Java自定义线程池的实现示例

目录

• 一、Java语言本身也是多线程，回顾Java创建线程方式如下：
• 二、JDK线程池工具类.
• 三、业界知名自定义线程池扩展使用.

一、Java语言本身也是多线程，回顾Java创建线程方式如下：

1、继承Thread类,(Thread类实现Runnable接口)，来个类图加深印象。

2、实现Runnable接口实现无返回值、实现run()方法，啥时候run，黑话了。

3、实现Callable接口重写call()+FutureTask获取.

public class CustomThread {
    public static void main(String[] args) {
        // 自定义线程
        new Thread(new Runnable() {
            @Override
            public void run() {
                System.out.println("Custom Run");
                System.out.println(Thread.currentThread().getName());
            }
        },"custom-thread-1").start();
    }
}

4、基于线程池集中管理创建线程系列周期.【本篇文章重点介绍】

二、JDK线程池工具类.

1、Executors工具类，是JDK中Doug Lea大佬实现供开发者使用。

随着JDK版本迭代逐渐加入了基于工作窃取算法的线程池了，阿里编码规范也推荐开发者自定义线程池，禁止生产直接使用Executos线程池工具类，因此很有可能造成OOM异常。同时在某些类型的线程池里面，使用无界队列还会导致maxinumPoolSize、keepAliveTime、handler等参数失效。因此目前在大厂的开发规范中会强调禁止使用Executors来创建线程池。这里说道阻塞队列。LinkedBlockingQueue。

2、自定义线程池工具类基于ThreadPoolExecutor实现，那个JDK封装的线程池工具类也是基于这个ThreadPoolExecutor实现的。

public class ConstomThreadPool extends ThreadPoolExecutor{
    /**
     *
     * @param corePoolSize 核心线程池
     * @param maximumPoolSize 线程池最大数量
     * @param keepAliveTime 线程存活时间
     * @param unit TimeUnit
     * @param workQueue 工作队列,自定义大小
     * @param poolName 线程工厂自定义线程名称
     */
    public ConstomThreadPool(int corePoolSize, int maximumPoolSize, long keepAliveTime, TimeUnit unit, BlockingQueue<Runnable> workQueue, String poolName) {
        super(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue);
        setThreadFactory(new CustomThreadFactory(poolName, false));
    }
}

自定义线程工厂类,这样线程命名有开发者控制实现了,这样参数可以做到可配置化，生产环境可以供不同业务模块使用，如果系统配置值不生效，就给一个默认值，更加满足业务需要.

/**
 * 自定义线程工厂
 */
public class CustomThreadFactory implements ThreadFactory {
    /**
     * 线程前缀,采用AtomicInteger实现线程编号线程安全自增
     */
    private final AtomicInteger atomicInteger = new AtomicInteger(1);
    /**
     * 线程命名前缀
     */
    private final String namePrefix;
    /**
     * 线程工厂创建的线程是否是守护线程
     */
    private final boolean isDaemon;

    public CustomThreadFactory(String prefix, boolean daemin) {
        if (StringUtils.isNoneBlank(prefix)) {
            this.namePrefix = prefix;
        } else {
            this.namePrefix = "thread_pool";
        }
        // 是否是守护线程
        isDaemon = daemin;
    }

    @Override
    public Thread newThread(Runnable r) {
        Thread thread = new Thread(r, namePrefix + "-" + atomicInteger.getAndIncrement());
        thread.setDaemon(isDaemon);
        // 设置线程优先级
        if (thread.getPriority() != Thread.NORM_PRIORITY) {
            thread.setPriority(Thread.NORM_PRIORITY);
        }
        return thread;
    }
}

这里Spring框架提供的自定义线程池工厂类，当然了一些开源包也会提供这样的轮子，这个比较简单了.

@SuppressWarnings("serial")
public class CustomizableThreadFactory extends CustomizableThreadCreator implements ThreadFactory {

	/**
	 * Create a new CustomizableThreadFactory with default thread name prefix.
	 */
	public CustomizableThreadFactory() {
		super();
	}

	/**
	 * Create a new CustomizableThreadFactory with the given thread name prefix.
	 * @param threadNamePrefix the prefix to use for the names of newly created threads
	 */
	public CustomizableThreadFactory(String threadNamePrefix) {
		super(threadNamePrefix);
	}

	@Override
	public Thread newThread(Runnable runnable) {
		return createThread(runnable);
	}

}

3、SpringBoot框架提供的自定义线程池,基于异步注解@Async名称和一些业务自定义配置项,很好的实现了业务间线程池的隔离。

@Configuration
public class ThreadPoolConfig {
    /**
     *
     * @return ThreadPoolTaskExecutor
     */
    @Bean("serviceTaskA")
    public ThreadPoolTaskExecutor serviceTaskA() {
        ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
        executor.setCorePoolSize(2);
        executor.setMaxPoolSize(2);
        executor.setQueueCapacity(10);
        executor.setKeepAliveSeconds(60);
        executor.setThreadNamePrefix("service-a");
        executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
        return executor;
    }

    /**
     *
     * @return ThreadPoolTaskExecutor
     */
    @Bean("serviceTaskB")
    public ThreadPoolTaskExecutor serviceTaskB() {
        ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
        executor.setCorePoolSize(2);
        executor.setMaxPoolSize(2);
        executor.setQueueCapacity(10);
        executor.setKeepAliveSeconds(60);
        executor.setThreadNamePrefix("service-b");
        executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
        return executor;
    }
}

整体来看是Spring框架对JDK的线程池做了封装，公开发者使用，毕竟框架嘛，肯定是把方便留给开发者。

4、并发流线程池。

        List<String> list = new ArrayList<>(4);
        list.add("A");
        list.add("B");
        list.add("C");
        list.add("D");
        list.parallelStream().forEach(string -> {
            string = string + "paralleStream";
            System.out.println(Thread.currentThread().getName()+":-> "+string);
        });

运行实例：

说明：并发流默认使用系统公共的线程池ForkJoinWorkerThread，供整个程序使用。

类图如下，基于分治法，双端窃取算法实现的一种线程池。

ForkJoin实现的了自己的线程工厂命名。

也可以自定义并发流线程，然后提交任务，一般并发流适用于短暂耗时业务，避免拖垮整个线程池业务.

5、实现一个基于系统公用线程池工具类，运行这个系统中的异步业务.

public final class CustomExecutors  {
    /**
     * 核心线程数大小
     */
    private static final int CORE_POOL_SIZE=5;
    /**
     * 核心线程池大小
     */
    private static final int MAX_POOL_SIZE=10;
    /**
     * 线程存活时间
     */
    private static final int KEEP_ALIVE_TIME=60;
    /**
     * 工作队列大小
     */
    private static final LinkedBlockingQueue queue=new LinkedBlockingQueue(100);
    /**
     * 自定义线程池名前缀
     */
    private static final String POOL_PREFIX_NAME="Custom-Common-Pool";

    private CustomExecutors(){
        //throw new XXXXException("un support create pool!");
    }

    private static ConstomThreadPool constomThreadPool;

    /**
     * 静态块初始化只执行一次,不关闭,整个系统公用一个线程池
     */
    static {
        constomThreadPool=new ConstomThreadPool(CORE_POOL_SIZE,MAX_POOL_SIZE,KEEP_ALIVE_TIME,TimeUnit.SECONDS,queue,POOL_PREFIX_NAME);
    }

    /**
     *  单例模式获取线程池
     * @return ExecutorService
     */
    private static ExecutorService getInstance(){
        return constomThreadPool;
    }

    private static Future<?> submit(Runnable task){
       return constomThreadPool.submit(task);
    }

    private static <T> Future<T> submit(Runnable task, T result){
        return constomThreadPool.submit(task,result);
    }

    private static <T> Future<T> submit(Callable<T> task){
        return constomThreadPool.submit(task);
    }

    private static void execute(Runnable task){
        constomThreadPool.execute(task);
    }
}

三、业界知名自定义线程池扩展使用.

1、org.apache.tomcat.util.threads;【Tomcat线程池】

2、XXL-JOB分布式任务调度框架的快慢线程池，线程池任务隔离.

public class JobTriggerPoolHelper {
    private static Logger logger = LoggerFactory.getLogger(JobTriggerPoolHelper.class);

    // ---------------------- trigger pool ----------------------

    // fast/slow thread pool
    private ThreadPoolExecutor fastTriggerPool = null;
    private ThreadPoolExecutor slowTriggerPool = null;

    public void start(){
        fastTriggerPool = new ThreadPoolExecutor(
                10,
                XxlJobAdminConfig.getAdminConfig().getTriggerPoolFastMax(),
                60L,
                TimeUnit.SECONDS,
                new LinkedBlockingQueue<Runnable>(1000),
                new ThreadFactory() {
                    @Override
                    public Thread newThread(Runnable r) {
                        return new Thread(r, "xxl-job, admin JobTriggerPoolHelper-fastTriggerPool-" + r.hashCode());
                    }
                });

        slowTriggerPool = new ThreadPoolExecutor(
                10,
                XxlJobAdminConfig.getAdminConfig().getTriggerPoolSlowMax(),
                60L,
                TimeUnit.SECONDS,
                new LinkedBlockingQueue<Runnable>(2000),
                new ThreadFactory() {
                    @Override
                    public Thread newThread(Runnable r) {
                        return new Thread(r, "xxl-job, admin JobTriggerPoolHelper-slowTriggerPool-" + r.hashCode());
                    }
                });
    }

    public void stop() {
        //triggerPool.shutdown();
        fastTriggerPool.shutdownNow();
        slowTriggerPool.shutdownNow();
        logger.info(">>>>>>>>> xxl-job trigger thread pool shutdown success.");
    }

    // job timeout count
    private volatile long minTim = System.currentTimeMillis()/60000;     // ms > min
    private volatile ConcurrentMap<Integer, AtomicInteger> jobTimeoutCountMap = new ConcurrentHashMap<>();

    /**
     * add trigger
     */
    public void addTrigger(final int jobId,
                           final TriggerTypeEnum triggerType,
                           final int failRetryCount,
                           final String executorShardingParam,
                           final String executorParam,
                           final String addressList) {

        // choose thread pool
        ThreadPoolExecutor triggerPool_ = fastTriggerPool;
        AtomicInteger jobTimeoutCount = jobTimeoutCountMap.get(jobId);
        if (jobTimeoutCount!=null && jobTimeoutCount.get() > 10) {      // job-timeout 10 times in 1 min
            triggerPool_ = slowTriggerPool;
        }

        // trigger
        triggerPool_.execute(new Runnable() {
            @Override
            public void run() {

                long start = System.currentTimeMillis();

                try {
                    // do trigger
                    XxlJobTrigger.trigger(jobId, triggerType, failRetryCount, executorShardingParam, executorParam, addressList);
                } catch (Exception e) {
                    logger.error(e.getMessage(), e);
                } finally {

                    // check timeout-count-map
                    long minTim_now = System.currentTimeMillis()/60000;
                    if (minTim != minTim_now) {
                        minTim = minTim_now;
                        jobTimeoutCountMap.clear();
                    }

                    // incr timeout-count-map
                    long cost = System.currentTimeMillis()-start;
                    if (cost > 500) {       // ob-timeout threshold 500ms
                        AtomicInteger timeoutCount = jobTimeoutCountMap.putIfAbsent(jobId, new AtomicInteger(1));
                        if (timeoutCount != null) {
                            timeoutCount.incrementAndGet();
                        }
                    }

                }

            }
        });
    }

    // ---------------------- helper ----------------------

    private static JobTriggerPoolHelper helper = new JobTriggerPoolHelper();

    public static void toStart() {
        helper.start();
    }
    public static void toStop() {
        helper.stop();
    }

    /**
     * @param jobId
     * @param triggerType
     * @param failRetryCount
     * 			>=0: use this param
     * 			<0: use param from job info config
     * @param executorShardingParam
     * @param executorParam
     *          null: use job param
     *          not null: cover job param
     */
    public static void trigger(int jobId, TriggerTypeEnum triggerType, int failRetryCount, String executorShardingParam, String executorParam, String addressList) {
        helper.addTrigger(jobId, triggerType, failRetryCount, executorShardingParam, executorParam, addressList);
    }

}

①、定义两个线程池，一个是fastTriggerPool，另一个是slowTriggerPool。
②、定义一个容器ConcurrentMap，存放每个任务的执行慢次数，60秒后自动清空该容器。
③、在线程的run()方法中计算每个任务的耗时，如果大于500ms，则任务的慢执行次数+1。

3、基于线程池动态监控动态线程池

引用图片，线程池常见问题

还有比较多啦，例如ES的基于JDK的线程池，Dubbo中等。

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