SpringBoot|SpringBoot 项目中创建线程池

【SpringBoot|SpringBoot 项目中创建线程池】 前言:
前两天做项目的时候,想提高一下插入表的性能优化,因为是两张表,先插旧的表,紧接着插新的表,一万多条数据就有点慢了

后面就想到了线程池ThreadPoolExecutor,而用的是Spring Boot项目,可以用Spring提供的对ThreadPoolExecutor封装的线程池ThreadPoolTaskExecutor,直接使用注解启用
使用步骤:
先创建一个线程池的配置,让Spring Boot加载,用来定义如何创建一个ThreadPoolTaskExecutor,要使用@Configuration和@EnableAsync这两个注解,表示这是个配置类,并且是线程池的配置类
@Configuration@EnableAsyncpublic class ExecutorConfig {private static final Logger logger = LoggerFactory.getLogger(ExecutorConfig.class); @Value("${async.executor.thread.core_pool_size}")private int corePoolSize; @Value("${async.executor.thread.max_pool_size}")private int maxPoolSize; @Value("${async.executor.thread.queue_capacity}")private int queueCapacity; @Value("${async.executor.thread.name.prefix}")private String namePrefix; @Bean(name = "asyncServiceExecutor")public Executor asyncServiceExecutor() {logger.info("start asyncServiceExecutor"); ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor(); //配置核心线程数executor.setCorePoolSize(corePoolSize); //配置最大线程数executor.setMaxPoolSize(maxPoolSize); //配置队列大小executor.setQueueCapacity(queueCapacity); //配置线程池中的线程的名称前缀executor.setThreadNamePrefix(namePrefix); // rejection-policy:当pool已经达到max size的时候,如何处理新任务// CALLER_RUNS:不在新线程中执行任务,而是有调用者所在的线程来执行executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy()); //执行初始化executor.initialize(); return executor; }}

@Value是我配置在application.properties,可以参考配置,自由定义
> 推荐下自己做的 Spring Cloud 的实战项目:>> # 异步线程配置# 配置核心线程数async.executor.thread.core_pool_size = 5# 配置最大线程数async.executor.thread.max_pool_size = 5# 配置队列大小async.executor.thread.queue_capacity = 99999# 配置线程池中的线程的名称前缀async.executor.thread.name.prefix = async-service-

创建一个Service接口,是异步线程的接口
public interface AsyncService {/** * 执行异步任务 * 可以根据需求,自己加参数拟定,我这里就做个测试演示 */void executeAsync(); }

实现类:
@Servicepublic class AsyncServiceImpl implements AsyncService {private static final Logger logger = LoggerFactory.getLogger(AsyncServiceImpl.class); @Override@Async("asyncServiceExecutor")public void executeAsync() {logger.info("start executeAsync"); System.out.println("异步线程要做的事情"); System.out.println("可以在这里执行批量插入等耗时的事情"); logger.info("end executeAsync"); }}

将Service层的服务异步化,在executeAsync()方法上增加注解@Async("asyncServiceExecutor")asyncServiceExecutor方法是前面ExecutorConfig.java 中的方法名,表明executeAsync方法进入的线程池是asyncServiceExecutor方法创建的
接下来就是在Controller里或者是哪里通过注解@Autowired注入这个Service
@Autowiredprivate AsyncService asyncService; @GetMapping("/async")public void async(){asyncService.executeAsync(); }

用postmain或者其他工具来多次测试请求一下
2018-07-16 22:15:47.655INFO 10516 --- [async-service-5] c.u.d.e.executor.impl.AsyncServiceImpl: start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:15:47.655INFO 10516 --- [async-service-5] c.u.d.e.executor.impl.AsyncServiceImpl: end executeAsync
2018-07-16 22:15:47.770INFO 10516 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl: start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:15:47.770INFO 10516 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl: end executeAsync
2018-07-16 22:15:47.816INFO 10516 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl: start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:15:47.816INFO 10516 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl: end executeAsync
2018-07-16 22:15:48.833INFO 10516 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl: start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:15:48.834INFO 10516 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl: end executeAsync
2018-07-16 22:15:48.986INFO 10516 --- [async-service-4] c.u.d.e.executor.impl.AsyncServiceImpl: start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:15:48.987INFO 10516 --- [async-service-4] c.u.d.e.executor.impl.AsyncServiceImpl: end executeAsync
通过以上日志可以发现,[async-service-]是有多个线程的,显然已经在我们配置的线程池中执行了,并且每次请求中,controller的起始和结束日志都是连续打印的,表明每次请求都快速响应了,而耗时的操作都留给线程池中的线程去异步执行;
虽然我们已经用上了线程池,但是还不清楚线程池当时的情况,有多少线程在执行,多少在队列中等待呢?这里我创建了一个ThreadPoolTaskExecutor的子类,在每次提交线程的时候都会将当前线程池的运行状况打印出来
import org.slf4j.Logger; import org.slf4j.LoggerFactory; import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor; import org.springframework.util.concurrent.ListenableFuture; import java.util.concurrent.Callable; import java.util.concurrent.Future; import java.util.concurrent.ThreadPoolExecutor; /** * @Author: ChenBin * @Date: 2018/7/16/0016 22:19 */public class VisiableThreadPoolTaskExecutor extends ThreadPoolTaskExecutor {private static final Logger logger = LoggerFactory.getLogger(VisiableThreadPoolTaskExecutor.class); private void showThreadPoolInfo(String prefix) {ThreadPoolExecutor threadPoolExecutor = getThreadPoolExecutor(); if (null == threadPoolExecutor) {return; }logger.info("{}, {},taskCount [{}], completedTaskCount [{}], activeCount [{}], queueSize [{}]",this.getThreadNamePrefix(),prefix,threadPoolExecutor.getTaskCount(),threadPoolExecutor.getCompletedTaskCount(),threadPoolExecutor.getActiveCount(),threadPoolExecutor.getQueue().size()); }@Overridepublic void execute(Runnable task) {showThreadPoolInfo("1. do execute"); super.execute(task); }@Overridepublic void execute(Runnable task, long startTimeout) {showThreadPoolInfo("2. do execute"); super.execute(task, startTimeout); }@Overridepublic Future submit(Runnable task) {showThreadPoolInfo("1. do submit"); return super.submit(task); }@Overridepublic Future submit(Callable task) {showThreadPoolInfo("2. do submit"); return super.submit(task); }@Overridepublic ListenableFuture submitListenable(Runnable task) {showThreadPoolInfo("1. do submitListenable"); return super.submitListenable(task); }@Overridepublic ListenableFuture submitListenable(Callable task) {showThreadPoolInfo("2. do submitListenable"); return super.submitListenable(task); }}

如上所示,showThreadPoolInfo方法中将任务总数、已完成数、活跃线程数,队列大小都打印出来了,然后Override了父类的execute、submit等方法,在里面调用showThreadPoolInfo方法,这样每次有任务被提交到线程池的时候,都会将当前线程池的基本情况打印到日志中;
修改ExecutorConfig.javaasyncServiceExecutor方法,将ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor()改为ThreadPoolTaskExecutor executor = new VisiableThreadPoolTaskExecutor()
@Bean(name = "asyncServiceExecutor")public Executor asyncServiceExecutor() {logger.info("start asyncServiceExecutor"); //在这里修改ThreadPoolTaskExecutor executor = new VisiableThreadPoolTaskExecutor(); //配置核心线程数executor.setCorePoolSize(corePoolSize); //配置最大线程数executor.setMaxPoolSize(maxPoolSize); //配置队列大小executor.setQueueCapacity(queueCapacity); //配置线程池中的线程的名称前缀executor.setThreadNamePrefix(namePrefix); // rejection-policy:当pool已经达到max size的时候,如何处理新任务// CALLER_RUNS:不在新线程中执行任务,而是有调用者所在的线程来执行executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy()); //执行初始化executor.initialize(); return executor; }

再次启动该工程测试
2018-07-16 22:23:30.951INFO 14088 --- [nio-8087-exec-2] u.d.e.e.i.VisiableThreadPoolTaskExecutor : async-service-, 2. do submit,taskCount [0], completedTaskCount [0], activeCount [0], queueSize [0]
2018-07-16 22:23:30.952INFO 14088 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl: start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:23:30.953INFO 14088 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl: end executeAsync
2018-07-16 22:23:31.351INFO 14088 --- [nio-8087-exec-3] u.d.e.e.i.VisiableThreadPoolTaskExecutor : async-service-, 2. do submit,taskCount [1], completedTaskCount [1], activeCount [0], queueSize [0]
2018-07-16 22:23:31.353INFO 14088 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl: start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:23:31.353INFO 14088 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl: end executeAsync
2018-07-16 22:23:31.927INFO 14088 --- [nio-8087-exec-5] u.d.e.e.i.VisiableThreadPoolTaskExecutor : async-service-, 2. do submit,taskCount [2], completedTaskCount [2], activeCount [0], queueSize [0]
2018-07-16 22:23:31.929INFO 14088 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl: start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:23:31.930INFO 14088 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl: end executeAsync
2018-07-16 22:23:32.496INFO 14088 --- [nio-8087-exec-7] u.d.e.e.i.VisiableThreadPoolTaskExecutor : async-service-, 2. do submit,taskCount [3], completedTaskCount [3], activeCount [0], queueSize [0]
2018-07-16 22:23:32.498INFO 14088 --- [async-service-4] c.u.d.e.executor.impl.AsyncServiceImpl: start executeAsync
异步线程要做的事情
可以在这里执行批量插入等耗时的事情
2018-07-16 22:23:32.499INFO 14088 --- [async-service-4] c.u.d.e.executor.impl.AsyncServiceImpl: end executeAsync
注意这一行日志:
2018-07-16 22:23:32.496INFO 14088 --- [nio-8087-exec-7] u.d.e.e.i.VisiableThreadPoolTaskExecutor : async-service-, 2. do submit,taskCount [3], completedTaskCount [3], activeCount [0], queueSize [0]
这说明提交任务到线程池的时候,调用的是submit(Callable task)这个方法,当前已经提交了3个任务,完成了3个,当前有0个线程在处理任务,还剩0个任务在队列中等待,线程池的基本情况一路了然。
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