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;

到此這篇關於Spring Boot使用線程池處理上萬條數據插入的文章就介紹到這瞭,更多相關Spring Boot線程池處理上萬條數據插入內容請搜索WalkonNet以前的文章或繼續瀏覽下面的相關文章希望大傢以後多多支持WalkonNet!

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