Java高并发系列——检视阅读(八)

Java高并发系列——CompletableFuture

JUC中工具类CompletableFuture

CompletableFuture是java8中新增的一个类,算是对Future的一种增强,用起来很方便,也是会经常用到的一个工具类,熟悉一下。

CompletionStage接口

  • CompletionStage代表异步计算过程中的某一个阶段,一个阶段完成以后可能会触发另外一个阶段
  • 一个阶段的计算执行可以是一个Function,Consumer或者Runnable。比如:stage.thenApply(x -> square(x)).thenAccept(x -> System.out.print(x)).thenRun(() -> System.out.println())
  • 一个阶段的执行可能是被单个阶段的完成触发,也可能是由多个阶段一起触发

CompletableFuture类

  • 在Java8中,CompletableFuture提供了非常强大的Future的扩展功能,可以帮助我们简化异步编程的复杂性,并且提供了函数式编程的能力,可以通过回调的方式处理计算结果,也提供了转换和组合 CompletableFuture 的方法。
  • 它可能代表一个明确完成的Future,也有可能代表一个完成阶段( CompletionStage ),它支持在计算完成以后触发一些函数或执行某些动作。
  • 实现了Future和CompletionStage接口

常见的方法,熟悉一下:

runAsync 和 supplyAsync方法

CompletableFuture 提供了四个静态方法来创建一个异步操作。

public static CompletableFuture runAsync(Runnable runnable)
public static CompletableFuture runAsync(Runnable runnable, Executor executor)
public static  CompletableFuture supplyAsync(Supplier supplier)
public static  CompletableFuture supplyAsync(Supplier supplier, Executor executor)

没有指定Executor的方法会使用ForkJoinPool.commonPool() 作为它的线程池执行异步代码。如果指定线程池,则使用指定的线程池运行。以下所有的方法都类同。

  • runAsync方法不支持返回值。
  • supplyAsync可以支持返回值。

示例:

public class CompletableFutureTest1 {

    public static void main(String[] args) throws Exception {
        CompletableFutureTest1.runAsync();
        CompletableFutureTest1.supplyAsync();
    }

    //runAsync方法不支持返回值 Runnable
    public static void runAsync() throws Exception {
        CompletableFuture future = CompletableFuture.runAsync(() -> {
            try {
                TimeUnit.SECONDS.sleep(1);
            } catch (InterruptedException e) {
            }
            System.out.println("run end ...");
        });

        future.get();
    }

    //supplyAsync可以支持返回值 Supplier
    public static void supplyAsync() throws Exception {
        CompletableFuture future = CompletableFuture.supplyAsync(() -> {
            try {
                TimeUnit.SECONDS.sleep(1);
            } catch (InterruptedException e) {
            }
            System.out.println("run end ...");
            return System.currentTimeMillis();
        });
  //如果没有future.get()阻塞等待结果的话,因为CompletableFuture.supplyAsync()方法默认是守护线程形式执行任务,在主线程结束后会跟着退出,
        // 如果传入的是线程池去执行,这不是守护线程,不会导致退出
        long time = future.get();
        System.out.println("time = "+time);
    }
}

输出:

run end ...
run end ...
time = 1599556248764

计算结果完成时的回调方法

当CompletableFuture的计算结果完成,或者抛出异常的时候,可以执行特定的Action。主要是下面的方法:

public CompletableFuture whenComplete(BiConsumer action)
public CompletableFuture whenCompleteAsync(BiConsumer action)
public CompletableFuture whenCompleteAsync(BiConsumer action, Executor executor)
public CompletableFuture exceptionally(Function fn)

可以看到Action的类型是BiConsumer它可以处理正常的计算结果,或者异常情况。

whenComplete 和 whenCompleteAsync 的区别:

  • whenComplete:当前任务的线程继续执行 whenComplete 的任务。
  • whenCompleteAsync:把 whenCompleteAsync 这个任务继续提交给线程池来进行执行

示例:

public class CompletableFutureTest1 {

    public static void main(String[] args) throws Exception {
        CompletableFutureTest1.whenComplete();
        CompletableFutureTest1.whenCompleteBySupply();
    }

    public static void whenComplete() throws Exception {
        CompletableFuture future = CompletableFuture.runAsync(() -> {
            try {
                TimeUnit.SECONDS.sleep(1);
            } catch (InterruptedException e) {
            }
            if (new Random().nextInt() % 2 >= 0) {
                int i = 12 / 0;
                //run end ...
                //执行完成!
                //int i = 12 / 0;
            }
            System.out.println("run end ...");
        });
        //对执行成功或者执行异常做处理的回调方法
        future.whenComplete((avoid, throwable) -> {
            //先判断是否抛异常分开处理
            if (throwable != null) {
                System.out.println("执行失败!" + throwable.getMessage());
            } else {
                System.out.println("执行完成!");
            }
        });
        //对执行异常做处理的回调方法
        future.exceptionally(throwable -> {
                    System.out.println("执行失败!" + throwable.getMessage());
                    return null;
                }
        );
        TimeUnit.SECONDS.sleep(2);
    }

    public static void whenCompleteBySupply() throws Exception {
        CompletableFuture future = CompletableFuture.supplyAsync(() -> {
            try {
                TimeUnit.SECONDS.sleep(1);
            } catch (InterruptedException e) {
            }
            if (new Random().nextInt() % 2 >= 0) {
                //int i = 12 / 0;
                //run end ...
                //执行完成!
                //int i = 12 / 0;
            }
            System.out.println("run end ...");
            return "success";
        });
        //whenComplete在thenAccept之前执行
        future.thenAccept(result -> {
            System.out.println(result);
        });
        //对执行成功或者执行异常做处理的回调方法
        future.whenComplete((avoid, throwable) -> {
            //先判断是否抛异常分开处理
            if (throwable != null) {
                System.out.println("执行失败!" + throwable.getMessage());
            } else {
                System.out.println("执行完成!");
            }
        });
        //对执行异常做处理的回调方法
        future.exceptionally(throwable -> {
                    System.out.println("执行失败!" + throwable.getMessage());
                    return null;
                }
        );
        TimeUnit.SECONDS.sleep(2);
    }
    }

输出:

执行失败!java.lang.ArithmeticException: / by zero
执行失败!java.lang.ArithmeticException: / by zero
run end ...
执行完成!
success

thenApply 方法

当一个线程依赖另一个线程时,可以使用 thenApply、thenApplyAsync 方法来把这两个线程串行化。

public  CompletableFuture thenApply(Function fn)
public  CompletableFuture thenApplyAsync(Function fn)
public  CompletableFuture thenApplyAsync(Function fn, Executor executor)
Function 
T:上一个任务返回结果的类型
U:当前任务的返回值类型

示例:

public class CompletableFutureTest2 {

    public static void main(String[] args) throws Exception {
        CompletableFutureTest2.thenApply();
    }
    //多个CompletableFuture可以串行执行
    //当一个线程依赖另一个线程时,可以使用 thenApply 方法来把这两个线程串行化。
    //多个任务串行执行,第二个任务依赖第一个任务的结果。
    private static void thenApply() throws Exception {
        CompletableFuture future = CompletableFuture.supplyAsync(() -> {
                    long result = new Random().nextInt(100);
                    System.out.println("result1=" + result);
                    return result;
                }
        ).thenApply((t -> {
            long result = t * 5;
            System.out.println("result2=" + result);
            return result;
        }));
        //方式一:阻塞等待结果
        long result = future.get();
        System.out.println("result2: " + result);
        //方式二:调用成功后接收任务的处理结果,并消费处理,无返回结果
        future.thenAccept((r) -> {
            System.out.println("result2: " + r);
        });
    }
}

输出:

result1=41
result2=205
result2: 205
result2: 205

handle 方法——可以处理正常和异常情况的thenApply 方法

handle 是执行任务完成时对结果的处理。
handle 方法和 thenApply 方法处理方式基本一样。不同的是 handle 是在任务完成后再执行,还可以处理异常的任务。thenApply 只可以执行正常的任务,任务出现异常则不执行 thenApply 方法。

public  CompletionStage handle(BiFunction fn);
public  CompletionStage handleAsync(BiFunction fn);
public  CompletionStage handleAsync(BiFunction fn,Executor executor);

示例:在 handle 中可以根据任务是否有异常来进行做相应的后续处理操作。而 thenApply 方法,如果上个任务出现错误,则不会执行 thenApply 方法。

public class CompletableFutureTest3 {

    public static void main(String[] args) throws Exception {
        CompletableFutureTest3.handle();
    }

    public static void handle() throws Exception {
        CompletableFuture future = CompletableFuture.supplyAsync(new Supplier() {

            @Override
            public Integer get() {
                int i = 10 / 0;
                return new Random().nextInt(10);
            }
        }).handle(
                (param, throwable) -> {
                    int result = -1;
                    if (throwable == null) {
                        result = param * 2;
                    } else {
                        System.out.println(throwable.getMessage());
                    }
                    return result;
                }
                /*new BiFunction() {
            @Override
            public Integer apply(Integer param, Throwable throwable) {
                int result = -1;
                if(throwable==null){
                    result = param * 2;
                }else{
                    System.out.println(throwable.getMessage());
                }
                return result;
            }
        }*/);
        System.out.println(future.get());
    }
}

输出:

java.lang.ArithmeticException: / by zero
-1

thenAccept 消费处理结果——无返回结果

接收任务的处理结果,并消费处理,无返回结果。

public CompletionStage thenAccept(Consumer action);
public CompletionStage thenAcceptAsync(Consumer action);
public CompletionStage thenAcceptAsync(Consumer action,Executor executor);

示例:

public class CompletableFutureTest3 {

    public static void main(String[] args) throws Exception {
        //CompletableFutureTest3.handle();
        CompletableFutureTest3.thenAccept();
    }

    public static void thenAccept() throws Exception {
        CompletableFuture future = CompletableFuture.supplyAsync(() -> {
                    return new Random().nextInt(10);
                }
        ).thenAccept(integer -> {
            System.out.println(integer);
        });
        future.get();
    }
}
   //输出:5 

thenRun 方法——继续执行下一个Runnable任务,不获取上一个任务的处理结果

跟 thenAccept 方法不一样的是,不关心任务的处理结果。只要上面的任务执行完成,就开始执行 thenRun 。

public CompletionStage thenRun(Runnable action);
public CompletionStage thenRunAsync(Runnable action);
public CompletionStage thenRunAsync(Runnable action,Executor executor);

示例:

public class CompletableFutureTest3 {

    public static void main(String[] args) throws Exception {
        CompletableFutureTest3.thenRun();
    }

    public static void thenRun() throws Exception{
        CompletableFuture future = CompletableFuture.supplyAsync(new Supplier() {
            @Override
            public Integer get() {
                try {
                    TimeUnit.SECONDS.sleep(2);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
                return new Random().nextInt(10);
            }
        }).thenRun(() -> {
            System.out.println("thenRun ...");
        });
        future.get();
    }
}
//2秒后输出:thenRun ...

thenCombine 合并任务

thenCombine 会把 两个 CompletionStage 的任务都执行完成后,把两个任务的结果一块交给 thenCombine 来处理。

public  CompletionStage thenCombine(CompletionStage other,BiFunction fn);
public  CompletionStage thenCombineAsync(CompletionStage other,BiFunction fn);
public  CompletionStage thenCombineAsync(CompletionStage other,BiFunction fn,Executor executor);

示例:

public class CompletableFutureTest3 {

    public static void main(String[] args) throws Exception {
        CompletableFutureTest3.thenCombine();
    }

    private static void thenCombine() throws Exception {
        CompletableFuture future1 = CompletableFuture.supplyAsync(() -> {
            return "hello";
        });
        CompletableFuture future2 = CompletableFuture.supplyAsync(() -> {
            return "world";
        });
        CompletableFuture result = future1.thenCombine(future2, (result1, result2) -> {
            return result1 + " " + result2;
        });
        System.out.println(result.get());
    }
}
//输出:hello world

thenAcceptBoth

当两个CompletionStage都执行完成后,把结果一块交给thenAcceptBoth来进行消耗。

public  CompletionStage thenAcceptBoth(CompletionStage other,BiConsumer action);
public  CompletionStage thenAcceptBothAsync(CompletionStage other,BiConsumer action);
public  CompletionStage thenAcceptBothAsync(CompletionStage other,BiConsumer action,     Executor executor);

示例:

public class CompletableFutureTest3 {

    public static void main(String[] args) throws Exception {
        CompletableFutureTest3.thenAcceptBoth();
        //等待守护进程执行完
        TimeUnit.SECONDS.sleep(5);
    }

    private static void thenAcceptBoth() throws Exception {
        CompletableFuture f1 = CompletableFuture.supplyAsync(() -> {
            int t = new Random().nextInt(3);
            try {
                TimeUnit.SECONDS.sleep(t);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            System.out.println("f1=" + t);
            return t;
        });

        CompletableFuture f2 = CompletableFuture.supplyAsync(() -> {
            int t = new Random().nextInt(3);
            try {
                TimeUnit.SECONDS.sleep(t);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            System.out.println("f2=" + t);
            return t;
        });
        f1.thenAcceptBoth(f2, (result1, result2) -> {
            System.out.println("f1=" + result1 + ";f2=" + result2 + ";");
        });
    }
 }

输出:

f1=1
f2=1
f1=1;f2=1;

applyToEither 方法——有返回值消耗

两个CompletionStage,谁执行返回的结果快,我就用那个CompletionStage的结果进行下一步的转化操作

public  CompletionStage applyToEither(CompletionStage other,Function fn);
public  CompletionStage applyToEitherAsync(CompletionStage other,Function fn);
public  CompletionStage applyToEitherAsync(CompletionStage other,Function fn,Executor executor);

示例:

public class CompletableFutureTest3 {
    public static void main(String[] args) throws Exception {
        CompletableFutureTest3.applyToEither();
    }

    private static void applyToEither() throws Exception {
        CompletableFuture f1 = CompletableFuture.supplyAsync(()->{
            int t = 1;
            try {
                TimeUnit.SECONDS.sleep(t);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            System.out.println("f1="+t);
            return t;
        });
        CompletableFuture f2 = CompletableFuture.supplyAsync(()->{
            int t = 2;
            try {
                TimeUnit.SECONDS.sleep(t);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            System.out.println("f2="+t);
            return t;
        });

        CompletableFuture result = f1.applyToEither(f2, (r)->{
            System.out.println(r);
            return r * 2;
        });
        System.out.println(result.get());
    }

输出:

f1=1
1
2

acceptEither 方法——无返回值消耗

两个CompletionStage,谁执行返回的结果快,我就用那个CompletionStage的结果进行下一步的消耗操作。注意,这时候其实两个CompletionStage都是会执行完的,只是我们只获取其中的一个比较快的结果而已,参考示例的输出。

public CompletionStage acceptEither(CompletionStage other,Consumer action);
public CompletionStage acceptEitherAsync(CompletionStage other,Consumer action);
public CompletionStage acceptEitherAsync(CompletionStage other,Consumer action,Executor executor);

示例:

public class CompletableFutureTest3 {
    public static void main(String[] args) throws Exception {
        //CompletableFutureTest3.applyToEither();
        CompletableFutureTest3.acceptEither();
        TimeUnit.SECONDS.sleep(5);
    }

    private static void acceptEither() throws Exception {
        CompletableFuture f1 = CompletableFuture.supplyAsync(() -> {
            int t = new Random().nextInt(3);
            try {
                TimeUnit.SECONDS.sleep(t);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            System.out.println("f1=" + t);
            return t;
        });

        CompletableFuture f2 = CompletableFuture.supplyAsync(() -> {
            int t = new Random().nextInt(3);
            try {
                TimeUnit.SECONDS.sleep(t);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            System.out.println("f2=" + t);
            return t;
        });
        f1.acceptEither(f2, (t) -> {
            System.out.println(t);
        });
    }
}

输出:

f1=1
1
f2=2

runAfterEither 方法

两个CompletionStage,任何一个完成了都会执行下一步的操作(Runnable),两个CompletionStage都是会执行完的.

public CompletionStage runAfterEither(CompletionStage other,Runnable action);
public CompletionStage runAfterEitherAsync(CompletionStage other,Runnable action);
public CompletionStage runAfterEitherAsync(CompletionStage other,Runnable action,Executor executor);

示例代码

public class CompletableFutureTest3 {
    public static void main(String[] args) throws Exception {
        //CompletableFutureTest3.applyToEither();
        //CompletableFutureTest3.acceptEither();
        CompletableFutureTest3.runAfterEither();
        TimeUnit.SECONDS.sleep(5);
    }

    private static void runAfterEither() throws Exception {
        CompletableFuture f1 = CompletableFuture.supplyAsync(new Supplier() {
            @Override
            public Integer get() {
                int t = new Random().nextInt(3);
                try {
                    TimeUnit.SECONDS.sleep(t);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
                System.out.println("f1=" + t);
                return t;
            }
        });

        CompletableFuture f2 = CompletableFuture.supplyAsync(new Supplier() {
            @Override
            public Integer get() {
                int t = new Random().nextInt(3);
                try {
                    TimeUnit.SECONDS.sleep(t);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
                System.out.println("f2=" + t);
                return t;
            }
        });
        f1.runAfterEither(f2, ()->{
            System.out.println("上面有一个已经完成了。");
        });
    }
}

输出:

f1=0
上面有一个已经完成了。
f2=1

runAfterBoth

两个CompletionStage,都完成了计算才会执行下一步的操作(Runnable),注意输出顺序,runAfterBoth方法要等两个CompletionStage都执行完了才会执行。

public CompletionStage runAfterBoth(CompletionStage other,Runnable action);
public CompletionStage runAfterBothAsync(CompletionStage other,Runnable action);
public CompletionStage runAfterBothAsync(CompletionStage other,Runnable action,Executor executor);

示例代码

public class CompletableFutureTest3 {
    public static void main(String[] args) throws Exception {
        //CompletableFutureTest3.applyToEither();
        //CompletableFutureTest3.acceptEither();
        //CompletableFutureTest3.runAfterEither();
        CompletableFutureTest3.runAfterBoth();
        TimeUnit.SECONDS.sleep(5);
    }

    private static void runAfterBoth() throws Exception {
        CompletableFuture f1 = CompletableFuture.supplyAsync(new Supplier() {
            @Override
            public Integer get() {
                int t = new Random().nextInt(3);
                try {
                    TimeUnit.SECONDS.sleep(t);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
                System.out.println("f1="+t);
                return t;
            }
        });

        CompletableFuture f2 = CompletableFuture.supplyAsync(new Supplier() {
            @Override
            public Integer get() {
                int t = new Random().nextInt(3);
                try {
                    TimeUnit.SECONDS.sleep(t);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
                System.out.println("f2="+t);
                return t;
            }
        });
        f1.runAfterBoth(f2, new Runnable() {

            @Override
            public void run() {
                System.out.println("上面两个任务都执行完成了。");
            }
        });
    }
}

输出:

f1=1
f2=2
上面两个任务都执行完成了。

thenCompose 方法

thenCompose 方法允许你对两个 CompletionStage 进行流水线操作,第一个操作完成时,将其结果作为参数传递给第二个操作。

public  CompletableFuture thenCompose(Function> fn);
public  CompletableFuture thenComposeAsync(Function> fn) ;
public  CompletableFuture thenComposeAsync(Function> fn, Executor executor) ;

示例代码

public class CompletableFutureTest3 {
    public static void main(String[] args) throws Exception {
        CompletableFutureTest3.thenCompose();
        TimeUnit.SECONDS.sleep(3);
    }

    private static void thenCompose() throws Exception {
        CompletableFuture f = CompletableFuture.supplyAsync(() -> {
            int t = new Random().nextInt(3);
            System.out.println("t1=" + t);
            return t;
        }).thenCompose((param) -> {
            return CompletableFuture.supplyAsync(() -> {
                int t = param * 2;
                System.out.println("t2=" + t);
                return t;
            });
        });
        System.out.println("thenCompose result : " + f.get());
    }
}

输出:

t1=1
t2=2
thenCompose result : 2

疑问:

Q:thenAcceptBoth与thenCombine 的区别是什么?

A:thenAcceptBoth无返回值消耗执行,thenCombine 会有返回值。一般accept都是没有返回值的,apply是有返回值的。

Q:thenCompose 与thenApply 方法 的区别是什么?不都是串行执行下一个任务,并把第一个任务作为参数传递给第二个任务么?

thApplythenCompose都是将一个CompletableFuture转换为CompletableFuture。不同的是,thenApply中的传入函数的返回值是String,而thenCompose的传入函数的返回值是CompletableFuture

thenApply与thenCompose的异同

获取线程执行结果的6种方法

方式1:Thread的join()方法实现

代码中通过join方式阻塞了当前主线程,当thread线程执行完毕之后,join方法才会继续执行。

join的方式,只能阻塞一个线程,如果其他线程中也需要获取thread线程的执行结果,join方法无能为力了。

示例:

public class ThreadJoinTest {
    //用于封装结果
    static class Result {
        T result;

        public T getResult() {
            return result;
        }

        public void setResult(T result) {
            this.result = result;
        }
    }
    public static void main(String[] args) throws InterruptedException {
        Result result = new Result<>();
        Thread t = new Thread(() -> {
            System.out.println("start thread!");
            try {
                TimeUnit.SECONDS.sleep(1);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            result.setResult("success");
            System.out.println("end thread!");
        });
        t.start();
        //让主线程等待thread线程执行完毕之后再继续,join方法会让当前线程阻塞
        t.join();
        System.out.println("main get result="+result.getResult());
    }
}

输出:

start thread!
end thread!
main get result=success

方式2:CountDownLatch实现

使用CountDownLatch可以让一个或者多个线程等待一批线程完成之后,自己再继续.

示例:

public class CountDownLatchTest2 {
    static class Result{
        private T result;

        public T getResult() {
            return result;
        }

        public void setResult(T result) {
            this.result = result;
        }
    }

    public static void main(String[] args) throws InterruptedException {
        Result result = new Result<>();
        CountDownLatch latch = new CountDownLatch(1);
        Thread t = new Thread(() -> {
            System.out.println("start thread!");
            try {
                TimeUnit.SECONDS.sleep(1);
                result.setResult("success");
                System.out.println("end thread!");
            } catch (InterruptedException e) {
                e.printStackTrace();
            }finally {
                latch.countDown();
            }
        });
        t.start();
        latch.await();
        System.out.println("main get result="+result.getResult());
    }
}

输出:

start thread!
end thread!
main get result=success

方式3:ExecutorService.submit方法实现——ThreadPoolExecutor

使用ExecutorService.submit方法实现的,此方法返回一个Futurefuture.get()会让当前线程阻塞,直到Future关联的任务执行完毕。

示例:

public class ThreadPoolExecutorTest2 {

    public static void main(String[] args) throws ExecutionException, InterruptedException {
        //自定义包含策略
        ThreadPoolExecutor executor = new ThreadPoolExecutor(1, 5, 60,
                TimeUnit.SECONDS, new LinkedBlockingQueue<>(5),
                new DemoThreadFactory("订单创建组"), new ThreadPoolExecutor.AbortPolicy());
        Future future = executor.submit(() -> {
            System.out.println("start thread!");
            try {
                TimeUnit.SECONDS.sleep(1);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            System.out.println("end thread!");
            return "success";
        });
        executor.shutdown();
        System.out.println("main get result="+future.get());
    }
}

输出同上。

方式4:FutureTask方式1——作为Runnable传给Thread执行

线程池的submit方法传入的Callable对象本质上也是包装成一个FutureTask来执行。

代码中使用FutureTask实现的,FutureTask实现了Runnable接口,并且内部带返回值,所以可以传递给Thread直接运行,futureTask.get()会阻塞当前线程,直到FutureTask构造方法传递的任务执行完毕,get方法才会返回。

示例:

public class FutureTaskTest {
    public static void main(String[] args) throws ExecutionException, InterruptedException {
        //创建一个FutureTask
        FutureTask futureTask = new FutureTask<>(() -> {
            System.out.println("start thread!");
            try {
                TimeUnit.SECONDS.sleep(1);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            System.out.println("end thread!");
            return "success";
        });
        //将futureTask传递一个线程运行
        new Thread(futureTask).start();
        //futureTask.get()会阻塞当前线程,直到futureTask执行完毕
        String result = futureTask.get();
        System.out.println("main get result=" + result);
    }
}

方式5:FutureTask方式2——构造FutureTask对象及执行内容,直接在Thread里面跑run方法

当futureTask的run()方法执行完毕之后,futureTask.get()会从阻塞中返回。

示例:

public class FutureTaskTest1 {
    public static void main(String[] args) throws ExecutionException, InterruptedException {
        //创建一个FutureTask
        FutureTask futureTask = new FutureTask<>(() -> {
            System.out.println("start thread!");
            try {
                TimeUnit.SECONDS.sleep(1);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            System.out.println("end thread!");
            return "success";
        });
        //将futureTask传递一个线程运行
        new Thread(()->futureTask.run()).start();
        //futureTask.get()会阻塞当前线程,直到futureTask执行完毕
        String result = futureTask.get();
        System.out.println("main get result=" + result);
    }
}

方式6:CompletableFuture方式实现

CompletableFuture.supplyAsync可以用来异步执行一个带返回值的任务,调用completableFuture.get()

会阻塞当前线程,直到任务执行完毕,get方法才会返回。

public class CompletableFutureTest4 {

    public static void main(String[] args) throws Exception {
        CompletableFuture future = CompletableFuture.supplyAsync(() -> {
            System.out.println("start thread!");
            try {
                TimeUnit.SECONDS.sleep(1);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            System.out.println("end thread!");
            return "success";
        });
        // future.get()会阻塞当前线程直到获得结果
        System.out.println("main get result="+future.get());
    }
}

高并发中计数器的四种实现方式

需求:一个jvm中实现一个计数器功能,需保证多线程情况下数据正确性。

我们来模拟50个线程,每个线程对计数器递增100万次,最终结果应该是5000万。

我们使用4种方式实现,看一下其性能,然后引出为什么需要使用LongAdderLongAccumulator

方式一:使用加锁的方式实现——synchronized或Lock

从示例输出结果看,ReentrantLock的效率明显比synchronized差了2-3倍。

示例:

public class SynchronizeCalculator {
    private static long count = 0;
    private static Lock lock = new ReentrantLock();
    public synchronized static void incrment() {
        count++;
    }

    public static void incrmentByLock() {
        lock.lock();
        try {
            count++;
        }finally {
            lock.unlock();
        }
    }

    public static void main(String[] args) throws InterruptedException {
        for (int i = 0; i < 5; i++) {
            count = 0;
            averageTest();
        }
    }

    public static void averageTest() throws InterruptedException {
        long t1 = System.currentTimeMillis();
        //自定义包含策略
        ThreadPoolExecutor executor = new ThreadPoolExecutor(50, 50, 60,
                TimeUnit.SECONDS, new LinkedBlockingQueue<>(5),
                new DemoThreadFactory("订单创建组"), new ThreadPoolExecutor.AbortPolicy());
        CountDownLatch latch = new CountDownLatch(50);
        for (int i = 0; i < 50; i++) {
            executor.execute(() -> {
                try {
                    for (int j = 0; j < 1000000; j++) {
                        incrment();
                        //incrmentByLock();
                    }
                } finally {
                    latch.countDown();
                }

            });
        }
        latch.await();
        long t2 = System.currentTimeMillis();
        System.out.println(String.format("结果:%s,耗时(ms):%s", count, (t2 - t1)));
        executor.shutdown();
    }
}

输出:

//synchronized
结果:50000000,耗时(ms):490
结果:50000000,耗时(ms):1574
结果:50000000,耗时(ms):399
结果:50000000,耗时(ms):395
结果:50000000,耗时(ms):396
//lock
结果:50000000,耗时(ms):1289
结果:50000000,耗时(ms):1239
结果:50000000,耗时(ms):1224
结果:50000000,耗时(ms):1219
结果:50000000,耗时(ms):1246

方式2:AtomicLong实现

AtomicLong内部采用CAS的方式实现,并发量大的情况下,CAS失败率比较高,导致性能比synchronized还低一些。并发量不是太大的情况下,CAS性能还是可以的。

示例:

public class AtomicLongTest {
    private static AtomicLong count = new AtomicLong(0);

    public static void main(String[] args) throws InterruptedException {
        for (int i = 0; i < 5; i++) {
            count.set(0);
            averageTest();
        }
    }

    public static void averageTest() throws InterruptedException {
        long t1 = System.currentTimeMillis();
        //自定义包含策略
        ThreadPoolExecutor executor = new ThreadPoolExecutor(50, 50, 60,
                TimeUnit.SECONDS, new LinkedBlockingQueue<>(5),
                new DemoThreadFactory("订单创建组"), new ThreadPoolExecutor.AbortPolicy());
        CountDownLatch latch = new CountDownLatch(50);
        for (int i = 0; i < 50; i++) {
            executor.execute(() -> {
                try {
                    for (int j = 0; j < 1000000; j++) {
                        count.getAndIncrement();
                    }
                } finally {
                    latch.countDown();
                }

            });
        }
        latch.await();
        long t2 = System.currentTimeMillis();
        System.out.println(String.format("结果:%s,耗时(ms):%s", count.get(), (t2 - t1)));
        executor.shutdown();
    }
}

输出:

结果:50000000,耗时(ms):1018
结果:50000000,耗时(ms):1442
结果:50000000,耗时(ms):1033
结果:50000000,耗时(ms):935
结果:50000000,耗时(ms):1320

方式3:LongAdder实现——相当于锁分段技术

先介绍一下LongAdder,说到LongAdder,不得不提的就是AtomicLong,AtomicLong是JDK1.5开始出现的,里面主要使用了一个long类型的value作为成员变量,然后使用循环的CAS操作去操作value的值,并发量比较大的情况下,CAS操作失败的概率较高,内部失败了会重试,导致耗时可能会增加。

LongAdder是JDK1.8开始出现的,所提供的API基本上可以替换掉原先的AtomicLong。LongAdder在并发量比较大的情况下,操作数据的时候,相当于把这个数字分成了很多份数字,然后交给多个人去管控,每个管控者负责保证部分数字在多线程情况下操作的正确性。当多线程访问的时,通过hash算法映射到具体管控者去操作数据,最后再汇总所有的管控者的数据,得到最终结果。相当于降低了并发情况下锁的粒度,所以效率比较高,看一下下面的图,方便理解:

image.png

示例:

代码中new LongAdder()创建一个LongAdder对象,内部数字初始值是0,调用increment()方法可以对LongAdder内部的值原子递增1。reset()方法可以重置LongAdder的值,使其归0。

public class LongAdderTest {
    private static LongAdder count = new LongAdder();

    public static void main(String[] args) throws InterruptedException {
        for (int i = 0; i < 5; i++) {
            count.reset();
            averageTest();
        }
    }

    public static void averageTest() throws InterruptedException {
        long t1 = System.currentTimeMillis();
        //自定义包含策略
        ThreadPoolExecutor executor = new ThreadPoolExecutor(50, 50, 60,
                TimeUnit.SECONDS, new LinkedBlockingQueue<>(5),
                new DemoThreadFactory("订单创建组"), new ThreadPoolExecutor.AbortPolicy());
        CountDownLatch latch = new CountDownLatch(50);
        for (int i = 0; i < 50; i++) {
            executor.execute(() -> {
                try {
                    for (int j = 0; j < 1000000; j++) {
                        count.increment();
                    }
                } finally {
                    latch.countDown();
                }

            });
        }
        latch.await();
        long t2 = System.currentTimeMillis();
        System.out.println(String.format("结果:%s,耗时(ms):%s", count.sum(), (t2 - t1)));
        executor.shutdown();
    }
}

输出:

结果:50000000,耗时(ms):209
结果:50000000,耗时(ms):133
结果:50000000,耗时(ms):149
结果:50000000,耗时(ms):146
结果:50000000,耗时(ms):148

方式4:LongAccumulator实现

LongAccumulator介绍

LongAccumulator是LongAdder的功能增强版。LongAdder的API只有对数值的加减,而LongAccumulator提供了自定义的函数操作,其构造函数如下:

/**
  * accumulatorFunction:需要执行的二元函数(接收2个long作为形参,并返回1个long)
  * identity:初始值
 **/
public LongAccumulator(LongBinaryOperator accumulatorFunction, long identity) {
    this.function = accumulatorFunction;
    base = this.identity = identity;
}

示例:

LongAccumulator的效率和LongAdder差不多,不过更灵活一些。

调用new LongAdder()等价于new LongAccumulator((x, y) -> x + y, 0L)

从上面4个示例的结果来看,LongAdder、LongAccumulator全面超越同步锁及AtomicLong的方式,建议在使用AtomicLong的地方可以直接替换为LongAdder、LongAccumulator吞吐量更高一些。

public class LongAccumulatorTest {
    private static volatile LongAccumulator count = new LongAccumulator((x, y) -> x + y, 0);

    public static void main(String[] args) throws InterruptedException {
        for (int i = 0; i < 5; i++) {
            count.reset();
            averageTest();
        }
    }

    public static void averageTest() throws InterruptedException {
        long t1 = System.currentTimeMillis();
        //自定义包含策略
        ThreadPoolExecutor executor = new ThreadPoolExecutor(50, 50, 60,
                TimeUnit.SECONDS, new LinkedBlockingQueue<>(5),
                new DemoThreadFactory("订单创建组"), new ThreadPoolExecutor.AbortPolicy());
        CountDownLatch latch = new CountDownLatch(50);
        for (int i = 0; i < 50; i++) {
            executor.execute(() -> {
                try {
                    for (int j = 0; j < 1000000; j++) {
                        count.accumulate(1);
                    }
                } finally {
                    latch.countDown();
                }

            });
        }
        latch.await();
        long t2 = System.currentTimeMillis();
        System.out.println(String.format("结果:%s,耗时(ms):%s", count.longValue(), (t2 - t1)));
        executor.shutdown();
    }
}

输出:

结果:50000000,耗时(ms):152
结果:50000000,耗时(ms):148
结果:50000000,耗时(ms):137
结果:50000000,耗时(ms):137
结果:50000000,耗时(ms):144
疑问:

Q:LongAccumulator.reset方法并不能重置重置LongAccumulator的identity:初始值正确,使其恢复原来的初始值。当初始值为0是不会发生这个问题,而当我们设置初始值如1时,就会导致后续的计算操作增加了5份初始值,目前猜测原因是因为代码中LongAccumulator在并发量比较大的情况下,操作数据的时候,相当于把这个数字分成了很多份数字 ,而初始化的时候也是初始化了多份数据,导致初始值叠加了多份。不知道这是个bug么?待解惑。

在此记录下来希望有遇到这种情况的同学注意。解决方法便是要么初始值identity=0不会有这种问题;或者有需要使用reset方法重置的改为重新创建个LongAccumulator处理。

源码:

public void reset() {
    Cell[] as = cells; Cell a;
    base = identity;
    if (as != null) {
        for (int i = 0; i < as.length; ++i) {
            if ((a = as[i]) != null)
                //对多个cell进行初始值赋值导致后面计算叠加了多份初始值
                a.value = identity;
        }
    }
}

示例:

public class LongAccumulatorTest {
    //设置初始值为1查看输出结果
    private static volatile LongAccumulator count = new LongAccumulator((x, y) -> x + y, 1);

    public static void main(String[] args) throws InterruptedException {
        for (int i = 0; i < 5; i++) {
            count.reset();
            averageTest();
        }
    }

    public static void averageTest() throws InterruptedException {
        long t1 = System.currentTimeMillis();
        //自定义包含策略
        ThreadPoolExecutor executor = new ThreadPoolExecutor(50, 50, 60,
                TimeUnit.SECONDS, new LinkedBlockingQueue<>(5),
                new DemoThreadFactory("订单创建组"), new ThreadPoolExecutor.AbortPolicy());
        CountDownLatch latch = new CountDownLatch(50);
        for (int i = 0; i < 50; i++) {
            executor.execute(() -> {
                try {
                    for (int j = 0; j < 1000000; j++) {
                        count.accumulate(1);
                    }
                } finally {
                    latch.countDown();
                }

            });
        }
        latch.await();
        long t2 = System.currentTimeMillis();
        System.out.println(String.format("结果:%s,耗时(ms):%s", count.longValue(), (t2 - t1)));
        executor.shutdown();
    }
}

输出:这时候你会发现只有第一次计算是正确的,只要使用了rest方法重置就会导致这个错误。

结果:50000001,耗时(ms):185
结果:50000005,耗时(ms):143
结果:50000005,耗时(ms):139
结果:50000005,耗时(ms):162
结果:50000005,耗时(ms):142

演示公平锁和非公平锁

先理解一下什么是公平锁、非公平锁?

公平锁和非公平锁体现在别人释放锁的一瞬间,如果前面已经有排队的,新来的是否可以插队,如果可以插队表示是非公平的,如果不可用插队,只能排在最后面,是公平的方式。

示例:

@Slf4j
public class ReentrantLockTest2 {

    public static void main(String[] args) throws InterruptedException {
        ReentrantLockTest2.LockTest(false);
        TimeUnit.SECONDS.sleep(4);
        log.error("-------------------------------");
        ReentrantLockTest2.LockTest(true);
    }

    public static void LockTest(boolean fair) throws InterruptedException {
        ReentrantLock lock = new ReentrantLock(fair);
        new Thread(() -> {
            lock.lock();
            try {
                log.error(Thread.currentThread().getName() + " start!");
                TimeUnit.SECONDS.sleep(3);
                new Thread(() -> {
                    //注意线程池要当前线程创建的才能使用,如果传给新开的线程会获取不到线程池
                    test("后到组",lock);
                }).start();
                //test(executorAfter,lock);
                log.error(Thread.currentThread().getName() + "end!");
            } catch (InterruptedException e) {
                e.printStackTrace();
            } finally {
                lock.unlock();
            }
        }, "Hold Lock 4 Test Thread").start();
        test("先到组",lock);
        TimeUnit.SECONDS.sleep(3);
    }

    private static void test(String name,Lock lock){
        //自定义包含策略
        ThreadPoolExecutor executor = new ThreadPoolExecutor(10, 10, 60,
                TimeUnit.SECONDS, new LinkedBlockingQueue<>(5),
                new DemoThreadFactory(name), new ThreadPoolExecutor.AbortPolicy());
        for (int i = 0; i < 10; i++) {
            executor.execute(() -> {
                lock.lock();
                try {
                    log.error("获取到锁!");
                } finally {
                    lock.unlock();
                }
            });
        }
        executor.shutdown();
    }
}

输出:

14:45:23.204 [Hold Lock 4 Test Thread] ERROR com.self.current.ReentrantLockTest2 - Hold Lock 4 Test Thread start!
14:45:26.211 [Hold Lock 4 Test Thread] ERROR com.self.current.ReentrantLockTest2 - Hold Lock 4 Test Threadend!
14:45:26.211 [From DemoThreadFactory's 先到组-Worker-1] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.211 [From DemoThreadFactory's 先到组-Worker-2] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.212 [From DemoThreadFactory's 先到组-Worker-3] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.212 [From DemoThreadFactory's 先到组-Worker-4] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.212 [From DemoThreadFactory's 先到组-Worker-5] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.212 [From DemoThreadFactory's 先到组-Worker-6] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.212 [From DemoThreadFactory's 先到组-Worker-7] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.212 [From DemoThreadFactory's 先到组-Worker-8] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.212 [From DemoThreadFactory's 后到组-Worker-4] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.212 [From DemoThreadFactory's 先到组-Worker-9] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.213 [From DemoThreadFactory's 后到组-Worker-8] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.218 [From DemoThreadFactory's 后到组-Worker-10] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.218 [From DemoThreadFactory's 先到组-Worker-10] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.218 [From DemoThreadFactory's 后到组-Worker-2] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.218 [From DemoThreadFactory's 后到组-Worker-1] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.219 [From DemoThreadFactory's 后到组-Worker-3] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.219 [From DemoThreadFactory's 后到组-Worker-5] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.219 [From DemoThreadFactory's 后到组-Worker-6] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.219 [From DemoThreadFactory's 后到组-Worker-7] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:26.219 [From DemoThreadFactory's 后到组-Worker-9] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:30.205 [main] ERROR com.self.current.ReentrantLockTest2 - -------------------------------
14:45:30.205 [Hold Lock 4 Test Thread] ERROR com.self.current.ReentrantLockTest2 - Hold Lock 4 Test Thread start!
14:45:33.206 [Hold Lock 4 Test Thread] ERROR com.self.current.ReentrantLockTest2 - Hold Lock 4 Test Threadend!
14:45:33.206 [From DemoThreadFactory's 先到组-Worker-1] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.206 [From DemoThreadFactory's 先到组-Worker-2] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.209 [From DemoThreadFactory's 先到组-Worker-3] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.209 [From DemoThreadFactory's 先到组-Worker-4] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.209 [From DemoThreadFactory's 先到组-Worker-5] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.209 [From DemoThreadFactory's 先到组-Worker-6] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.210 [From DemoThreadFactory's 先到组-Worker-7] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.210 [From DemoThreadFactory's 先到组-Worker-8] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.210 [From DemoThreadFactory's 先到组-Worker-9] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.210 [From DemoThreadFactory's 先到组-Worker-10] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.210 [From DemoThreadFactory's 后到组-Worker-2] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.210 [From DemoThreadFactory's 后到组-Worker-1] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.211 [From DemoThreadFactory's 后到组-Worker-6] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.211 [From DemoThreadFactory's 后到组-Worker-7] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.211 [From DemoThreadFactory's 后到组-Worker-5] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.211 [From DemoThreadFactory's 后到组-Worker-4] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.211 [From DemoThreadFactory's 后到组-Worker-3] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.211 [From DemoThreadFactory's 后到组-Worker-9] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.212 [From DemoThreadFactory's 后到组-Worker-10] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!
14:45:33.212 [From DemoThreadFactory's 后到组-Worker-8] ERROR com.self.current.ReentrantLockTest2 - 获取到锁!

google提供的一些好用的并发工具类

关于并发方面的,juc已帮我们提供了很多好用的工具,而谷歌在此基础上做了扩展,使并发编程更容易,这些工具放在guava.jar包中。

guava maven配置


    com.google.guava
    guava
    27.0-jre

guava中常用几个类

MoreExecutors:提供了一些静态方法,是对juc中的Executors类的一个扩展。
Futures:也提供了很多静态方法,是对juc中Future的一个扩展。

案例1:异步执行任务完毕之后回调——相当于CompletableFuture的whenComplete方法

ListeningExecutorService接口继承于juc中的ExecutorService接口,对ExecutorService做了一些扩展,看其名字中带有Listening,说明这个接口自带监听的功能,可以监听异步执行任务的结果。通过MoreExecutors.listeningDecorator创建一个ListeningExecutorService对象,需传递一个ExecutorService参数,传递的ExecutorService负责异步执行任务。

ListeningExecutorServicesubmit方法用来异步执行一个任务,返回ListenableFutureListenableFuture接口继承于juc中的Future接口,对Future做了扩展,使其带有监听的功能。调用submit.addListener可以在执行的任务上添加监听器,当任务执行完毕之后会回调这个监听器中的方法。

ListenableFutureget方法会阻塞当前线程直到任务执行完毕

另一种回调方式是通过调用Futures的静态方法addCallback在异步执行的任务中添加回调,回调的对象是一个FutureCallback,此对象有2个方法,任务执行成功调用onSuccess,执行失败调用onFailure

失败的情况可以将代码中int i = 10 / 0;注释去掉,执行一下可以看看效果。

示例:

@Slf4j
public class GuavaTest {

    //相当于CompletableFuture的whenComplete方法
    public static void main1(String[] args) throws ExecutionException, InterruptedException {
        //创建一个线程池
        ExecutorService delegate = Executors.newFixedThreadPool(5);
        try {
            ListeningExecutorService executorService = MoreExecutors.listeningDecorator(delegate);
            //异步执行一个任务
            ListenableFuture submit = executorService.submit(() -> {
                log.error("{}", System.currentTimeMillis());
                //休眠2秒,默认耗时
                TimeUnit.SECONDS.sleep(2);
                log.error("{}", System.currentTimeMillis());
                return 10;
            });
            //当任务执行完毕之后回调对应的方法
            submit.addListener(() -> {
                log.error("任务执行完毕了,我被回调了");
            }, MoreExecutors.directExecutor());
            log.error("{}", submit.get());
        } finally {
            delegate.shutdown();
        }
    }

    //相当于CompletableFuture的whenComplete方法
    public static void main(String[] args) throws ExecutionException, InterruptedException {
        ThreadPoolExecutor executor = new ThreadPoolExecutor(5, 10, 60,
                TimeUnit.SECONDS, new LinkedBlockingQueue<>(10),
                new DemoThreadFactory("订单创建组"), new ThreadPoolExecutor.AbortPolicy());


        ListeningExecutorService service = MoreExecutors.listeningDecorator(executor);
        try {
            ListenableFuture future = service.submit(() -> {
                log.error("{}", System.currentTimeMillis());
                //休眠2秒,默认耗时
                TimeUnit.SECONDS.sleep(2);
                //int i = 10 / 0;
                log.error("{}", System.currentTimeMillis());
                return 10;
            });
            Futures.addCallback(future, new FutureCallback() {
                @Override
                public void onSuccess(Integer integer) {
                    log.error("执行成功:{}", integer);
                }

                @Override
                public void onFailure(Throwable throwable) {
                    log.error("执行失败:{}", throwable.getMessage());
                }
            });
            log.error("{}", future.get());
        } finally {
            service.shutdown();
        }

    }
}

输出:

15:32:54.480 [From DemoThreadFactory's 订单创建组-Worker-1] ERROR com.self.current.GuavaTest - 1599809574477
15:32:56.487 [From DemoThreadFactory's 订单创建组-Worker-1] ERROR com.self.current.GuavaTest - 1599809576487
15:32:56.488 [main] ERROR com.self.current.GuavaTest - 10
15:32:56.488 [From DemoThreadFactory's 订单创建组-Worker-1] ERROR com.self.current.GuavaTest - 执行成功:10

示例2:获取一批异步任务的执行结果——Futures.allAsList(futureList).get()

结果中按顺序输出了6个异步任务的结果,此处用到了Futures.allAsList方法,看一下此方法的声明:

public static  ListenableFuture> allAsList(
      Iterable> futures)

传递一批ListenableFuture,返回一个ListenableFuture>,内部将一批结果转换为了一个ListenableFuture对象。

示例:

public static void main(String[] args) throws ExecutionException, InterruptedException {
    log.error("star");
    ExecutorService delegate = Executors.newFixedThreadPool(5);
    try {
        ListeningExecutorService executorService = MoreExecutors.listeningDecorator(delegate);
        List> futureList = new ArrayList<>();
        for (int i = 5; i >= 0; i--) {
            int j = i;
            futureList.add(executorService.submit(() -> {
                TimeUnit.SECONDS.sleep(j);
                return j;
            }));
        }
        //把多个ListenableFuture转换为一个ListenableFuture
        //ListenableFuture> listListenableFuture = Futures.allAsList(futureList);
        //获取一批任务的执行结果
        List resultList = Futures.allAsList(futureList).get();
        //输出
        resultList.forEach(item -> {
            log.error("{}", item);
        });
    } finally {
        delegate.shutdown();
    }
}

输出:

15:45:51.160 [main] ERROR com.self.current.GuavaTest - star
15:45:56.185 [main] ERROR com.self.current.GuavaTest - 5
15:45:56.185 [main] ERROR com.self.current.GuavaTest - 4
15:45:56.185 [main] ERROR com.self.current.GuavaTest - 3
15:45:56.185 [main] ERROR com.self.current.GuavaTest - 2
15:45:56.185 [main] ERROR com.self.current.GuavaTest - 1
15:45:56.185 [main] ERROR com.self.current.GuavaTest - 0

示例3:一批任务异步执行完毕之后回调——包装futureList传递给Futures.addCallback 方法

异步执行一批任务,最后计算其和,代码中异步执行了一批任务,所有任务完成之后,回调了上面的onSuccess方法,内部对所有的结果进行sum操作。

示例:

public static void main(String[] args) throws ExecutionException, InterruptedException {
    log.error("start");
    ExecutorService delegate = Executors.newFixedThreadPool(5);
    try {
        ListeningExecutorService executorService = MoreExecutors.listeningDecorator(delegate);
        List> futureList = new ArrayList<>();
        for (int i = 5; i >= 0; i--) {
            int j = i;
            futureList.add(executorService.submit(() -> {
                TimeUnit.SECONDS.sleep(j);
                return j;
            }));
        }
        //把多个ListenableFuture转换为一个ListenableFuture
        ListenableFuture> listListenableFuture = Futures.allAsList(futureList);
        Futures.addCallback(listListenableFuture, new FutureCallback>() {
            @Override
            public void onSuccess(List result) {
              log.error("result中所有结果之和:"+result.stream().reduce(Integer::sum).get());
            }

            @Override
            public void onFailure(Throwable throwable) {
                log.error("执行任务发生异常:" + throwable.getMessage(), throwable);
            }
        });
    } finally {
        delegate.shutdown();
    }
}

输出:

15:57:00.539 [main] ERROR com.self.current.GuavaTest - start
15:57:05.560 [pool-2-thread-1] ERROR com.self.current.GuavaTest - result中所有结果之和:15
其他疑问:

Q:运行下面这个例子结束不了,debug倒是可以,这是为什么呢?Thread[Monitor Ctrl-Break,5,main]是哪来的?

public class VolatileTest1 {

    public static volatile int num = 0;

    public  static void add(){
        num++;
    }

    public static void main(String[] args) throws InterruptedException {
        Thread[] threads = new Thread[10];
        for (Thread thread : threads) {
            thread = new Thread(()->{
                for (int i = 0; i < 1000; i++) {
                    VolatileTest1.add();
                }
            });
            thread.start();
            thread.join();
        }
        //2
        //java.lang.ThreadGroup[name=main,maxpri=10]
        //    Thread[main,5,main]
        //    Thread[Monitor Ctrl-Break,5,main]
        //结束不了,debug倒是可以,这是为什么呢?Thread[Monitor Ctrl-Break,5,main]是哪来的?
        while (Thread.activeCount() >1){
            Thread.yield();
            System.out.println(Thread.activeCount());
            ThreadGroup parent = Thread.currentThread().getThreadGroup();
            parent.list();
        }
        System.out.println("num="+num);
    }
}

其他

AQS原理没讲,需要找资料补充。

JUC中常见的集合原来没讲,比如ConcurrentHashMap最常用的,后面的都很泛,没有深入,虎头蛇尾。

阻塞队列讲得不够深入。

参考

java高并发系列

liaoxuefeng Java教程 CompletableFuture

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