Spring Boot使用线程池处理上万条数据插入功能
目录
- # 前言
- # 使用步骤
# 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 @EnableAsync public 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
# 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
@Service public 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"); } }
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(); }
日志打印
2022-07-16 22:15:47.655 INFO 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
2022-07-16 22:15:47.655 INFO 10516 --- [async-service-5] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2022-07-16 22:15:47.770 INFO 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
2022-07-16 22:15:47.770 INFO 10516 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2022-07-16 22:15:47.816 INFO 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
2022-07-16 22:15:47.816 INFO 10516 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2022-07-16 22:15:48.833 INFO 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
2022-07-16 22:15:48.834 INFO 10516 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2022-07-16 22:15:48.986 INFO 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
2022-07-16 22:15:48.987 INFO 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: 腾腾 * @Date: 2022/7/16/0016 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()); } @Override public void execute(Runnable task) { showThreadPoolInfo("1. do execute"); super.execute(task); } @Override public void execute(Runnable task, long startTimeout) { showThreadPoolInfo("2. do execute"); super.execute(task, startTimeout); } @Override public Future<?> submit(Runnable task) { showThreadPoolInfo("1. do submit"); return super.submit(task); } @Override public <T> Future<T> submit(Callable<T> task) { showThreadPoolInfo("2. do submit"); return super.submit(task); } @Override public ListenableFuture<?> submitListenable(Runnable task) { showThreadPoolInfo("1. do submitListenable"); return super.submitListenable(task); } @Override public <T> ListenableFuture<T> submitListenable(Callable<T> 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.java的asyncServiceExecutor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
2022-07-16 22:23:30.951 INFO 14088 --- [nio-8087-exec-2] u.d.e.e.i.VisiableThreadPoolTaskExecutor : async-service-, 2. do submit,taskCount [0], completedTaskCount [0], activeCount [0], queueSize [0]
2022-07-16 22:23:30.952 INFO 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
2022-07-16 22:23:30.953 INFO 14088 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2022-07-16 22:23:31.351 INFO 14088 --- [nio-8087-exec-3] u.d.e.e.i.VisiableThreadPoolTaskExecutor : async-service-, 2. do submit,taskCount [1], completedTaskCount [1], activeCount [0], queueSize [0]
2022-07-16 22:23:31.353 INFO 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
2022-07-16 22:23:31.353 INFO 14088 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2022-07-16 22:23:31.927 INFO 14088 --- [nio-8087-exec-5] u.d.e.e.i.VisiableThreadPoolTaskExecutor : async-service-, 2. do submit,taskCount [2], completedTaskCount [2], activeCount [0], queueSize [0]
2022-07-16 22:23:31.929 INFO 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
2022-07-16 22:23:31.930 INFO 14088 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2022-07-16 22:23:32.496 INFO 14088 --- [nio-8087-exec-7] u.d.e.e.i.VisiableThreadPoolTaskExecutor : async-service-, 2. do submit,taskCount [3], completedTaskCount [3], activeCount [0], queueSize [0]
2022-07-16 22:23:32.498 INFO 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
2022-07-16 22:23:32.499 INFO 14088 --- [async-service-4] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
注意这一行日志:
2022-07-16 22:23:32.496 INFO 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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