SpringBoot 線程池，這也太好用了！
來源：blog.csdn.net/m0_37701381/
article/details/81072774
前言 使用步驟
前兩天做項目的時候，想提高一下插入表的性能優(yōu)化，因為是兩張表，先插舊的表，緊接著插新的表，一萬多條數(shù)據(jù)就有點慢了
后面就想到了線程池
ThreadPoolExecutor，而用的是Spring Boot項目，可以用Spring提供的對ThreadPoolExecutor封裝的線程池ThreadPoolTaskExecutor，直接使用注解啟用
使用步驟
先創(chuàng)建一個線程池的配置，讓Spring Boot加載，用來定義如何創(chuàng)建一個ThreadPoolTaskExecutor，要使用@Configuration和@EnableAsync這兩個注解，表示這是個配置類，并且是線程池的配置類
@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();
//配置核心線程數(shù)
executor.setCorePoolSize(corePoolSize);
//配置最大線程數(shù)
executor.setMaxPoolSize(maxPoolSize);
//配置隊列大小
executor.setQueueCapacity(queueCapacity);
//配置線程池中的線程的名稱前綴
executor.setThreadNamePrefix(namePrefix);
// rejection-policy：當pool已經(jīng)達到max size的時候，如何處理新任務
// CALLER_RUNS：不在新線程中執(zhí)行任務，而是有調(diào)用者所在的線程來執(zhí)行
executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
//執(zhí)行初始化
executor.initialize();
return executor;
}
}
@Value是我配置在application.properties，可以參考配置，自由定義
> 推薦下自己做的 Spring Cloud 的實戰(zhàn)項目：
>
> <https://github.com/YunaiV/onemall>
# 異步線程配置
# 配置核心線程數(shù)
async.executor.thread.core_pool_size = 5
# 配置最大線程數(shù)
async.executor.thread.max_pool_size = 5
# 配置隊列大小
async.executor.thread.queue_capacity = 99999
# 配置線程池中的線程的名稱前綴
async.executor.thread.name.prefix = async-service-
創(chuàng)建一個Service接口，是異步線程的接口
public interface AsyncService {
/** * 執(zhí)行異步任務 * 可以根據(jù)需求，自己加參數(shù)擬定，我這里就做個測試演示 */
void executeAsync();
}
實現(xiàn)類
@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("異步線程要做的事情");
System.out.println("可以在這里執(zhí)行批量插入等耗時的事情");
logger.info("end executeAsync");
}
}
將Service層的服務異步化，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方法進入的線程池是asyncServiceExecutor方法創(chuàng)建的
接下來就是在Controller里或者是哪里通過注解@Autowired注入這個Service
@Autowired
private AsyncService asyncService;
@GetMapping("/async")
public void async(){
asyncService.executeAsync();
}
用postmain或者其他工具來多次測試請求一下
2018-07-16 22:15:47.655 INFO 10516 --- [async-service-5] c.u.d.e.executor.impl.AsyncServiceImpl : start executeAsync
異步線程要做的事情
可以在這里執(zhí)行批量插入等耗時的事情
2018-07-16 22:15:47.655 INFO 10516 --- [async-service-5] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2018-07-16 22:15:47.770 INFO 10516 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl : start executeAsync
異步線程要做的事情
可以在這里執(zhí)行批量插入等耗時的事情
2018-07-16 22:15:47.770 INFO 10516 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2018-07-16 22:15:47.816 INFO 10516 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl : start executeAsync
異步線程要做的事情
可以在這里執(zhí)行批量插入等耗時的事情
2018-07-16 22:15:47.816 INFO 10516 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2018-07-16 22:15:48.833 INFO 10516 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl : start executeAsync
異步線程要做的事情
可以在這里執(zhí)行批量插入等耗時的事情
2018-07-16 22:15:48.834 INFO 10516 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2018-07-16 22:15:48.986 INFO 10516 --- [async-service-4] c.u.d.e.executor.impl.AsyncServiceImpl : start executeAsync
異步線程要做的事情
可以在這里執(zhí)行批量插入等耗時的事情
2018-07-16 22:15:48.987 INFO 10516 --- [async-service-4] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
通過以上日志可以發(fā)現(xiàn)，[async-service-]是有多個線程的，顯然已經(jīng)在我們配置的線程池中執(zhí)行了，并且每次請求中，controller的起始和結(jié)束日志都是連續(xù)打印的，表明每次請求都快速響應了，而耗時的操作都留給線程池中的線程去異步執(zhí)行；
雖然我們已經(jīng)用上了線程池，但是還不清楚線程池當時的情況，有多少線程在執(zhí)行，多少在隊列中等待呢？這里我創(chuàng)建了一個ThreadPoolTaskExecutor的子類，在每次提交線程的時候都會將當前線程池的運行狀況打印出來
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());
}
@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方法中將任務總數(shù)、已完成數(shù)、活躍線程數(shù)，隊列大小都打印出來了，然后Override了父類的execute、submit等方法，在里面調(diào)用showThreadPoolInfo方法，這樣每次有任務被提交到線程池的時候，都會將當前線程池的基本情況打印到日志中；
修改ExecutorConfig.java的asyncServiceExecutor方法，將ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor()改為ThreadPoolTaskExecutor executor = new VisiableThreadPoolTaskExecutor()
@Bean(name = "asyncServiceExecutor")
public Executor asyncServiceExecutor() {
logger.info("start asyncServiceExecutor");
//在這里修改
ThreadPoolTaskExecutor executor = new VisiableThreadPoolTaskExecutor();
//配置核心線程數(shù)
executor.setCorePoolSize(corePoolSize);
//配置最大線程數(shù)
executor.setMaxPoolSize(maxPoolSize);
//配置隊列大小
executor.setQueueCapacity(queueCapacity);
//配置線程池中的線程的名稱前綴
executor.setThreadNamePrefix(namePrefix);
// rejection-policy：當pool已經(jīng)達到max size的時候，如何處理新任務
// CALLER_RUNS：不在新線程中執(zhí)行任務，而是有調(diào)用者所在的線程來執(zhí)行
executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
//執(zhí)行初始化
executor.initialize();
return executor;
}
再次啟動該工程測試
2018-07-16 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]
2018-07-16 22:23:30.952 INFO 14088 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl : start executeAsync
異步線程要做的事情
可以在這里執(zhí)行批量插入等耗時的事情
2018-07-16 22:23:30.953 INFO 14088 --- [async-service-1] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2018-07-16 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]
2018-07-16 22:23:31.353 INFO 14088 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl : start executeAsync
異步線程要做的事情
可以在這里執(zhí)行批量插入等耗時的事情
2018-07-16 22:23:31.353 INFO 14088 --- [async-service-2] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2018-07-16 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]
2018-07-16 22:23:31.929 INFO 14088 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl : start executeAsync
異步線程要做的事情
可以在這里執(zhí)行批量插入等耗時的事情
2018-07-16 22:23:31.930 INFO 14088 --- [async-service-3] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
2018-07-16 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]
2018-07-16 22:23:32.498 INFO 14088 --- [async-service-4] c.u.d.e.executor.impl.AsyncServiceImpl : start executeAsync
異步線程要做的事情
可以在這里執(zhí)行批量插入等耗時的事情
2018-07-16 22:23:32.499 INFO 14088 --- [async-service-4] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
注意這一行日志：
2018-07-16 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]
這說明提交任務到線程池的時候，調(diào)用的是submit(Callable task)這個方法，當前已經(jīng)提交了3個任務，完成了3個，當前有0個線程在處理任務，還剩0個任務在隊列中等待，線程池的基本情況一路了然；
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