# 【优雅代码】04-1行代码完成多线程，别再写runnable了 > 欢迎关注b站账号/公众号【六边形战士夏宁】，一个要把各项指标拉满的男人。该文章已在[github目录](https://github.com/edanlx/SealBook/blob/master/catalogue/wechat.md)收录。屏幕前的**大帅比**和**大漂亮**如果有帮助到你的话请顺手点个赞、加个收藏这对我真的很重要。别下次一定了，都不关注上哪下次一定。 * [可直接运行的完整代码](https://github.com/edanlx/TechingCode/tree/master/demoGrace/src/main/java/com/example/demo/lesson/grace/thread) * [视频讲解](https://www.bilibili.com/video/BV1jr4y1w7SH/) ## 1.背景介绍 java8提供的CompletableFuture以及匿名函数可以让我们一行代码完成多线程 ## 2.建立相关类 ### 2.1.ThreadEntity 用于多线程测试的实体类 ```java public class ThreadEntity { private int num; private int price; public int countPrice(){ price = RandomUtils.nextInt(); try { System.out.println(num); // 随机等待1~10秒 Thread.sleep(RandomUtils.nextInt(1, 10) * 1000); System.out.println(num); } catch (InterruptedException e) { e.printStackTrace(); } return price; } } ``` ### 2.2.ThreadPoolManager ```java /** * tasks 每秒的任务数，默认200,依据访问量及使用线程池的地方进行计算 * taskCost：每个任务花费时间，默认0.1s * responseTime：最大响应时间，默认为1s，一般用户最大忍受时间为3秒 * * @author seal email:876651109@qq.com * @date 2020/5/30 10:08 AM */ @Data @Slf4j @Configuration public class ThreadPoolManager { /** * 平均响应时间默认2秒 */ private static final float ALL_COST_AVG = 2F; /** * 平均IO时间默认1.5秒 */ private static final float IO_COST_AVG = 1.5F; /** * 服务器核数 */ private static final int SIZE_PROCESSOR = Runtime.getRuntime().availableProcessors(); /** * https://www.cnblogs.com/dennyzhangdd/p/6909771.html?utm_source=itdadao&utm_medium=referral * 阻塞系数=阻塞时间/（阻塞时间+计算时间） * 线程数=核心数/(1-阻塞系数) * 等同于CPU核心数*cpu使用率*(1+等待时间与计算时间的比率) * N+1通常为最优效率 *

* https://blog.51cto.com/13527416/2056080 */ private static final int SIZE_CORE_POOL = SIZE_PROCESSOR + 1; /** * 线程池维护最大数量，默认会与核心线程数一致无意义，保守情况取2cpu * 或者使用简单计算线程池大小 = （（线程 IO time + 线程 CPU time ）/线程 CPU time ） CPU数目** * 请求所消耗的时间 /(请求所消耗的时间-DB处理)*CPU数目,重点在于cpu等待时间，通常为数据库DB时间 * 按照通常2秒展示界面，数据库运算1.5秒则(2/0.5)*n,其实就是优化等待时间 *

* 默认4n即8核32线程 */ private static final int SIZE_MAX_POOL = (int) (SIZE_PROCESSOR * (ALL_COST_AVG / (ALL_COST_AVG - IO_COST_AVG))); /** * 线程池队列长度，默认为integer最大值,Dubbo使用1000，无限大会引起用户用户的任务一直排队，应选择适当性丢弃， * 可忍受时间6其它的则抛弃 * SIZE_MAX_POOL/IO_COST_AVG=每秒可处理任务数,默认为 * 可忍受时间6*每秒可处理任务数=X队列数 */ private static final int SIZE_QUEUE = (int) (6 * (SIZE_MAX_POOL / IO_COST_AVG)); /** * 线程池具体类 * LinkedBlockingDeque常用于固定线程，SynchronousQueue常用于cache线程池 * Executors.newCachedThreadPool()常用于短期任务 *

* 线程工厂选择,区别不大 * 有spring的CustomizableThreadFactory,new CustomizableThreadFactory("springThread-pool-") * guava的ThreadFactoryBuilder,new ThreadFactoryBuilder().setNameFormat("retryClient-pool-").build(); * apache-lang的BasicThreadFactory,new BasicThreadFactory.Builder().namingPattern("basicThreadFactory-").build() *

* 队列满了的策略默认AbortPolicy */ private static ThreadPoolManager threadPoolManager = new ThreadPoolManager(); private final ThreadPoolExecutor pool = new ThreadPoolExecutor( SIZE_CORE_POOL, SIZE_MAX_POOL, 30L, TimeUnit.SECONDS, new LinkedBlockingDeque<>(SIZE_QUEUE), new CustomizableThreadFactory("springThread-pool-"), new ThreadPoolExecutor.AbortPolicy() ); private void prepare() { if (pool.isShutdown() && !pool.prestartCoreThread()) { int coreSize = pool.prestartAllCoreThreads(); System.out.println("当前线程池"); } } public static ThreadPoolManager getInstance() { if (threadPoolManager != null) { ThreadPoolExecutor pool = threadPoolManager.pool; } return threadPoolManager; } } ``` ## 3.核心代码 ### 3.1.并行流 parallel是并行核心可以发现内部是多线程运行，但是经过collect以后会排好序所以不用担心，小项目可以使用，大项目的话建议老老实实用自己的线程池，JDK自带的fork/join并不贴合业务 ```java System.out.println(Stream.of(1, 2, 3, 4, 5, 6).parallel().map(l -> { System.out.println(l); return l; }).collect(Collectors.toList())); ``` 输出如下，因为多线程所以随机输出，但因为使用collect收集则最终结果并未发生改变 ```text 2 6 4 5 3 1 [1, 2, 3, 4, 5, 6] ``` ### 3.2.同步代码这个可以不用再去实现线程的接口，不过还是要考虑一下队列满了的丢弃情况 ```java List listEntity = IntStream.range(0, 10).mapToObj(x -> ThreadEntity.builder().num(x).build()).collect(Collectors.toList()); List> listCompletableFuture = listEntity.stream().map(x -> { try { // 此处ThreadPoolManager.getInstance().getPool()如果不传该参数则使用默认commonPool，无特殊需求的话trycatch一般不写 return CompletableFuture.supplyAsync(() -> x.countPrice(), ThreadPoolManager.getInstance().getPool()); } catch (RejectedExecutionException e) { System.out.println("reject" + x); log.error("", e); return null; } }).collect(Collectors.toList()); List result = listCompletableFuture.stream().map(CompletableFuture::join).collect(Collectors.toList()); System.out.println(result); System.out.println(listEntity); ``` 输出如下可以看到运行是以多线程的方式进行，但是结果和原先是保持一致的 ```text start6 start9 start0 start3 start2 start1 start8 start5 start4 start7 end3 end8 end5 end7 end9 end1 end2 end6 end0 end4 [131523688, 1491605535, 222657954, 132274662, 1134597171, 2057763841, 1168687436, 1842194861, 1264173480, 56446450] [ThreadEntity(super=com.example.demo.lesson.grace.thread.ThreadEntity@7d6f201, num=0, price=131523688), ThreadEntity(super=com.example.demo.lesson.grace.thread.ThreadEntity@58e825f3, num=1, price=1491605535), ThreadEntity(super=com.example.demo.lesson.grace.thread.ThreadEntity@d458bb1, num=2, price=222657954), ThreadEntity(super=com.example.demo.lesson.grace.thread.ThreadEntity@7e26830, num=3, price=132274662), ThreadEntity(super=com.example.demo.lesson.grace.thread.ThreadEntity@43a0a2b8, num=4, price=1134597171), ThreadEntity(super=com.example.demo.lesson.grace.thread.ThreadEntity@7aa70ac1, num=5, price=2057763841), ThreadEntity(super=com.example.demo.lesson.grace.thread.ThreadEntity@45a8d047, num=6, price=1168687436), ThreadEntity(super=com.example.demo.lesson.grace.thread.ThreadEntity@6dcdb8e3, num=7, price=1842194861), ThreadEntity(super=com.example.demo.lesson.grace.thread.ThreadEntity@4b59d119, num=8, price=1264173480), ThreadEntity(super=com.example.demo.lesson.grace.thread.ThreadEntity@35d5d9e, num=9, price=56446450)] ``` 如果IntStream.range(0, 10)改成(0, 1000)则会有如下拒绝报错 ```text java.util.concurrent.RejectedExecutionException: Task java.util.concurrent.CompletableFuture$AsyncSupply@5af97850 rejected from java.util.concurrent.ThreadPoolExecutor@491666ad[Running, pool size = 64, active threads = 64, queued tasks = 256, completed tasks = 0] at java.util.concurrent.ThreadPoolExecutor$AbortPolicy.rejectedExecution(ThreadPoolExecutor.java:2063) at java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.java:830) at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:1379) at java.util.concurrent.CompletableFuture.asyncSupplyStage(CompletableFuture.java:1618) at java.util.concurrent.CompletableFuture.supplyAsync(CompletableFuture.java:1843) at com.example.demo.lesson.grace.thread.TestMain.lambda$threadEx1$2(TestMain.java:34) at java.util.stream.ReferencePipeline$3$1.accept(ReferencePipeline.java:193) at java.util.ArrayList$ArrayListSpliterator.forEachRemaining(ArrayList.java:1384) at java.util.stream.AbstractPipeline.copyInto(AbstractPipeline.java:482) at java.util.stream.AbstractPipeline.wrapAndCopyInto(AbstractPipeline.java:472) at java.util.stream.ReduceOps$ReduceOp.evaluateSequential(ReduceOps.java:708) at java.util.stream.AbstractPipeline.evaluate(AbstractPipeline.java:234) at java.util.stream.ReferencePipeline.collect(ReferencePipeline.java:499) at com.example.demo.lesson.grace.thread.TestMain.threadEx1(TestMain.java:41) at com.example.demo.lesson.grace.thread.TestMain.main(TestMain.java:26) rejectThreadEntity(super=com.example.demo.lesson.grace.thread.ThreadEntity@1a9, num=366) ``` ### 3.3.异步代码以下代码可以直接简写成一行，在处理异步任务变得异常方便 CompletableFuture.runAsync(() -> fun()) ```java List listEntity = IntStream.range(0, 500).mapToObj(x -> ThreadEntity.builder().num(x).build()).collect(Collectors.toList()); List listCompletableFuture = listEntity.stream().map(x -> { try { // 此处ThreadPoolManager.getInstance().getPool()如果不传该参数则使用默认commonPool，无特殊需求的话trycatch一般不写 return CompletableFuture.runAsync(() -> x.countPrice(), ThreadPoolManager.getInstance().getPool()); } catch (RejectedExecutionException e) { System.out.println("reject" + x); return null; } }).collect(Collectors.toList()); listCompletableFuture.stream().map(CompletableFuture::join); System.out.println("1234"); // 一行多线程异步执行写法 CompletableFuture.runAsync(() -> System.out.println(1)); ``` 输出如下，可以看到主线程已经结束了其它子线程才在输出，完全没有等待的多线程 ```text 1234 1 start7 start0 start6 start5 start4 start2 start8 start1 start9 start3 end8 end4 end9 end6 end2 end0 end1 end3 end5 end7 ```