什么是线程池
线程池的作用是初始化一些线程,当有任务的时候,就从中启动一个来执行相关任务,执行完后,线程资源重新回收到线程池中,达到复用的效果,从而减少资源的开销
创建线程池
在JDK中,Executors
类已经帮我们封装了创建线程池的方法。
Executors.newFixedThreadPool(); Executors.newCachedThreadPool(); Executors.newScheduledThreadPool();
但是点进去看的话,
public static ExecutorService newFixedThreadPool(int nThreads) { return new ThreadPoolExecutor(nThreads, nThreads, 0L, TimeUnit.MILLISECONDS, new LinkedBlockingQueue<Runnable>()); }
它的内部实现还是基于ThreadPoolExecutor
来实现的。通过阿里代码规范插件扫描会提示我们用ThreadPoolExecutor
去实现线程池。通过查看ThreadPoolExecutor
的构造方法
public ThreadPoolExecutor(int corePoolSize, int maximumPoolSize, long keepAliveTime, TimeUnit unit, BlockingQueue<Runnable> workQueue, ThreadFactory threadFactory, RejectedExecutionHandler handler) { ... do something ... }
我觉得有以下几方面的原因。
- 可以灵活设置
keepAliveTime
(当线程池中线程数大于corePoolSize
的数m, 为这m个线程设置的最长等待时间 ),节约系统资源。 workQueue
:线程等待队列,在Executors
中默认的是LinkedBlockingQueue
。可以理解是一种无界的数组,当有不断有线程来的时候,可能会撑爆机器内存。- 可以设线程工厂,里面添加自己想要的一些元素,只需要实现JDK的
ThreadFactory
类。 - 按照自己的业务设置合适的拒绝策略。策略有以下几种
- AbortPolicy:直接抛出拒绝异常(继承自RuntimeException),会中断调用者的处理过程,所以除非有明确需求,一般不推荐
- DiscardPolicy:默默丢弃无法加载的任务。
- DiscardOldestPolicy:丢弃队列中最老的,然后再次尝试提交新任务。
- CallerRunsPolicy:在调用者线程中(也就是说谁把 r 这个任务甩来的),运行当前被丢弃的任务。只会用调用者所在线程来运行任务,也就是说任务不会进入线程池。如果线程池已经被关闭,则直接丢弃该任务。
使用线程池
声明ThreadFactory
public class NacosSyncThreadFactory implements ThreadFactory { private final AtomicInteger threadNum = new AtomicInteger(1); private String threadPrefix = null; private ThreadGroup threadGroup; public NacosSyncThreadFactory(String prefix) { this.threadPrefix = "thread" + "-" + prefix + "-" ; threadGroup = Thread.currentThread().getThreadGroup(); } public NacosSyncThreadFactory() { this("pool"); } @Override public Thread newThread(Runnable r) { String name = threadPrefix + threadNum.incrementAndGet(); Thread thread = new Thread(threadGroup, r, name); return thread; } }
创建线程池类
public class MyThreadPool { private ThreadFactory threadFactory; private int threadNum; private BlockingQueue blockingQueue; private RejectedExecutionHandler handler; public MyThreadPool(ThreadFactory threadFactory, int threadNum, BlockingQueue blockingQueue, RejectedExecutionHandler handler ) { this.threadFactory = threadFactory; this.threadNum = threadNum; this.blockingQueue = blockingQueue; this.handler = handler; } public MyThreadPool() { this(Executors.defaultThreadFactory(), 10, new ArrayBlockingQueue(10), new ThreadPoolExecutor.AbortPolicy()); } public ThreadPoolExecutor initThreadPool(ThreadFactory threadFactory, int threadNum, BlockingQueue blockingQueue, RejectedExecutionHandler handler) { if (handler == null) { handler = new ThreadPoolExecutor.AbortPolicy(); } return new ThreadPoolExecutor(1, threadNum, 5, TimeUnit.SECONDS, blockingQueue, threadFactory, handler); } }
调用线程池
初始化线程池类
MyThreadPool myThreadPool = new MyThreadPool(); threadPoolExecutor = myThreadPool.initThreadPool( new NacosSyncThreadFactory("nacos-sync"), threadNum, new ArrayBlockingQueue(10), new ThreadPoolExecutor.DiscardPolicy() ); }
创建Callable(FutureTask)
/** * 分页获取task信息 * @return */ private List<Task> getTask(int pageNum) { IPage<Task> page = new Page(pageNum, 25); IPage<Task> taskIPage = this.taskService.page(page); if (null == taskIPage || CollectionUtils.isEmpty(taskIPage.getRecords())) { return null; } return taskIPage.getRecords(); } // 执行任务 private FutureTask<String> assembleTaskFuture(Task task) { FutureTask<String> futureTask = new FutureTask(() -> { // 执行任务 this.doSyncWork(task); return "success"; }); return futureTask; }
执行任务(FutureTask)
public void zkSync() { // 获取数据总数,得到线程数 int count = this.taskService.count(); int pageSize = 25; int num = count / pageSize; int pageTotal = count % pageSize == 0 ? num : num + 1; log.info("========总记录数:{}=====总页数:{}", count, pageTotal); for (int i = 1; i <= pageTotal; i++) { List<Task> taskList = this.getTask(i); if (CollectionUtils.isEmpty(taskList)) { break; } List<Integer> collect = taskList.stream().map(task -> task.getId()).collect(Collectors.toList()); taskList.forEach(task -> { FutureTask<String> futureTask = this.assembleTaskFuture(task); threadPoolExecutor.execute(futureTask); }); } threadPoolExecutor.shutdown(); }
来源:https://www.cnblogs.com/KevinStark/p/12430091.html