Spring Boot使用線程池處理上萬條數據插入功能
# 前言
前兩天做項目的時候,想提高一下插入表的性能優化,因為是兩張表,先插舊的表,緊接著插新的表,一萬多條數據就有點慢瞭
後面就想到瞭線程池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,直接使用註解啟用
# 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,我這裡就做個測試演示 */ 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("可以在這裡執行批量插入等耗時的事情"); logger.info("end executeAsync"); } }
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裡或者是哪裡通過註解@Autowired註入這個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
異步線程要做的事情
可以在這裡執行批量插入等耗時的事情
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
異步線程要做的事情
可以在這裡執行批量插入等耗時的事情
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
異步線程要做的事情
可以在這裡執行批量插入等耗時的事情
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
異步線程要做的事情
可以在這裡執行批量插入等耗時的事情
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
異步線程要做的事情
可以在這裡執行批量插入等耗時的事情
2022-07-16 22:15:48.987 INFO 10516 — [async-service-4] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
通過以上日志可以發現,[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瞭,並且每次請求中,controller的起始和結束日志都是連續打印的,表明每次請求都快速響應瞭,而耗時的操作都留給線程池中的線程去異步執行;
雖然我們已經用上瞭線程池,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?這裡我創建瞭一個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: 騰騰 * @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方法中將任務總數、已完成數、活躍線程數,隊列大小都打印出來瞭,然後Override瞭父類的execute、submit等方法,在裡面調用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"); //在這裡修改 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; }
再次啟動該工程測試
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
異步線程要做的事情
可以在這裡執行批量插入等耗時的事情
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
異步線程要做的事情
可以在這裡執行批量插入等耗時的事情
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
異步線程要做的事情
可以在這裡執行批量插入等耗時的事情
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
異步線程要做的事情
可以在這裡執行批量插入等耗時的事情
2022-07-16 22:23:32.499 INFO 14088 — [async-service-4] c.u.d.e.executor.impl.AsyncServiceImpl : end executeAsync
註意這一行日志:
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]
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,當前已經提交瞭3個任務,完成瞭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;
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