Spring線程池ThreadPoolTaskExecutor配置詳情,

來源:互聯網
上載者:User

Spring線程池ThreadPoolTaskExecutor配置詳情,

本文介紹了Spring線程池ThreadPoolTaskExecutor配置,分享給大家,具體如下:

1. ThreadPoolTaskExecutor配置

<!-- spring thread pool executor -->    <bean id="taskExecutor" class="org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor">  <!-- 線程池維護線程的最少數量 -->  <property name="corePoolSize" value="5" />  <!-- 允許的空閑時間 -->  <property name="keepAliveSeconds" value="200" />  <!-- 線程池維護線程的最大數量 -->  <property name="maxPoolSize" value="10" />  <!-- 緩衝隊列 -->  <property name="queueCapacity" value="20" />  <!-- 對拒絕task的處理策略 -->  <property name="rejectedExecutionHandler">   <bean class="java.util.concurrent.ThreadPoolExecutor$CallerRunsPolicy" />  </property> </bean>

屬性欄位說明

corePoolSize:線程池維護線程的最少數量

keepAliveSeconds:允許的空閑時間

maxPoolSize:線程池維護線程的最大數量

queueCapacity:緩衝隊列

rejectedExecutionHandler:對拒絕task的處理策略

2. execute(Runable)方法執行過程

如果此時線程池中的數量小於corePoolSize,即使線程池中的線程都處於空閑狀態,也要建立新的線程來處理被添加的任務。

如果此時線程池中的數量等於 corePoolSize,但是緩衝隊列 workQueue未滿,那麼任務被放入緩衝隊列。

如果此時線程池中的數量大於corePoolSize,緩衝隊列workQueue滿,並且線程池中的數量小於maxPoolSize,建新的線程來處理被添加的任務。

如果此時線程池中的數量大於corePoolSize,緩衝隊列workQueue滿,並且線程池中的數量等於maxPoolSize,那麼通過handler所指定的策略來處理此任務。也就是:處理任務的優先順序為:核心線程corePoolSize、任務隊列workQueue、最大線程 maximumPoolSize,如果三者都滿了,使用handler處理被拒絕的任務。

當線程池中的線程數量大於corePoolSize時,如果某線程空閑時間超過keepAliveTime,線程將被終止。這樣,線程池可以動態調整池中的線程數。

3. 範例程式碼

Junit Test

@RunWith(SpringJUnit4ClassRunner.class)@ContextConfiguration(classes = { MultiThreadConfig.class })public class MultiThreadTest { @Autowired private ThreadPoolTaskExecutor taskExecutor; @Autowired private MultiThreadProcessService multiThreadProcessService;  @Test public void test() {  int n = 20;  for (int i = 0; i < n; i++) {   taskExecutor.execute(new MultiThreadDemo(multiThreadProcessService));   System.out.println("int i is " + i + ", now threadpool active threads totalnum is " + taskExecutor.getActiveCount());  }    try {   System.in.read();  } catch (IOException e) {   throw new RuntimeException(e);  } }}

MultiThreadDemo

/** * 多線程並發處理demo * @author daniel.zhao * */public class MultiThreadDemo implements Runnable { private MultiThreadProcessService multiThreadProcessService;  public MultiThreadDemo() { }  public MultiThreadDemo(MultiThreadProcessService multiThreadProcessService) {  this.multiThreadProcessService = multiThreadProcessService; }  @Override public void run() {  multiThreadProcessService.processSomething(); }}

MultiThreadProcessService

@Servicepublic class MultiThreadProcessService { public static final Logger logger = Logger.getLogger(MultiThreadProcessService.class);  /**  * 預設處理流程耗時1000ms  */ public void processSomething() {  logger.debug("MultiThreadProcessService-processSomething" + Thread.currentThread() + "......start");  try {   Thread.sleep(1000);  } catch (InterruptedException e) {   throw new RuntimeException(e);  }  logger.debug("MultiThreadProcessService-processSomething" + Thread.currentThread() + "......end"); }}

MultiThreadConfig

 @Configuration @ComponentScan(basePackages = { "com.xxx.multithread" }) @ImportResource(value = { "classpath:config/application-task.xml" }) @EnableScheduling public class MultiThreadConfig { }

以上就是本文的全部內容,希望對大家的學習有所協助,也希望大家多多支援幫客之家。

聯繫我們

該頁面正文內容均來源於網絡整理,並不代表阿里雲官方的觀點,該頁面所提到的產品和服務也與阿里云無關,如果該頁面內容對您造成了困擾,歡迎寫郵件給我們,收到郵件我們將在5個工作日內處理。

如果您發現本社區中有涉嫌抄襲的內容,歡迎發送郵件至: info-contact@alibabacloud.com 進行舉報並提供相關證據,工作人員會在 5 個工作天內聯絡您,一經查實,本站將立刻刪除涉嫌侵權內容。

A Free Trial That Lets You Build Big!

Start building with 50+ products and up to 12 months usage for Elastic Compute Service

  • Sales Support

    1 on 1 presale consultation

  • After-Sales Support

    24/7 Technical Support 6 Free Tickets per Quarter Faster Response

  • Alibaba Cloud offers highly flexible support services tailored to meet your exact needs.