoneOffset.ofHours(8));
System.out.println(odt);
System.out.println(ins.getNano());
Instant ins2 = Instant.ofEpochSecond(5);
System.out.println(ins2);
}
//1. LocalDate、LocalTime、LocalDateTime
@Test
public void test1(){
LocalDateTime ldt = LocalDateTime.now();
System.out.println(ldt);
LocalDateTime ld2 = LocalDateTime.of(2016, 11, 21, 10, 10, 10);
System.out.println(ld2);
LocalDateTime ldt3 = ld2.plusYears(20);
System.out.println(ldt3);
LocalDateTime ldt4 = ld2.minusMonths(2);
System.out.println(ldt4);
System.out.println(ldt.getYear());
System.out.println(ldt.getMonthValue());
System.out.println(ldt.getDayOfMonth());
System.out.println(ldt.getHour());
System.out.println(ldt.getMinute());
System.out.println(ldt.getSecond());
}
}
在Java 8中,Base64编码已经成为Java类库的标准。
Java 8 内置了 Base64 编码的编码器和解码器。
Base64工具类提供了一套静态方法获取下面三种BASE64编解码器:
菜鸟教程: https://www.runoob.com/java/java8-new-features.html
尚硅谷:http://www.gulixueyuan.com/course/56/tasks
1、Lambda 表达式
2、方法引用
3、函数式接口
4、默认方法
5、Stream
6、Optional 类
7、Nashorn, JavaScript 引擎
8、新的日期时间 API
9、Base64