Spring Boot線程池

前言

前兩天做項目的時候，想提高一下插入表的性能優化，因爲是兩張表，先插舊的表，緊接着插新的表，一萬多條數據就有點慢了

後面就想到了線程池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，直接使用註解啓用

使用步驟

先創建一個線程池的配置，讓Spring Boot加載，用來定義如何創建一個ThreadPoolTaskExecutor，要使用@Configuration和@EnableAsync這兩個註解，表示這是個配置類，並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
        executor.setCorePoolSize(corePoolSize);
        //配置最大線程數
        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已經達到max size的時候，如何處理新任務
        // CALLER_RUNS：不在新線程中執行任務，而是有調用者所在的線程來執行
        executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
        //執行初始化
        executor.initialize();
        return executor;
    }
}
@Value是我配置在application.properties，可以參考配置，自由定義

# 異步線程配置
# 配置核心線程數
async.executor.thread.core_pool_size = 5
# 配置最大線程數
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-
創建一個Service接口，是異步線程的接口
public interface AsyncService {
    /**
     * 執行異步任務
     * 可以根據需求，自己加參數擬定，我這裏就做個測試演示
     */
    void executeAsync();
}
實現類
@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("可以在這裏執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()方法上增加註解@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方法創建的

接下來就是在Controller裏或者是哪裏通過註解@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
可以在這裏執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
可以在這裏執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
可以在這裏執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
可以在這裏執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
可以在這裏執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

通過以上日誌可以發現，[async-service-]是有多個線程的，顯然已經在我們配置的線程池中執行了，並且每次請求中，controller的起始和結束日誌都是連續打印的，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行；

雖然我們已經用上了線程池，但是還不清楚線程池當時的情況，有多少線程在執行，多少在隊列中等待呢？這裏我創建了一個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、已完成數、活躍線程數，隊列大小都打印出來了，然後Override了父類的execute、submit等方法，在裏面調用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誌中；

修改ExecutorConfig.java的asyncServiceExecutor方法，將ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor()改爲ThreadPoolTaskExecutor executor = new VisiableThreadPoolTaskExecutor()
@Bean(name = "asyncServiceExecutor")
    public Executor asyncServiceExecutor() {
        logger.info("start asyncServiceExecutor");
        //在這裏修改
        ThreadPoolTaskExecutor executor = new VisiableThreadPoolTaskExecutor();
        //配置核心線程數
        executor.setCorePoolSize(corePoolSize);
        //配置最大線程數
        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已經達到max size的時候，如何處理新任務
        // CALLER_RUNS：不在新線程中執行任務，而是有調用者所在的線程來執行
        executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
        //執行初始化
        executor.initialize();
        return executor;
    }
再次啓動該工程測試
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
可以在這裏執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
可以在這裏執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
可以在這裏執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
可以在這裏執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
注意這一行日誌：
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，調用的是submit(Callable task)這個方法，當前已經提交了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瞭然；