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线程有序化神器CompletionService

java water 155℃ 0评论

话说有一天,产品经理突然找到正在摸鱼的你。 产品:『我们要加一个聚合搜索功能,当用户在我们网站查询一件商品时,我们分别从 A、B、C 三个网站上查询这个信息,然后再把得到的结果返回给用户』 你:『哦,就是写个爬虫,从 3 个网站上抓取数据是吧?』 产品:『呸,爬虫是犯法的,这叫数据分析,怎么样,能实现吧?』 你:『可以』 产品:『好的,明天上线』 你:『。。。』

Code 1.0

你很快完成了开发,代码如下:

/*
 *
 *  * *
 *  *  * blog.coder4j.cn
 *  *  * Copyright (C) B0A6-B0B0 All Rights Reserved.
 *  *
 *
 */
package cn.coder4j.study.example.thread;

import cn.hutool.core.thread.ThreadUtil;
import com.google.common.collect.Lists;

import java.util.List;

/**
 * @author buhao
 * @version TestCompletionService.java, v 0.A B0B0-0B-A8 A9:0C buhao
 */
public class TestCompletionService {

    public static void main(String[] args) {
        // 查询信息
        String queryName = "java";
        // 调用查询接口
        long startTime = System.currentTimeMillis();
        List<String> result = queryInfoCode1(queryName);
        System.out.println("耗时: " + (System.currentTimeMillis() - startTime));
        System.out.println(result);
    }

    /**
     * 聚合查询信息 code 1
     *
     * @param queryName
     * @return
     */
    private static List<String> queryInfoCode1(String queryName) {
        List<String> resultList = Lists.newArrayList();

        String webA = searchWebA(queryName);
        resultList.add(webA);

        String webB = searchWebB(queryName);
        resultList.add(webB);

        String webC = searchWebC(queryName);
        resultList.add(webC);

        return resultList;
    }

    /**
     * 查询网站 A
     *
     * @param name
     * @return
     */
    public static String searchWebA(String name) {
        ThreadUtil.sleep(5000);
        return "webA";
    }

    /**
     * 查询网站B
     *
     * @param name
     * @return
     */
    public static String searchWebB(String name) {
        ThreadUtil.sleep(3000);
        return "webB";
    }

    /**
     * 查询网站C
     *
     * @param name
     * @return
     */
    public static String searchWebC(String name) {
        ThreadUtil.sleep(500);
        return "webC";
    }
}

你运行了一下代码,结果如下:

耗时: 8512
[webA, webB, webC]

我去,怎么请求一下要8秒多?上线了,产品还不砍死我。

debug 了一下代码,发现问题出在了请求的网站上:

    /**
     * 查询网站 A
     *
     * @param name
     * @return
     */
    public static String searchWebA(String name) {
        ThreadUtil.sleep(5000);
        return "webA";
    }

    /**
     * 查询网站B
     *
     * @param name
     * @return
     */
    public static String searchWebB(String name) {
        ThreadUtil.sleep(3000);
        return "webB";
    }

    /**
     * 查询网站C
     *
     * @param name
     * @return
     */
    public static String searchWebC(String name) {
        ThreadUtil.sleep(500);
        return "webC";
    }

网站 A、网站 B 因为年久失修,没人维护,接口响应很慢,平均响应时间一个是 5秒,一个是 3秒(这里使用 sleep 模拟)。网站 C 性能还可以,平均响应时间 0.5 秒。而我们程序的执行时间就是 网站A 响应时间 + 网站 B 响应时间 + 网站 C 响应时间。

Code 2.0

好了,问题知道了,因为请求的网站太慢了,那么如何解决呢?总不能打电话找他们把网站优化一下让我爬吧。书上教导我们要先从自己身上找问题。先看看自己代码哪里可以优化。

一分析代码发现,我们的代码全是串行化, A 网站请求完,再请求 B 网站,B 网站请求完再请求 C 网站。突然想到提高效率的第一要义,提高代码的并行率。为什么要一个一个串行请求,而不是 A、B、C 三个网站一起请求呢,Java 的多线程很轻松就可以实现,代码如下:

/*
 *
 *  * *
 *  *  * blog.coder4j.cn
 *  *  * Copyright (C) B0A6-B0B0 All Rights Reserved.
 *  *
 *
 */
package cn.coder4j.study.example.thread;

import cn.hutool.core.thread.ThreadUtil;
import com.google.common.collect.Lists;

import java.util.List;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;

/**
 * @author buhao
 * @version TestCompletionService.java, v 0.A B0B0-0B-A8 A9:0C buhao
 */
public class TestCompletionService {

    public static void main(String[] args) throws ExecutionException, InterruptedException {
        // 查询信息
        String queryName = "java";
        // 调用查询接口
        long startTime = System.currentTimeMillis();
        List<String> result = queryInfoCode2(queryName);
        System.out.println("耗时: " + (System.currentTimeMillis() - startTime));
        System.out.println(result);
    }

    /**
     * 聚合查询信息 code 1
     *
     * @param queryName
     * @return
     */
    private static List<String> queryInfoCode1(String queryName) {
        List<String> resultList = Lists.newArrayList();

        String webA = searchWebA(queryName);
        resultList.add(webA);

        String webB = searchWebB(queryName);
        resultList.add(webB);

        String webC = searchWebC(queryName);
        resultList.add(webC);

        return resultList;
    }

    /**
     * 聚合查询信息 code 2
     *
     * @param queryName
     * @return
     */
    private static List<String> queryInfoCode2(String queryName) throws ExecutionException, InterruptedException {
        List<String> resultList = Lists.newArrayList();

        // 创建3个线程的线程池
        ExecutorService pool = Executors.newFixedThreadPool(3);

        try {
            // 创建任务的 feature
            Future<String> webAFuture = pool.submit(() -> searchWebA(queryName));
            Future<String> webBFuture = pool.submit(() -> searchWebB(queryName));
            Future<String> webCFuture = pool.submit(() -> searchWebC(queryName));
            // 得到任务结果
            resultList.add(webAFuture.get());
            resultList.add(webBFuture.get());
            resultList.add(webCFuture.get());
        } finally {
            // 关闭线程池
            pool.shutdown();
        }
        
        return resultList;
    }

    /**
     * 查询网站 A
     *
     * @param name
     * @return
     */
    public static String searchWebA(String name) {
        ThreadUtil.sleep(5000);
        return "webA";
    }

    /**
     * 查询网站B
     *
     * @param name
     * @return
     */
    public static String searchWebB(String name) {
        ThreadUtil.sleep(3000);
        return "webB";
    }

    /**
     * 查询网站C
     *
     * @param name
     * @return
     */
    public static String searchWebC(String name) {
        ThreadUtil.sleep(500);
        return "webC";
    }
}

这里的重点代码如下:

    /**
     * 聚合查询信息 code 2
     *
     * @param queryName
     * @return
     */
    private static List<String> queryInfoCode2(String queryName) throws ExecutionException, InterruptedException {
        List<String> resultList = Lists.newArrayList();

        // 创建3个线程的线程池
        ExecutorService pool = Executors.newFixedThreadPool(3);

        try {
            // 创建任务的 feature
            Future<String> webAFuture = pool.submit(() -> searchWebA(queryName));
            Future<String> webBFuture = pool.submit(() -> searchWebB(queryName));
            Future<String> webCFuture = pool.submit(() -> searchWebC(queryName));
            // 得到任务结果
            resultList.add(webAFuture.get());
            resultList.add(webBFuture.get());
            resultList.add(webCFuture.get());
        } finally {
            // 关闭线程池
            pool.shutdown();
        }
        
        return resultList;
    }

请求网站的代码其实一行没变,变的是我们调用请求方法的地方,把之前串行的代码,变成了多线程的形式,而且还不是普通的多线程的形式,因为我们要在主线程获得线程的结果,所以还要使用 Future 的形式。

好的运行一下代码,看看效果,结果如下:

耗时: 5058
[webA, webB, webC]

嗯,效果明显,从 8 秒多下降到了 5 秒多,但是还是很长,没法接受的长。做为一个有追求的程序员,还要去优化。我们分析一下,刚开始代码是串行的,流程如下,总请求时间是三次请求的总时长。

然后我们优化了一下,把串行请求给并行化,流程如下:

因为是并行化,类似木桶效应,决定最长时间的因素,是你请求中最耗时的的那个操作,这里是时间为 5 秒的请求 A 网站操作。

Code 3.0

其实分析到这里,在不能优化 AB 网站的请求时间的前提下,已经很难优化了。但是方法总比困难多,我们的确没办法再去压缩总请求时间,但是可以让用户体验更好一点,这里需要引入两个技术一个是 Websocket,一个是 **CompletionService。**其中websocket 可以简单的理解成服务端推送技术,就是不需要客户端主动请求,而是通过服务端主动推送消息(ws 在本文中不是重点,会一笔带过。

 *
 *  * *
 *  *  * blog.coder4j.cn
 *  *  * Copyright (C) B0A6-B0B0 All Rights Reserved.
 *  *
 *
 */
package cn.coder4j.study.example.thread;

import cn.hutool.core.thread.ThreadUtil;
import com.google.common.collect.Lists;

import java.util.List;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.ExecutorCompletionService;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;

/**
 * @author buhao
 * @version TestCompletionService.java, v 0.A B0B0-0B-A8 A9:0C buhao
 */
public class TestCompletionService {

    public static void main(String[] args) throws ExecutionException, InterruptedException {
        // 查询信息
        String queryName = "java";
        // 调用查询接口
        long startTime = System.currentTimeMillis();
        queryInfoCode3(queryName);
        System.out.println("耗时: " + (System.currentTimeMillis() - startTime));
    }

    /**
     * 聚合查询信息 code 1
     *
     * @param queryName
     * @return
     */
    private static List<String> queryInfoCode1(String queryName) {
        List<String> resultList = Lists.newArrayList();

        String webA = searchWebA(queryName);
        resultList.add(webA);

        String webB = searchWebB(queryName);
        resultList.add(webB);

        String webC = searchWebC(queryName);
        resultList.add(webC);

        return resultList;
    }

    /**
     * 聚合查询信息 code 2
     *
     * @param queryName
     * @return
     */
    private static List<String> queryInfoCode2(String queryName) throws ExecutionException, InterruptedException {
        List<String> resultList = Lists.newArrayList();

        // 创建3个线程的线程池
        ExecutorService pool = Executors.newFixedThreadPool(3);

        try {
            // 创建任务的 feature
            Future<String> webAFuture = pool.submit(() -> searchWebA(queryName));
            Future<String> webBFuture = pool.submit(() -> searchWebB(queryName));
            Future<String> webCFuture = pool.submit(() -> searchWebC(queryName));
            // 得到任务结果
            resultList.add(webAFuture.get());
            resultList.add(webBFuture.get());
            resultList.add(webCFuture.get());
        } finally {
            // 关闭线程池
            pool.shutdown();
        }

        return resultList;
    }

    /**
     * 聚合查询信息 code 3
     *
     * @param queryName
     * @return
     */
    private static void queryInfoCode3(String queryName) throws ExecutionException, InterruptedException {
        // 开始时间
        long startTime = System.currentTimeMillis();
        // 创建 CompletionService
        ExecutorCompletionService executorCompletionService = new ExecutorCompletionService(Executors.newFixedThreadPool(3));

        // 创建任务的 feature
        executorCompletionService.submit(() -> searchWebA(queryName));
        executorCompletionService.submit(() -> searchWebB(queryName));
        executorCompletionService.submit(() -> searchWebC(queryName));

        for (int i = 0; i < 3; i++) {
            Future take = executorCompletionService.take();
            System.out.println("获得请求结果 -> " + take.get());
            System.out.println("通过 ws 推送给客户端,总共耗时" + (System.currentTimeMillis() - startTime));
        }
    }

    /**
     * 查询网站 A
     *
     * @param name
     * @return
     */
    public static String searchWebA(String name) {
        ThreadUtil.sleep(5000);
        return "webA";
    }

    /**
     * 查询网站B
     *
     * @param name
     * @return
     */
    public static String searchWebB(String name) {
        ThreadUtil.sleep(3000);
        return "webB";
    }

    /**
     * 查询网站C
     *
     * @param name
     * @return
     */
    public static String searchWebC(String name) {
        ThreadUtil.sleep(500);
        return "webC";
    }
}

核心代码如下:

    /**
     * 聚合查询信息 code 3
     *
     * @param queryName
     * @return
     */
    private static void queryInfoCode3(String queryName) throws ExecutionException, InterruptedException {
        // 开始时间
        long startTime = System.currentTimeMillis();
        // 创建 CompletionService
        ExecutorCompletionService executorCompletionService = new ExecutorCompletionService(Executors.newFixedThreadPool(3));

        // 创建任务的 feature
        executorCompletionService.submit(() -> searchWebA(queryName));
        executorCompletionService.submit(() -> searchWebB(queryName));
        executorCompletionService.submit(() -> searchWebC(queryName));

        for (int i = 0; i < 3; i++) {
            Future take = executorCompletionService.take();
            System.out.println("获得请求结果 -> " + take.get());
            System.out.println("通过 ws 推送给客户端,总共耗时" + (System.currentTimeMillis() - startTime));
        }
    }

先看执行结果:

获得请求结果 -> webC
通过 ws 推送给客户端,总共耗时561
获得请求结果 -> webB
通过 ws 推送给客户端,总共耗时3055
获得请求结果 -> webA
通过 ws 推送给客户端,总共耗时5060
耗时: 5060

我们来分析一下执行结果,首先总耗时时间还是 5 秒多没变,但是我们不是等全部执行完再推送给客户端,而是执行完一个就推送一个,并且发现了一个规律,最先推送的是请求最快的,然后是第二快的,最后推最慢的那一个。也就是说推送结果是有序的。给用户的体验就是点击按钮后,1秒内会展示网站 C 的数据,然后过了2秒又在原有基础上又添加展示了网站 B 数据,又过了2秒,又增加展示了网站 A数据。这种体验要比用户一直白屏 5 秒,然后一下返回所有数据要好的多。

是不是很神奇,这背后的功臣就是 CompletionService,他的源码如下:

package java.util.concurrent;

/**
 * A service that decouples the production of new asynchronous tasks
 * from the consumption of the results of completed tasks.  Producers
 * {@code submit} tasks for execution. Consumers {@code take}
 * completed tasks and process their results in the order they
 * complete.  A {@code CompletionService} can for example be used to
 * manage asynchronous I/O, in which tasks that perform reads are
 * submitted in one part of a program or system, and then acted upon
 * in a different part of the program when the reads complete,
 * possibly in a different order than they were requested.
 *
 * <p>Typically, a {@code CompletionService} relies on a separate
 * {@link Executor} to actually execute the tasks, in which case the
 * {@code CompletionService} only manages an internal completion
 * queue. The {@link ExecutorCompletionService} class provides an
 * implementation of this approach.
 *
 * <p>Memory consistency effects: Actions in a thread prior to
 * submitting a task to a {@code CompletionService}
 * <a href="package-summary.html#MemoryVisibility"><i>happen-before</i></a>
 * actions taken by that task, which in turn <i>happen-before</i>
 * actions following a successful return from the corresponding {@code take()}.
 */
public interface CompletionService<V> {
    /**
     * Submits a value-returning task for execution and returns a Future
     * representing the pending results of the task.  Upon completion,
     * this task may be taken or polled.
     *
     * @param task the task to submit
     * @return a Future representing pending completion of the task
     * @throws RejectedExecutionException if the task cannot be
     *         scheduled for execution
     * @throws NullPointerException if the task is null
     */
    Future<V> submit(Callable<V> task);

    /**
     * Submits a Runnable task for execution and returns a Future
     * representing that task.  Upon completion, this task may be
     * taken or polled.
     *
     * @param task the task to submit
     * @param result the result to return upon successful completion
     * @return a Future representing pending completion of the task,
     *         and whose {@code get()} method will return the given
     *         result value upon completion
     * @throws RejectedExecutionException if the task cannot be
     *         scheduled for execution
     * @throws NullPointerException if the task is null
     */
    Future<V> submit(Runnable task, V result);

    /**
     * Retrieves and removes the Future representing the next
     * completed task, waiting if none are yet present.
     *
     * @return the Future representing the next completed task
     * @throws InterruptedException if interrupted while waiting
     */
    Future<V> take() throws InterruptedException;

    /**
     * Retrieves and removes the Future representing the next
     * completed task, or {@code null} if none are present.
     *
     * @return the Future representing the next completed task, or
     *         {@code null} if none are present
     */
    Future<V> poll();

    /**
     * Retrieves and removes the Future representing the next
     * completed task, waiting if necessary up to the specified wait
     * time if none are yet present.
     *
     * @param timeout how long to wait before giving up, in units of
     *        {@code unit}
     * @param unit a {@code TimeUnit} determining how to interpret the
     *        {@code timeout} parameter
     * @return the Future representing the next completed task or
     *         {@code null} if the specified waiting time elapses
     *         before one is present
     * @throws InterruptedException if interrupted while waiting
     */
    Future<V> poll(long timeout, TimeUnit unit) throws InterruptedException;
}

可以看到 CompletionService 方法,分别如下:

  1. Futuresubmit(Callabletask);

submit 用于提交一个 Callable 对象,用于提交一个可以获得结果的线程任务

  1. Futuresubmit(Runnable task, V result);

submit 用于提交一个 Runnable 对象及 result 对象,类似于上面的 submit,但是 runnable 的返回值 void 无法获得线程的结果,所以添加了 result 用于做为参数的桥梁

  1. Futuretake() throws InterruptedException;

take 用于取出最新的线程执行结果,注意这里是阻塞的

  1. Futurepoll();

take 用于取出最新的线程执行结果,是非阻塞的,如果没有结果就返回 null

  1. Futurepoll(long timeout, TimeUnit unit) throws InterruptedException;

同上,只是加了一个超时时间

另外,CompletionService 是接口,无法直接使用,通常使用他的实现类 ExecutorCompletionService,具体使用方法如上面的 demo。

可能看到这里会很好奇 ExecutorCompletionService 实现原理,其实原理很简单,他在内部维护了一个阻塞队列,提交的任务,先执行完的先进入队列,所以你通过 poll 或 take 获得的肯定是最先执行完的任务结果。

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