0 文章概述

动态线程池是指可以动态调节线程池某些参数，本文我们结合Apollo和线程池实现一个动态线程池。

1 线程池基础

1.1 七个参数

我们首先回顾Java线程池七大参数，这对后续设置线程池参数有帮助。我们查看ThreadPoolExecutor构造函数如下：

public class ThreadPoolExecutor extends AbstractExecutorService {public ThreadPoolExecutor(int corePoolSize,int maximumPoolSize,long keepAliveTime,TimeUnit unit,BlockingQueue workQueue,ThreadFactory threadFactory,RejectedExecutionHandler handler) {if (corePoolSize < 0 ||maximumPoolSize <= 0 ||maximumPoolSize < corePoolSize ||keepAliveTime < 0)throw new IllegalArgumentException();if (workQueue == null || threadFactory == null || handler == null)throw new NullPointerException();this.acc = System.getSecurityManager() == null ?null :AccessController.getContext();this.corePoolSize = corePoolSize;this.maximumPoolSize = maximumPoolSize;this.workQueue = workQueue;this.keepAliveTime = unit.toNanos(keepAliveTime);this.threadFactory = threadFactory;this.handler = handler;}
}

corePoolSize

线程池核心线程数，类比业务大厅开设的固定窗口。例如业务大厅开设2个固定窗口，那么这两个窗口不会关闭，全天都会进行业务办理

workQueue

存储已提交但尚未执行的任务，类比业务大厅等候区。例如业务大厅一开门进来很多顾客，2个固定窗口进行业务办理，其他顾客到等候区等待

maximumPoolSize

线程池可以容纳同时执行最大线程数，类比业务大厅最大窗口数。例如业务大厅最大窗口数是5个，业务员看到2个固定窗口和等候区都满了，可以临时增加3个窗口

keepAliveTime

非核心线程数存活时间。当业务不忙时刚才新增的3个窗口需要关闭，空闲时间超过keepAliveTime空闲会被关闭

unit

keepAliveTime存活时间单位

threadFactory

线程工厂可以用来指定线程名

handler

线程池线程数已达到maximumPoolSize且队列已满时执行拒绝策略。例如业务大厅5个窗口全部处于忙碌状态且等候区已满，业务员根据实际情况选择拒绝策略

1.2 四种拒绝策略

(1) AbortPolicy

默认策略直接抛出RejectExecutionException阻止系统正常运行

/*** AbortPolicy** @author **/
public class AbortPolicyTest {public static void main(String[] args) {int coreSize = 1;int maxSize = 2;int queueSize = 1;AbortPolicy abortPolicy = new ThreadPoolExecutor.AbortPolicy();ThreadPoolExecutor executor = new ThreadPoolExecutor(coreSize, maxSize, 1, TimeUnit.SECONDS, new LinkedBlockingQueue(queueSize), Executors.defaultThreadFactory(), abortPolicy);for (int i = 0; i < 100; i++) {executor.execute(new Runnable() {@Overridepublic void run() {System.out.println(Thread.currentThread().getName() + " -> run");}});}}
}

程序执行结果：

pool-1-thread-1 -> run
pool-1-thread-2 -> run
pool-1-thread-1 -> run
Exception in thread "main" java.util.concurrent.RejectedExecutionException: Task com.xy.juc.threadpool.reject.AbortPolicyTest$1@70dea4e rejected from java.util.concurrent.ThreadPoolExecutor@5c647e05[Running, pool size = 2, active threads = 0, queued tasks = 0, completed tasks = 2]at java.util.concurrent.ThreadPoolExecutor$AbortPolicy.rejectedExecution(ThreadPoolExecutor.java:2063)at java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.java:830)at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:1379)at com.xy.juc.threadpool.reject.AbortPolicyTest.main(AbortPolicyTest.java:21)

(2) CallerRunsPolicy

任务回退给调用者自己运行

/*** CallerRunsPolicy** @author **/
public class CallerRunsPolicyTest {public static void main(String[] args) {int coreSize = 1;int maxSize = 2;int queueSize = 1;CallerRunsPolicy callerRunsPolicy = new ThreadPoolExecutor.CallerRunsPolicy();ThreadPoolExecutor executor = new ThreadPoolExecutor(coreSize, maxSize, 1, TimeUnit.SECONDS, new LinkedBlockingQueue(queueSize), Executors.defaultThreadFactory(), callerRunsPolicy);for (int i = 0; i < 10; i++) {executor.execute(new Runnable() {@Overridepublic void run() {System.out.println(Thread.currentThread().getName() + " -> run");}});}}
}

程序执行结果：

main -> run
pool-1-thread-1 -> run
pool-1-thread-2 -> run
pool-1-thread-1 -> run
main -> run
main -> run
pool-1-thread-2 -> run
pool-1-thread-1 -> run
main -> run
pool-1-thread-2 -> run

(3) DiscardOldestPolicy

抛弃队列中等待最久的任务不会抛出异常

/*** DiscardOldestPolicy** @author **/
public class DiscardOldestPolicyTest {public static void main(String[] args) {int coreSize = 1;int maxSize = 2;int queueSize = 1;DiscardOldestPolicy discardOldestPolicy = new ThreadPoolExecutor.DiscardOldestPolicy();ThreadPoolExecutor executor = new ThreadPoolExecutor(coreSize, maxSize, 1, TimeUnit.SECONDS, new LinkedBlockingQueue(queueSize), Executors.defaultThreadFactory(), discardOldestPolicy);for (int i = 0; i < 10; i++) {executor.execute(new Runnable() {@Overridepublic void run() {System.out.println(Thread.currentThread().getName() + " -> run");}});}}
}

程序执行结果：

pool-1-thread-1 -> run
pool-1-thread-2 -> run
pool-1-thread-1 -> run

(4) DiscardPolicy

直接丢弃任务不会抛出异常

/*** DiscardPolicy** @author **/
public class DiscardPolicyTest {public static void main(String[] args) {int coreSize = 1;int maxSize = 2;int queueSize = 1;DiscardPolicy discardPolicy = new ThreadPoolExecutor.DiscardPolicy();ThreadPoolExecutor executor = new ThreadPoolExecutor(coreSize, maxSize, 1, TimeUnit.SECONDS, new LinkedBlockingQueue(queueSize), Executors.defaultThreadFactory(), discardPolicy);for (int i = 0; i < 10; i++) {executor.execute(new Runnable() {@Overridepublic void run() {System.out.println(Thread.currentThread().getName() + " -> run");}});}}
}

程序执行结果：

pool-1-thread-1 -> run
pool-1-thread-2 -> run
pool-1-thread-1 -> run

1.3 修改参数

如果初始化线程池完成后，我们是否可以修改线程池某些参数呢？答案是可以。我们选择线程池提供的四个修改方法进行源码分析。

(1) setCorePoolSize

public class ThreadPoolExecutor extends AbstractExecutorService {public void setCorePoolSize(int corePoolSize) {if (corePoolSize < 0)throw new IllegalArgumentException();// 新核心线程数减去原核心线程数int delta = corePoolSize - this.corePoolSize;// 新核心线程数赋值this.corePoolSize = corePoolSize;// 如果当前线程数大于新核心线程数if (workerCountOf(ctl.get()) > corePoolSize)// 中断空闲线程interruptIdleWorkers();// 如果需要新增线程则通过addWorker增加工作线程else if (delta > 0) {int k = Math.min(delta, workQueue.size());while (k-- > 0 && addWorker(null, true)) {if (workQueue.isEmpty())break;}}}
}

(2) setMaximumPoolSize

public class ThreadPoolExecutor extends AbstractExecutorService {public void setMaximumPoolSize(int maximumPoolSize) {if (maximumPoolSize <= 0 || maximumPoolSize < corePoolSize)throw new IllegalArgumentException();this.maximumPoolSize = maximumPoolSize;// 如果当前线程数量大于新最大线程数量if (workerCountOf(ctl.get()) > maximumPoolSize)// 中断空闲线程interruptIdleWorkers();}
}

(3) setKeepAliveTime

public class ThreadPoolExecutor extends AbstractExecutorService {public void setKeepAliveTime(long time, TimeUnit unit) {if (time < 0)throw new IllegalArgumentException();if (time == 0 && allowsCoreThreadTimeOut())throw new IllegalArgumentException("Core threads must have nonzero keep alive times");long keepAliveTime = unit.toNanos(time);// 新超时时间减去原超时时间long delta = keepAliveTime - this.keepAliveTime;this.keepAliveTime = keepAliveTime;// 如果新超时时间小于原超时时间if (delta < 0)// 中断空闲线程interruptIdleWorkers();}
}

(4) setRejectedExecutionHandler

public class ThreadPoolExecutor extends AbstractExecutorService {public void setRejectedExecutionHandler(RejectedExecutionHandler handler) {if (handler == null)throw new NullPointerException();// 设置拒绝策略this.handler = handler;}
}

现在我们知道线程池系统上述调整参数的方法，但仅仅分析到此是不够的，因为如果没有动态调整参数的方法，每次修改必须重新发布才可以生效，那么有没有方法不用发布就可以动态调整线程池参数呢？

2 Apollo配置中心

2.1 核心原理

Apollo是携程框架部门研发的分布式配置中心，能够集中化管理应用不同环境、不同集群的配置，配置修改后能够实时推送到应用端，并且具备规范的权限、流程治理等特性，适用于微服务配置管理场景。Apollo开源地址如下：

https://github.com/ctripcorp/apollo

我们在使用配置中心时第一步用户在配置中心修改配置项，第二步配置中心通知Apollo客户端有配置更新，第三步Apollo客户端从配置中心拉取最新配置，更新本地配置并通知到应用，官网基础模型图如下：

配置中心配置项发生变化客户端如何感知呢？分为推和拉两种方式。推依赖客户端和服务端保持了一个长连接，发生数据变化时服务端推送信息给客户端，这就是长轮询机制。拉依赖客户端定时从配置中心服务端拉取应用最新配置，这是一个fallback机制。官网客户端设计图如下：

本文重点分析配置更新推送方式，我们首先看官网服务端设计图：

ConfigService模块提供配置的读取推送等功能，服务对象是Apollo客户端。AdminService模块提供配置的修改发布等功能，服务对象是Portal模块即管理界面。需要说明Apollo并没有引用消息中间件，官方图中发送异步消息是指ConfigService定时扫描异步消息数据表：

消息数据保存在MySQL消息表：

CREATE TABLE `releasemessage` (`Id` int(11) unsigned NOT NULL AUTO_INCREMENT COMMENT '自增主键',`Message` varchar(1024) NOT NULL DEFAULT '' COMMENT '发布的消息内容',`DataChange_LastTime` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '最后修改时间',PRIMARY KEY (`Id`),KEY `DataChange_LastTime` (`DataChange_LastTime`),KEY `IX_Message` (`Message`(191))
) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT='发布消息'

2.2 实例分析

2.2.1 服务端安装

服务端关键步骤是导入数据库和修改端口号，具体步骤请参看官方网站：

https://ctripcorp.github.io/apollo/#/zh/deployment/quick-start

启动成功后访问地址：

http://localhost:8070

输入用户名apollo、密码admin登录：

点击进入我创建myApp项目，我们看到在DEV环境、default集群、application命名空间包含一个timeout配置项，100是这个配置项的值，下面我们在应用程序读取这个配置项：

2.2.2 应用程序

(1) 引入依赖

com.ctrip.framework.apolloapollo-client1.7.0
 

(2) 简单实例

public class GetApolloConfigTest extends BaseTest {/*** -Dapp.id=myApp -Denv=DEV -Dapollo.cluster=default -Ddev_meta=http://localhost:8080** myApp+DEV+default+application*/@Testpublic void testGet() throws InterruptedException {Config appConfig = ConfigService.getAppConfig();while (true) {String value = appConfig.getProperty("timeout", "200");System.out.println("timeout=" + value);TimeUnit.SECONDS.sleep(1);}}
}

因为上述程序是通过while(true)不断获取配置项的值，所以程序输出结果如下：

timeout=100
timeout=100
timeout=100
timeout=100
timeout=100
timeout=100

我们现在把配置项的值改为200程序输出结果如下:

timeout=100
timeout=100
timeout=100
timeout=100
timeout=200
timeout=200
timeout=200

(3) 监听实例

生产环境我们一般不用while(true)监听变化，而是通过注册监听器方式感知变化信息：

public class GetApolloConfigTest extends BaseTest {/*** 监听命名空间变化** -Dapp.id=myApp -Denv=DEV -Dapollo.cluster=default -Ddev_meta=http://localhost:8080** myApp+DEV+default+application*/@Testpublic void testListen() throws InterruptedException {Config config = ConfigService.getConfig("application");config.addChangeListener(new ConfigChangeListener() {@Overridepublic void onChange(ConfigChangeEvent changeEvent) {System.out.println("发生变化命名空间=" + changeEvent.getNamespace());for (String key : changeEvent.changedKeys()) {ConfigChange change = changeEvent.getChange(key);System.out.println(String.format("发生变化key=%s,oldValue=%s,newValue=%s,changeType=%s", change.getPropertyName(), change.getOldValue(), change.getNewValue(), change.getChangeType()));}}});Thread.sleep(1000000L);}
}

我们现在把timeout值从200改为300，程序输出结果：

发生变化命名空间=application
发生变化key=timeout,oldValue=200,newValue=300,changeType=MODIFIED

3 动态线程池

现在我们把线程池和Apollo结合起来构建动态线程池，具备了上述知识编写起来并不复杂。首先我们用默认值构建一个线程池，然后线程池会监听Apollo关于相关配置项，如果相关配置有变化则刷新相关参数。第一步在Apollo配置中心设置三个线程池参数（本文没有设置拒绝策略）：

第二步编写核心代码：

/*** 动态线程池工厂** @author **/
@Slf4j
@Component
public class DynamicThreadPoolFactory {private static final String NAME_SPACE = "threadpool-config";/** 线程执行器 **/private volatile ThreadPoolExecutor executor;/** 核心线程数 **/private Integer CORE_SIZE = 10;/** 最大值线程数 **/private Integer MAX_SIZE = 20;/** 等待队列长度 **/private Integer QUEUE_SIZE = 2000;/** 线程存活时间 **/private Long KEEP_ALIVE_TIME = 1000L;/** 线程名 **/private String threadName;public DynamicThreadPoolFactory() {Config config = ConfigService.getConfig(NAME_SPACE);init(config);listen(config);}/*** 初始化*/private void init(Config config) {if (executor == null) {synchronized (DynamicThreadPoolFactory.class) {if (executor == null) {String coreSize = config.getProperty(KeysEnum.CORE_SIZE.getNodeKey(), CORE_SIZE.toString());String maxSize = config.getProperty(KeysEnum.MAX_SIZE.getNodeKey(), MAX_SIZE.toString());String keepAliveTIme = config.getProperty(KeysEnum.KEEP_ALIVE_TIME.getNodeKey(), KEEP_ALIVE_TIME.toString());BlockingQueue queueToUse = new LinkedBlockingQueue(QUEUE_SIZE);executor = new ThreadPoolExecutor(Integer.valueOf(coreSize), Integer.valueOf(maxSize), Long.valueOf(keepAliveTIme), TimeUnit.MILLISECONDS, queueToUse, new NamedThreadFactory(threadName, true), new AbortPolicyDoReport(threadName));}}}}/*** 监听器*/private void listen(Config config) {config.addChangeListener(new ConfigChangeListener() {@Overridepublic void onChange(ConfigChangeEvent changeEvent) {log.info("命名空间发生变化={}", changeEvent.getNamespace());for (String key : changeEvent.changedKeys()) {ConfigChange change = changeEvent.getChange(key);String newValue = change.getNewValue();refreshThreadPool(key, newValue);log.info("发生变化key={},oldValue={},newValue={},changeType={}", change.getPropertyName(), change.getOldValue(), change.getNewValue(), change.getChangeType());}}});}/*** 刷新线程池*/private void refreshThreadPool(String key, String newValue) {if (executor == null) {return;}if (KeysEnum.CORE_SIZE.getNodeKey().equals(key)) {executor.setCorePoolSize(Integer.valueOf(newValue));log.info("修改核心线程数key={},value={}", key, newValue);}if (KeysEnum.MAX_SIZE.getNodeKey().equals(key)) {executor.setMaximumPoolSize(Integer.valueOf(newValue));log.info("修改最大线程数key={},value={}", key, newValue);}if (KeysEnum.KEEP_ALIVE_TIME.getNodeKey().equals(key)) {executor.setKeepAliveTime(Integer.valueOf(newValue), TimeUnit.MILLISECONDS);log.info("修改活跃时间key={},value={}", key, newValue);}}public ThreadPoolExecutor getExecutor(String threadName) {return executor;}enum KeysEnum {CORE_SIZE("coreSize", "核心线程数"),MAX_SIZE("maxSize", "最大线程数"),KEEP_ALIVE_TIME("keepAliveTime", "线程活跃时间");private String nodeKey;private String desc;KeysEnum(String nodeKey, String desc) {this.nodeKey = nodeKey;this.desc = desc;}public String getNodeKey() {return nodeKey;}public void setNodeKey(String nodeKey) {this.nodeKey = nodeKey;}public String getDesc() {return desc;}public void setDesc(String desc) {this.desc = desc;}}
}/*** 动态线程池执行器** @author **/
@Component
public class DynamicThreadExecutor {@Resourceprivate DynamicThreadPoolFactory threadPoolFactory;public void execute(String bizName, Runnable job) {threadPoolFactory.getExecutor(bizName).execute(job);}public Future sumbit(String bizName, Runnable job) {return threadPoolFactory.getExecutor(bizName).submit(job);}
}

第三步运行测试用例并结合VisualVM观察线程数：

/*** 动态线程池测试** @author **/
public class DynamicThreadExecutorTest extends BaseTest {@Resourceprivate DynamicThreadExecutor dynamicThreadExecutor;/*** -Dapp.id=myApp -Denv=DEV -Dapollo.cluster=default -Ddev_meta=http://localhost:8080** myApp+DEV+default+thread-pool*/@Testpublic void testExecute() throws InterruptedException {while (true) {dynamicThreadExecutor.execute("bizName", new Runnable() {@Overridepublic void run() {System.out.println("bizInfo");}});TimeUnit.SECONDS.sleep(1);}}
}

我们在配置中心修改配置项把核心线程数设置为50，最大线程数设置为100：

通过VisualVM可以观察到线程数显著上升：

4 文章总结

本文我们首先介绍了线程池基础知识，包括七大参数和四个拒绝策略，随后我们介绍了Apollo配置中心的原理和应用，最后我们将线程池和配置中心相结合，实现了动态调整线程数的效果，希望本文对大家有所帮助。