关于线程池:NacosThreadPoolExecutor构建动态线程池

动静线程池是指能够动静调节线程池某些参数，本文咱们联合 Apollo 和线程池实现一个动静线程池。

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


public class ThreadPoolExecutor extends AbstractExecutorService {
    public ThreadPoolExecutor(int corePoolSize,
                              int maximumPoolSize,
                              long keepAliveTime,
                              TimeUnit unit,
                              BlockingQueue<Runnable> 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;
    }
}

线程池外围线程数，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敞开，全天都会进行业务办理

存储已提交但尚未执行的工作，类比业务大厅等待区。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，其余顾客到等待区期待

线程池能够包容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 个固定窗口和等待区都满了，能够长期减少 3 个窗口

非核心线程数存活工夫。当业务不忙时方才新增的 3 个窗口须要敞开，闲暇工夫超过 keepAliveTime 闲暇会被敞开

keepAliveTime 存活工夫单位

线程工厂能够用来指定线程名

线程池线程数已达到 maximumPoolSize 且队列已满时执行回绝策略。例如业务大厅 5 个窗口全副处于繁忙状态且等待区已满，业务员依据理论状况抉择回绝策略

默认策略间接抛出 RejectExecutionException 阻止零碎失常运行

/**
 * 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<Runnable>(queueSize), Executors.defaultThreadFactory(), abortPolicy);
        for (int i = 0; i < 100; i++) {executor.execute(new Runnable() {
                @Override
                public void run() {System.out.println(Thread.currentThread().getName() + "-> run");
                }
            });
        }
    }
}

程序执行后果：

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)

工作回退给调用者本人运行

/**
 * 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<Runnable>(queueSize), Executors.defaultThreadFactory(), callerRunsPolicy);
        for (int i = 0; i < 10; i++) {executor.execute(new Runnable() {
                @Override
                public void run() {System.out.println(Thread.currentThread().getName() + "-> run");
                }
            });
        }
    }
}

程序执行后果：

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

摈弃队列中期待最久的工作不会抛出异样

/**
 * 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<Runnable>(queueSize), Executors.defaultThreadFactory(), discardOldestPolicy);
        for (int i = 0; i < 10; i++) {executor.execute(new Runnable() {
                @Override
                public void run() {System.out.println(Thread.currentThread().getName() + "-> run");
                }
            });
        }
    }
}

程序执行后果：

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

间接抛弃工作不会抛出异样

/**
 * 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<Runnable>(queueSize), Executors.defaultThreadFactory(), discardPolicy);
        for (int i = 0; i < 10; i++) {executor.execute(new Runnable() {
                @Override
                public void run() {System.out.println(Thread.currentThread().getName() + "-> run");
                }
            });
        }
    }
}

程序执行后果：

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

如果初始化线程池实现后，咱们是否能够批改线程池某些参数呢？答案是能够。咱们抉择线程池提供的四个批改办法进行源码剖析。

public class ThreadPoolExecutor extends AbstractExecutorService {public void setCorePoolSize(int corePoolSize) {if (corePoolSize < 0)
            throw new IllegalArgumentException();
        // 新外围线程数减去原外围线程数
        int delta = corePoolSize - this.corePoolSize;
        // 新外围线程数赋值
        this.corePoolSize = corePoolSize;
        // 如果以后线程数大于新外围线程数
        if (workerCountOf(ctl.get()) > corePoolSize)
            // 中断闲暇线程
            interruptIdleWorkers();
        // 如果须要新增线程则通过 addWorker 减少工作线程
        else if (delta > 0) {int k = Math.min(delta, workQueue.size());
            while (k-- > 0 && addWorker(null, true)) {if (workQueue.isEmpty())
                    break;
            }
        }
    }
}

public class ThreadPoolExecutor extends AbstractExecutorService {public void setMaximumPoolSize(int maximumPoolSize) {if (maximumPoolSize <= 0 || maximumPoolSize < corePoolSize)
            throw new IllegalArgumentException();
        this.maximumPoolSize = maximumPoolSize;
        // 如果以后线程数量大于新最大线程数量
        if (workerCountOf(ctl.get()) > maximumPoolSize)
            // 中断闲暇线程
            interruptIdleWorkers();}
}

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);
        // 新超时工夫减去原超时工夫
        long delta = keepAliveTime - this.keepAliveTime;
        this.keepAliveTime = keepAliveTime;
        // 如果新超时工夫小于原超时工夫
        if (delta < 0)
            // 中断闲暇线程
            interruptIdleWorkers();}
}

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

当初咱们晓得线程池零碎上述调整参数的办法，但仅仅剖析到此是不够的，因为如果没有动静调整参数的办法，每次批改必须从新公布才能够失效，那么有没有办法不必公布就能够动静调整线程池参数呢？

Apollo 是携程框架部门研发的分布式配置核心，可能集中化治理利用不同环境、不同集群的配置，配置批改后可能实时推送到利用端，并且具备标准的权限、流程治理等个性，实用于微服务配置管理场景。Apollo 开源地址如下：

https://github.com/ctripcorp/apollo

咱们在应用配置核心时第一步用户在配置核心批改配置项，第二步配置核心告诉 Apollo 客户端有配置更新，第三步 Apollo 客户端从配置核心拉取最新配置，更新本地配置并告诉到利用，官网根底模型图如下：

配置核心配置项发生变化客户端如何感知呢？分为推和拉两种形式。推依赖客户端和服务端放弃了一个长连贯，产生数据变动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核心服务端拉取利用最新配置，这是一个 fallback 机制。官网客户端设计图如下：

本文重点剖析配置更新推送形式，咱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性能，服务对象是 Apollo 客户端。AdminService 模块提供配置的批改公布等性能，服务对象是 Portal 模块即治理界面。须要阐明 Apollo 并没有援用消息中间件，官网图中发送异步音讯是指 ConfigService 定时扫描异步音讯数据表：

音讯数据保留在 MySQL 音讯表：

CREATE TABLE `releasemessage` (`Id` int(11) unsigned NOT NULL AUTO_INCREMENT COMMENT '自增主键',
  `Message` varchar(1024) NOT NULL DEFAULT ''COMMENT' 公布的音讯内容 ',
  `DataChange_LastTime` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '最初批改工夫',
  PRIMARY KEY (`Id`),
  KEY `DataChange_LastTime` (`DataChange_LastTime`),
  KEY `IX_Message` (`Message`(191))
) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT='公布音讯'

服务端关键步骤是导入数据库和批改端口号，具体步骤请参看官方网站：

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

启动胜利后拜访地址：

http://localhost:8070

输出用户名 apollo、明码 admin 登录：

点击进入我创立 myApp 我的项目，咱们看到在 DEV 环境、default 集群、application 命名空间蕴含一个 timeout 配置项，100 是这个配置项的值，上面咱们在应用程序读取这个配置项：

<dependencies>
    <dependency>
    <groupId>com.ctrip.framework.apollo</groupId>
    <artifactId>apollo-client</artifactId>
    <version>1.7.0</version>
    </dependency>
</dependencies>

public class GetApolloConfigTest extends BaseTest {

    /**
     * -Dapp.id=myApp -Denv=DEV -Dapollo.cluster=default -Ddev_meta=http://localhost:8080
     *
     * myApp+DEV+default+application
     */
    @Test
    public 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) 一直获取配置项的值，所以程序输入后果如下：

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

咱们当初把配置项的值改为 200 程序输入后果如下:

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

生产环境咱们个别不必 while(true) 监听变动，而是通过注册监听器形式感知变动信息：

public class GetApolloConfigTest extends BaseTest {

    /**
     * 监听命名空间变动
     *
     * -Dapp.id=myApp -Denv=DEV -Dapollo.cluster=default -Ddev_meta=http://localhost:8080
     *
     * myApp+DEV+default+application
     */
    @Test
    public void testListen() throws InterruptedException {Config config = ConfigService.getConfig("application");
        config.addChangeListener(new ConfigChangeListener() {
            @Override
            public 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);
    }
}

咱们当初把 timeout 值从 200 改为 300，程序输入后果：

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

当初咱们把线程池和 Apollo 联合起来构建动静线程池，具备了上述常识编写起来并不简单。首先咱们用默认值构建一个线程池，而后线程池会监听 Apollo 对于相干配置项，如果相干配置有变动则刷新相干参数。第一步在 Apollo 配置核心设置三个线程池参数（本文没有设置回绝策略）：

第二步编写外围代码：

/**
 * 动静线程池工厂
 *
 * @author 
 *
 */
@Slf4j
@Component
public class DynamicThreadPoolFactory {
    private static final String NAME_SPACE = "threadpool-config";

    /** 线程执行器 **/
    private volatile ThreadPoolExecutor executor;

    /** 外围线程数 **/
    private Integer CORE_SIZE = 10;

    /** 最大值线程数 **/
    private Integer MAX_SIZE = 20;

    /** 期待队列长度 **/
    private Integer QUEUE_SIZE = 2000;

    /** 线程存活工夫 **/
    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<Runnable> queueToUse = new LinkedBlockingQueue<Runnable>(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() {
            @Override
            public 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("批改外围线程数 key={},value={}", key, newValue);
        }
        if (KeysEnum.MAX_SIZE.getNodeKey().equals(key)) {executor.setMaximumPoolSize(Integer.valueOf(newValue));
            log.info("批改最大线程数 key={},value={}", key, newValue);
        }
        if (KeysEnum.KEEP_ALIVE_TIME.getNodeKey().equals(key)) {executor.setKeepAliveTime(Integer.valueOf(newValue), TimeUnit.MILLISECONDS);
            log.info("批改沉闷工夫 key={},value={}", key, newValue);
        }
    }

    public ThreadPoolExecutor getExecutor(String threadName) {return executor;}

    enum KeysEnum {CORE_SIZE("coreSize", "外围线程数"),

        MAX_SIZE("maxSize", "最大线程数"),

        KEEP_ALIVE_TIME("keepAliveTime", "线程沉闷工夫")

        ;

        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;}
    }
}

/**
 * 动静线程池执行器
 *
 * @author 
 *
 */
@Component
public class DynamicThreadExecutor {

    @Resource
    private 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联合 VisualVM 察看线程数：

/**
 * 动静线程池测试
 *
 * @author 
 *
 */
public class DynamicThreadExecutorTest extends BaseTest {

    @Resource
    private DynamicThreadExecutor dynamicThreadExecutor;

    /**
     * -Dapp.id=myApp -Denv=DEV -Dapollo.cluster=default -Ddev_meta=http://localhost:8080
     *
     * myApp+DEV+default+thread-pool
     */
    @Test
    public void testExecute() throws InterruptedException {while (true) {dynamicThreadExecutor.execute("bizName", new Runnable() {
                @Override
                public void run() {System.out.println("bizInfo");
                }
            });
            TimeUnit.SECONDS.sleep(1);
        }
    }
}

咱们在配置核心批改配置项把外围线程数设置为 50，最大线程数设置为 100：

通过 VisualVM 能够察看到线程数显著回升：

本文咱们首先介绍了线程池基础知识，包含七大参数和四个回绝策略，随后咱们介绍了 Apollo 配置核心的原理和利用，最初咱们将线程池和配置核心相结合，实现了动静调整线程数的成果，心愿本文对大家有所帮忙。

关于线程池:NacosThreadPoolExecutor构建动态线程池

0 文章概述

1 线程池根底

1.1 七个参数

corePoolSize

workQueue

maximumPoolSize

keepAliveTime

unit

threadFactory

handler

1.2 四种回绝策略

(1) AbortPolicy

(2) CallerRunsPolicy

(3) DiscardOldestPolicy

(4) DiscardPolicy

1.3 批改参数

(1) setCorePoolSize

(2) setMaximumPoolSize

(3) setKeepAliveTime

(4) setRejectedExecutionHandler

2 Apollo 配置核心

2.1 外围原理

2.2 实例剖析

2.2.1 服务端装置

2.2.2 应用程序

(1) 引入依赖

(2) 简略实例

(3) 监听实例

3 动静线程池

4 文章总结

Just My Socks（注册教程内含优惠码）

关于线程池:NacosThreadPoolExecutor构建动态线程池

0 文章概述

1 线程池根底

1.1 七个参数

corePoolSize

workQueue

maximumPoolSize

keepAliveTime

unit

threadFactory

handler

1.2 四种回绝策略

(1) AbortPolicy

(2) CallerRunsPolicy

(3) DiscardOldestPolicy

(4) DiscardPolicy

1.3 批改参数

(1) setCorePoolSize

(2) setMaximumPoolSize

(3) setKeepAliveTime

(4) setRejectedExecutionHandler

2 Apollo 配置核心

2.1 外围原理

2.2 实例剖析

2.2.1 服务端装置

2.2.2 应用程序

(1) 引入依赖

(2) 简略实例

(3) 监听实例

3 动静线程池

4 文章总结

Just My Socks（注册教程 内含优惠码）

Just My Socks（注册教程内含优惠码）