CompletableFuture使用
/**
* 七大参数
* 1、corePoolSize:核心线程数，线程池创建好了就准备的线程数，等待异步任务去调用。一直存活除非指明了allowCoreThreadTimeOut
* 2、maximumPoolSize：最大线程数量，控制资源
* 3、keepAliveTime：当前存活时间，当线程数大于core指定的数据，当超过的线程数空闲时间大于这个keepAliveTime，线程释放。
* 4、TimeUnit：时间单位
* 5、BlockingQueue<Runnable> workQueue：阻塞队列，如果任务很多，会把任务放到队列里面，当线程空闲了就去队列里面拉任务执行
* 6、ThreadFactory：创建线程的工厂
* 7、RejectedExecutionHandler：如果队列满了，按照我们指定拒绝策略执行任务
**/
ThreadPoolExecutor executor = new ThreadPoolExecutor(5,
20,
10,
TimeUnit.SECONDS,
new LinkedBlockingDeque<>(100),
Executors.defaultThreadFactory(),
new ThreadPoolExecutor.AbortPolicy());
1.启动异步任务
-
无返回值启动
@Test public void test2(){ System.out.println("start.................."); CompletableFuture<Void> completableFuture = CompletableFuture.runAsync(() -> { System.out.println("当前线程：" + Thread.currentThread().getId()); int i = 10 / 2; System.out.println("运行结果：" + i); }, executor); System.out.println("end.................."); } -
有返回值启动
@Test public void test3() throws ExecutionException, InterruptedException { System.out.println("start.................."); CompletableFuture<Integer> completableFuture = CompletableFuture.supplyAsync(() -> { System.out.println("当前线程：" + Thread.currentThread().getId()); int i = 10 / 2; System.out.println("运行结果：" + i); return i; }, executor); System.out.println("返回的结果："+completableFuture.get()); System.out.println("end.................."); }
2.计算完成时的回调方法
// 和上一个任务用同一个线程
public CompletableFuture<T> whenComplete(
BiConsumer<? super T, ? super Throwable> action) {
return uniWhenCompleteStage(null, action);
}
// 异步调用一个新的线程
public CompletableFuture<T> whenCompleteAsync(
BiConsumer<? super T, ? super Throwable> action) {
return uniWhenCompleteStage(asyncPool, action);
}
public CompletableFuture<T> whenCompleteAsync(
BiConsumer<? super T, ? super Throwable> action, Executor executor) {
return uniWhenCompleteStage(screenExecutor(executor), action);
}
# 使用
@Test
public void test4() throws ExecutionException, InterruptedException {
System.out.println("start..................");
CompletableFuture<Integer> completableFuture = CompletableFuture.supplyAsync(() -> {
System.out.println("当前线程：" + Thread.currentThread().getId());
int i = 10 / 0;
System.out.println("运行结果：" + i);
return i;
}, executor).whenComplete((res,exception)->{
// 虽然可以得到异常信息，但是没有办法修改返回值
System.out.println("异步任务运行结束，获取结果是："+res+";异常是："+exception);
}).exceptionally(throwable -> {
// 可以感知异常，同时返回一个异常时抛出的默认返回值
return 10;
});
System.out.println("返回的结果："+completableFuture.get());
System.out.println("end..................");
}
3.handle方法
# whenComplete只能感知异常没办处理返回结果，handle可以进行方法执行完成的处理
public <U> CompletableFuture<U> handle(
BiFunction<? super T, Throwable, ? extends U> fn) {
return uniHandleStage(null, fn);
}
public <U> CompletableFuture<U> handleAsync(
BiFunction<? super T, Throwable, ? extends U> fn) {
return uniHandleStage(asyncPool, fn);
}
public <U> CompletableFuture<U> handleAsync(
BiFunction<? super T, Throwable, ? extends U> fn, Executor executor) {
return uniHandleStage(screenExecutor(executor), fn);
}
@Test
public void test5() throws ExecutionException, InterruptedException {
System.out.println("start..................");
CompletableFuture<Integer> completableFuture = CompletableFuture.supplyAsync(() -> {
System.out.println("当前线程：" + Thread.currentThread().getId());
int i = 10 / 0;
System.out.println("运行结果：" + i);
return i;
}, executor).handle((res,thr)->{
if(res != null){
return res*2;
}
if(thr != null){
return 0;
}
return 0;
});
System.out.println("返回的结果："+completableFuture.get());
System.out.println("end..................");
}
4.线程串行化方法
# 需要上一个任务的返回结果，作为下一个任务的参数，并且返回执行完成后的结果
public <U> CompletableFuture<U> thenApply(
Function<? super T,? extends U> fn) {
return uniApplyStage(null, fn);
}
public <U> CompletableFuture<U> thenApplyAsync(
Function<? super T,? extends U> fn) {
return uniApplyStage(asyncPool, fn);
}
public <U> CompletableFuture<U> thenApplyAsync(
Function<? super T,? extends U> fn, Executor executor) {
return uniApplyStage(screenExecutor(executor), fn);
}
# 需要上一个任务的返回结果，作为下一个任务的参数
public CompletableFuture<Void> thenAccept(Consumer<? super T> action) {
return uniAcceptStage(null, action);
}
public CompletableFuture<Void> thenAcceptAsync(Consumer<? super T> action) {
return uniAcceptStage(asyncPool, action);
}
public CompletableFuture<Void> thenAcceptAsync(Consumer<? super T> action,
Executor executor) {
return uniAcceptStage(screenExecutor(executor), action);
}
# 不需要接收上一个的返回结果，开启下一个任务
public CompletableFuture<Void> thenRun(Runnable action) {
return uniRunStage(null, action);
}
public CompletableFuture<Void> thenRunAsync(Runnable action) {
return uniRunStage(asyncPool, action);
}
public CompletableFuture<Void> thenRunAsync(Runnable action,
Executor executor) {
return uniRunStage(screenExecutor(executor), action);
}
@Test
public void test6() throws ExecutionException, InterruptedException {
System.out.println("start..................");
CompletableFuture.supplyAsync(() -> {
System.out.println("当前线程：" + Thread.currentThread().getId());
int i = 10 / 2;
System.out.println("运行结果：" + i);
return i;
}, executor).thenRunAsync(()->{
System.out.println("任务2启动");
},executor);
System.out.println("end..................");
}
@Test
public void test7() throws ExecutionException, InterruptedException {
System.out.println("start..................");
CompletableFuture.supplyAsync(() -> {
System.out.println("当前线程：" + Thread.currentThread().getId());
int i = 10 / 2;
System.out.println("运行结果：" + i);
return i;
}, executor).thenAcceptAsync(res ->{
System.out.println("任务2启动,上一步的值："+res);
});
System.out.println("end..................");
}
@Test
public void test8() throws ExecutionException, InterruptedException {
System.out.println("start..................");
CompletableFuture<Integer> integerCompletableFuture = CompletableFuture.supplyAsync(() -> {
System.out.println("当前线程：" + Thread.currentThread().getId());
int i = 10 / 2;
System.out.println("运行结果：" + i);
return i;
}, executor).thenApplyAsync(res -> {
System.out.println("任务2启动，上一步的值：" + res);
return res * 10;
}, executor);
System.out.println("结果"+integerCompletableFuture.get());
System.out.println("end..................");
}
##5.两任务组合-都要完成
# 组合二个任务没有返回值也不能获取参数值
public CompletableFuture<Void> runAfterBoth(CompletionStage<?> other,
Runnable action) {
return biRunStage(null, other, action);
}
public CompletableFuture<Void> runAfterBothAsync(CompletionStage<?> other,
Runnable action) {
return biRunStage(asyncPool, other, action);
}
public CompletableFuture<Void> runAfterBothAsync(CompletionStage<?> other,
Runnable action,
Executor executor) {
return biRunStage(screenExecutor(executor), other, action);
}
# 组合二个任务没有返回值有参数值
public <U> CompletableFuture<Void> thenAcceptBoth(
CompletionStage<? extends U> other,
BiConsumer<? super T, ? super U> action) {
return biAcceptStage(null, other, action);
}
public <U> CompletableFuture<Void> thenAcceptBothAsync(
CompletionStage<? extends U> other,
BiConsumer<? super T, ? super U> action) {
return biAcceptStage(asyncPool, other, action);
}
public <U> CompletableFuture<Void> thenAcceptBothAsync(
CompletionStage<? extends U> other,
BiConsumer<? super T, ? super U> action, Executor executor) {
return biAcceptStage(screenExecutor(executor), other, action);
}
# 组合二个任务有返回值有参数值
public <U> CompletableFuture<U> thenCompose(
Function<? super T, ? extends CompletionStage<U>> fn) {
return uniComposeStage(null, fn);
}
public <U> CompletableFuture<U> thenComposeAsync(
Function<? super T, ? extends CompletionStage<U>> fn) {
return uniComposeStage(asyncPool, fn);
}
public <U> CompletableFuture<U> thenComposeAsync(
Function<? super T, ? extends CompletionStage<U>> fn,
Executor executor) {
return uniComposeStage(screenExecutor(executor), fn);
}
@Test
public void test9() throws ExecutionException, InterruptedException {
System.out.println("start..................");
CompletableFuture<Integer> future01 = CompletableFuture.supplyAsync(() -> {
System.out.println("当前线程1开启：" + Thread.currentThread().getId());
int i = 10 / 2;
System.out.println("当前线程1结束：" + Thread.currentThread().getId());
return i;
}, executor);
CompletableFuture<String> future02 = CompletableFuture.supplyAsync(() -> {
System.out.println("当前线程2开启：" + Thread.currentThread().getId());
System.out.println("当前线程2结束：" + Thread.currentThread().getId());
return "hellow";
}, executor);
future01.runAfterBothAsync(future02,()->{
System.out.println("任务3开启");
},executor);
System.out.println("end..................");
}
@Test
public void test10() throws ExecutionException, InterruptedException {
System.out.println("start..................");
CompletableFuture<Integer> future01 = CompletableFuture.supplyAsync(() -> {
System.out.println("当前线程1开启：" + Thread.currentThread().getId());
int i = 10 / 2;
System.out.println("当前线程1结束：" + Thread.currentThread().getId());
return i;
}, executor);
CompletableFuture<String> future02 = CompletableFuture.supplyAsync(() -> {
System.out.println("当前线程2开启：" + Thread.currentThread().getId());
System.out.println("当前线程2结束：" + Thread.currentThread().getId());
return "hellow";
}, executor);
future01.thenAcceptBothAsync(future02,(f1,f2)->{
System.out.println("任务3开启:"+f1+"->"+f2);
},executor);
System.out.println("end..................");
}
@Test
public void test11() throws ExecutionException, InterruptedException {
System.out.println("start..................");
CompletableFuture<Integer> future01 = CompletableFuture.supplyAsync(() -> {
System.out.println("当前线程1开启：" + Thread.currentThread().getId());
int i = 10 / 2;
System.out.println("当前线程1结束：" + Thread.currentThread().getId());
return i;
}, executor);
CompletableFuture<String> future02 = CompletableFuture.supplyAsync(() -> {
System.out.println("当前线程2开启：" + Thread.currentThread().getId());
System.out.println("当前线程2结束：" + Thread.currentThread().getId());
return "hellow";
}, executor);
CompletableFuture<String> future03 = future01.thenCombineAsync(future02, (f1, f2) -> {
System.out.println("任务3开启");
return f1 + f2;
}, executor);
System.out.println("任务3返回"+future03.get());
System.out.println("end..................");
}
6.两任务组合-一个完成
public CompletableFuture<Void> runAfterEither(CompletionStage<?> other,
Runnable action) {
return orRunStage(null, other, action);
}
public CompletableFuture<Void> runAfterEitherAsync(CompletionStage<?> other,
Runnable action) {
return orRunStage(asyncPool, other, action);
}
public CompletableFuture<Void> runAfterEitherAsync(CompletionStage<?> other,
Runnable action,
Executor executor) {
return orRunStage(screenExecutor(executor), other, action);
public CompletableFuture<Void> acceptEither(
CompletionStage<? extends T> other, Consumer<? super T> action) {
return orAcceptStage(null, other, action);
}
public CompletableFuture<Void> acceptEitherAsync(
CompletionStage<? extends T> other, Consumer<? super T> action) {
return orAcceptStage(asyncPool, other, action);
}
public CompletableFuture<Void> acceptEitherAsync(
CompletionStage<? extends T> other, Consumer<? super T> action,
Executor executor) {
return orAcceptStage(screenExecutor(executor), other, action);
}
public <U> CompletableFuture<U> applyToEither(
CompletionStage<? extends T> other, Function<? super T, U> fn) {
return orApplyStage(null, other, fn);
}
public <U> CompletableFuture<U> applyToEitherAsync(
CompletionStage<? extends T> other, Function<? super T, U> fn) {
return orApplyStage(asyncPool, other, fn);
}
public <U> CompletableFuture<U> applyToEitherAsync(
CompletionStage<? extends T> other, Function<? super T, U> fn,
Executor executor) {
return orApplyStage(screenExecutor(executor), other, fn);
}
##7.多任务组合
/**
* Returns a new CompletableFuture that is completed when all of
* the given CompletableFutures complete. If any of the given
* CompletableFutures complete exceptionally, then the returned
* CompletableFuture also does so, with a CompletionException
* holding this exception as its cause. Otherwise, the results,
* if any, of the given CompletableFutures are not reflected in
* the returned CompletableFuture, but may be obtained by
* inspecting them individually. If no CompletableFutures are
* provided, returns a CompletableFuture completed with the value
* {@code null}.
*
* <p>Among the applications of this method is to await completion
* of a set of independent CompletableFutures before continuing a
* program, as in: {@code CompletableFuture.allOf(c1, c2,
* c3).join();}.
*
* @param cfs the CompletableFutures
* @return a new CompletableFuture that is completed when all of the
* given CompletableFutures complete
* @throws NullPointerException if the array or any of its elements are
* {@code null}
*/
public static CompletableFuture<Void> allOf(CompletableFuture<?>... cfs) {
return andTree(cfs, 0, cfs.length - 1);
}
/**
* Returns a new CompletableFuture that is completed when any of
* the given CompletableFutures complete, with the same result.
* Otherwise, if it completed exceptionally, the returned
* CompletableFuture also does so, with a CompletionException
* holding this exception as its cause. If no CompletableFutures
* are provided, returns an incomplete CompletableFuture.
*
* @param cfs the CompletableFutures
* @return a new CompletableFuture that is completed with the
* result or exception of any of the given CompletableFutures when
* one completes
* @throws NullPointerException if the array or any of its elements are
* {@code null}
*/
public static CompletableFuture<Object> anyOf(CompletableFuture<?>... cfs) {
return orTree(cfs, 0, cfs.length - 1);
}
JDK lambda
1.函数式接口
定义：只包含一个抽象方法的接口，称为函数式接口，在任意函数式接口上使用 @FunctionalInterface 注解， 这样做可以检查它是否是一个函数式接口。
@FunctionalInterface
public interface MyFun<T> {
public T getValue(T num);
}
//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);
}
@FunctionalInterface
public interface MyPredicate<T> {
public boolean test(T t);
}
//优化方式一：策略设计模式
public List<Employee> filterEmployee(List<Employee> emps, MyPredicate<Employee> mp){
List<Employee> list = new ArrayList<>();
for (Employee employee : emps) {
if(mp.test(employee)){
list.add(employee);
}
}
return list;
}
//优化方式三：Lambda 表达式
@Test
public void test6(){
List<Employee> list = filterEmployee(emps, (e) -> e.getAge() <= 35);
list.forEach(System.out::println);
System.out.println("------------------------------------------");
List<Employee> list2 = filterEmployee(emps, (e) -> e.getSalary() >= 5000);
list2.forEach(System.out::println);
}
##2.Java 内置四大核心函数式接口
/*
* Java8 内置的四大核心函数式接口
*
* Consumer<T> : 消费型接口
* void accept(T t);
*
* Supplier<T> : 供给型接口
* T get();
*
* Function<T, R> : 函数型接口
* R apply(T t);
*
* Predicate<T> : 断言型接口
* boolean test(T t);
*
*/
public class TestLambda3 {
//Predicate<T> 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<T, R> 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<T> 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<T> 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);
}
}
3.方法引用和构造器引用
/*
* 一、方法引用：若 Lambda 体中的功能，已经有方法提供了实现，可以使用方法引用
* （可以将方法引用理解为 Lambda 表达式的另外一种表现形式）
*
* 1. 对象的引用 :: 实例方法名
*
* 2. 类名 :: 静态方法名
*
* 3. 类名 :: 实例方法名
*
* 注意：
* 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
*
* 二、构造器引用 :构造器的参数列表，需要与函数式接口中参数列表保持一致！
*
* 1. 类名 :: new
*
* 三、数组引用
*
* 类型[] :: new;
*
*
*/
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;
}
}
4.强大的Stream API
定义：是数据渠道，用于操作数据源（集合、数组等）所生成的元素序列。“集合讲的是数据，流讲的是计算！”
注意：
- Stream 自己不会存储元素。
- Stream 不会改变源对象。相反，他们会返回一个持有结果的新Stream。
- Stream 操作是延迟执行的。这意味着他们会等到需要结果的时候才执行。
Stream操作的三个步骤：创建->中间操作->终止操作
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;
/*
* 一、 Stream 的操作步骤
*
* 1. 创建 Stream
*
* 2. 中间操作
*
* 3. 终止操作
*/
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。
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
*/
@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.Arrays;
import java.util.List;
import java.util.Optional;
import java.util.stream.Stream;
import org.junit.Test;
import com.atguigu.java8.Employee.Status;
/*
* 一、 Stream 的操作步骤
*
* 1. 创建 Stream
*
* 2. 中间操作
*
* 3. 终止操作
*/
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)
);
//3. 终止操作
/*
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——检查是否没有匹配的元素
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——返回流中最大值
min——返回流中最小值
*/
@Test
public void test1(){
boolean bl = emps.stream()
.allMatch((e) -> e.getStatus().equals(Status.BUSY));
System.out.println(bl);
boolean bl1 = emps.stream()
.anyMatch((e) -> e.getStatus().equals(Status.BUSY));
System.out.println(bl1);
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("--------------------------------");
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);
}
}
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());
}
}
5.Fork/Join 框架
定义：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.
Fork/Join 框架与传统线程池的区别：
采用 “工作窃取”模式（work-stealing）： 当执行新的任务时它可以将其拆分分成更小的任务执行，并将小任务加到线 程队列中，然后再从一个随机线程的队列中偷一个并把它放在自己的队列中。 相对于一般的线程池实现,fork/join框架的优势体现在对其中包含的任务的 处理方式上.在一般的线程池中,如果一个线程正在执行的任务由于某些原因 无法继续运行,那么该线程会处于等待状态.而在fork/join框架实现中,如果 某个子问题由于等待另外一个子问题的完成而无法继续运行.那么处理该子 问题的线程会主动寻找其他尚未运行的子问题来执行.这种方式减少了线程 的等待时间,提高了性能.
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();
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;
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();
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
}
}
6.新时间日期API
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());
}
}
7.Optional 类
package com.atguigu.java8;
import java.util.Optional;
import org.junit.Test;
/*
* 一、Optional 容器类：用于尽量避免空指针异常
* Optional.of(T t) : 创建一个 Optional 实例
* Optional.empty() : 创建一个空的 Optional 实例
* Optional.ofNullable(T t):若 t 不为 null,创建 Optional 实例,否则创建空实例
* isPresent() : 判断是否包含值
* orElse(T t) : 如果调用对象包含值，返回该值，否则返回t
* orElseGet(Supplier s) :如果调用对象包含值，返回该值，否则返回 s 获取的值
* map(Function f): 如果有值对其处理，并返回处理后的Optional，否则返回 Optional.empty()
* flatMap(Function mapper):与 map 类似，要求返回值必须是Optional
*/
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<Employee> op = Optional.ofNullable(null);
System.out.println(op.get());*/
// Optional<Employee> 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();
}
}
