线程池的使用案例一

线程池的使用案例一_第1张图片

一、配置线程池

1、不推荐的方式

ExecutorService executorService = Executors.newFixedThreadPool();  // 创建⼀个固定⼤⼩的线程池,可控制并发的线程数,超出的线程会在队列中等待;
ExecutorService executorService = Executors.newCachedThreadPool();  // 创建⼀个可缓存的线程池,若线程数超过处理所需,缓存⼀段时间后会回收,若线程数不够,则新建线程;
ExecutorService executorService = Executors.newSingleThreadExecutor();  // 创建单个线程数的线程池,它可以保证先进先出的执⾏顺序;
ExecutorService executorService = Executors.newScheduledThreadPool();  // 创建⼀个可以执⾏延迟任务的线程池;
ExecutorService executorService = Executors.newSingleThreadScheduledExecutor();  // 创建⼀个单线程的可以执⾏延迟任务的线程池;
ExecutorService executorService = Executors.newWorkStealingPool();  // 创建⼀个抢占式执⾏的线程池(任务执⾏顺序不确定)【JDK1.8 添加】。

2、原始方式

import java.util.concurrent.ArrayBlockingQueue;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.ThreadFactory;
import java.util.concurrent.ThreadPoolExecutor;
import java.util.concurrent.TimeUnit;

public class ThreadPoolUtil {

    // 核心线程数
    private static int corePoolSize =10;
    // 最大线程数
    private static int maxmumPoolSize =30;
    // 空闲存活时间
    private static long keepTime = 30;
    // 时间单位
    private static TimeUnit unit = TimeUnit.SECONDS;
    // 任务队列
    private static ArrayBlockingQueue blockingQueue = new ArrayBlockingQueue(1000);
    // 创建线程工厂
    private static ThreadFactory threadFactory1 =  Executors.defaultThreadFactory();

    private static ThreadPoolExecutor.AbortPolicy policy = new ThreadPoolExecutor.AbortPolicy();

    public static void main(String[] args) throws Exception{

        ExecutorService executorService1 = Executors.newFixedThreadPool(10);
        ExecutorService executorService = new ThreadPoolExecutor(
                corePoolSize,
                maxmumPoolSize,
                keepTime,
                unit,
                blockingQueue,
                threadFactory1,
                policy);
        executorService.execute(new Runnable(){
            public void run(){
                System.out.println("new Runnable!");
            };
        });
         /*
          //线程池拒接收新提交的任务,同时立马关闭线程池,线程池里的任务不再执行。
          executorService.shutdownNow();
         */
         /*
          //线程池拒接收新提交的任务,同时等待线程池里的任务执行完毕后关闭线程池。
          executorService.shutdown();
         */

        // 这个方法会使线程等待timeout时长,当超过timeout时间后,会监测ExecutorService是否已经关闭,若关闭则返回true,
        // 否则返回false,一般情况下会和shutdown方法组合使用。
        boolean boole = executorService.awaitTermination(3,TimeUnit.SECONDS);
    }

}

3、Spring的方式

import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.scheduling.annotation.EnableAsync;
import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;

import java.util.concurrent.ThreadPoolExecutor;
import java.util.concurrent.TimeUnit;

@Configuration
@EnableAsync  // 同一个类的中调用无效
public class ThreadPoolConfig {

    // 获取服务器的cpu个数
    private static final int CPU_COUNT = Runtime.getRuntime().availableProcessors(); // 获取cpu个数
    // 核心线程数
    private static final int COUR_SIZE = CPU_COUNT * 2;
    // 最大线程数
    private static final int MAX_COUR_SIZE = CPU_COUNT * 4;
    // 队列容量
    private static final int QUEUE_SIZE = CPU_COUNT * 4 * 4;
    // 空闲存活时间
    private static long keepTime = 30;
    // 时间单位
    private static TimeUnit unit = TimeUnit.SECONDS;

    // 任务队列
    // private static ArrayBlockingQueue blockingQueue = new ArrayBlockingQueue(10*10000);

    @Bean(name = "asyncDownLoadExcelExecutor")
    public ThreadPoolTaskExecutor threadPoolTaskExecutor() {
        // ThreadPoolTaskScheduler
        ThreadPoolTaskExecutor threadPoolTaskExecutor = new ThreadPoolTaskExecutor();
        // 设置核心线程数
        threadPoolTaskExecutor.setCorePoolSize(COUR_SIZE);
        // 配置最大线程数
        threadPoolTaskExecutor.setMaxPoolSize(MAX_COUR_SIZE);
        // 配置队列容量(这里设置成最大线程数的四倍)
        threadPoolTaskExecutor.setQueueCapacity(QUEUE_SIZE);
        // 默认是 60s,这里设置 30s
        threadPoolTaskExecutor.setKeepAliveSeconds(30);
        // 给线程池设置名称
        threadPoolTaskExecutor.setThreadNamePrefix("async-download-excel");
        threadPoolTaskExecutor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());// 设置任务的拒绝策略
        return threadPoolTaskExecutor;
    }

    @Bean(name = "asyncUploadExcelExecutor")
    public ThreadPoolTaskExecutor asyncUploadExcelExecutor() {
        ThreadPoolTaskExecutor threadPoolTaskExecutor =  new ThreadPoolTaskExecutor();
        // 设置核心线程数
        threadPoolTaskExecutor.setCorePoolSize(5);
        // 设置最大线程数
        threadPoolTaskExecutor.setMaxPoolSize(10);
        // 设置阻塞队列大小
        threadPoolTaskExecutor.setQueueCapacity(999);
        // 默认是 60s,这里设置30s
        threadPoolTaskExecutor.setKeepAliveSeconds(30);
        // 设置线程池中线程名前缀
        threadPoolTaskExecutor.setThreadNamePrefix("async-upload-excel");
        //当达到 MaxPoolSize 不再调用新线程,用调用者所在线程之星异步任务。
        threadPoolTaskExecutor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
        return threadPoolTaskExecutor;
    }

}

二、百万数据的导出(生成多个文件,统一压缩)

2.1、引入依赖

 
    org.apache.poi
    poi-ooxml
    4.0.1
 

2.2、实体类

public class PersonEntity {

    private Long id;

    private String name;

    private Integer age;

    private String address;

    public Long getId() {
        return id;
    }

    public void setId(Long id) {
        this.id = id;
    }

    public String getName() {
        return name;
    }

    public void setName(String name) {
        this.name = name;
    }

    public Integer getAge() {
        return age;
    }

    public void setAge(Integer age) {
        this.age = age;
    }

    public String getAddress() {
        return address;
    }

    public void setAddress(String address) {
        this.address = address;
    }
}

2.3、Controller

    /**
     * 导出方法
     * 此处应注意 线程池拒绝策略 抛出的异常,若任务过大,则走降级方法。
     */
    public void exportMillionData(HttpServletRequest request, HttpServletResponse response) throws IOException {
        // 表格表头
        String[] TITLE = new String[]{ "姓名", "年龄", "地址"};
        // 获取数据进行分割
        int count = 100*10000; // personService.count();
        int pageSize = 50000;
        // 获取批次数
        int tableNum = count % pageSize == 0 ? (count / pageSize) : (count / pageSize) + 1;

        // 将数据多线程方式导出到excel
        CountDownLatch latch = new CountDownLatch(tableNum);
        for (int i = 0; i < tableNum; i++) {
          exportDataToExcel(latch, TITLE, pageSize, i);
        }
        try {
            // 阻塞 —— 等待全部执行完
            latch.await();
            // 压缩响应
            // 处理中文名不显示的问题
            String fileName = URLEncoder.encode("人员信息.zip", "UTF-8");
            response.setContentType("application/octet-stream;charset=UTF-8");
            response.setContentType("application/x-zip-compressed;charset=UTF-8");
            response.setHeader("Content-Disposition", "attachment;filename=" + fileName);
            response.addHeader("Pargam", "no-cache");
            response.addHeader("Cache-Control", "no-cache");
            response.addHeader("Access-Contro1-A11ow-0rigin", "*");
            File zip = ZipUtil.zip(new File("D://file/sys/"));
            ServletOutputStream output = response.getOutputStream();
            FileInputStream input = new FileInputStream(zip);
            byte[] buff = new byte[1024 * 10];
            int len = 0;
            while ((len = input.read(buff)) > -1) {
                output.write(buff, 0, len);
            }
            output.flush();
            output.close();
            if (zip.exists()) {
                zip.delete();
            }
        } catch (InterruptedException e){
            e.printStackTrace();
        }finally {
            FileUtil.deleteDir(new File("D://file/sys/"));
        }
    }

2.4、Service

    /**
     * 导出数据到 Excel
     * @param latch    锁
     * @param TITLE    表格头
     * @param pageSize 每个sheet的记录数
     * @param first    表格序号
     */
    @Async("asyncDownLoadExcelExecutor")
    public void exportDataToExcel(CountDownLatch latch, String[] TITLE, int pageSize, int first) throws IOException {
       //  IPage page = new Page();
       //  page.setCurrent(i + 1);
       //  page.setSize(pageSize);
        List records = new ArrayList<>();// personService.page(page).getRecords();
        int start = first * pageSize;
        int end = start + pageSize;
        String fileName = start + "-" + end + "人员信息" + ".xlsx";
        // 写出到本地的excel文件中
        SXSSFWorkbook wb = new SXSSFWorkbook();
        Sheet sheet = wb.createSheet(fileName);
        Row row = sheet.createRow(0);
        Cell cell = null;
        // 写标题
        for (int j = 0; j < TITLE.length; j++) {
            cell = row.createCell(j);
            cell.setCellValue(TITLE[j]);
        }
        // 写内容
        int rowNum = 1;
        for (PersonEntity entity : records) {
            row = sheet.createRow(rowNum++);
            row.createCell(0).setCellValue(entity.getName());
            row.createCell(1).setCellValue(entity.getAge());
            row.createCell(2).setCellValue(entity.getAddress());
        }
        fileName = new String(fileName.getBytes(), "UTF-8");
        File file = new File("D://file/sys/" + fileName);
        if (!file.exists()) {
            file.getParentFile().mkdirs();
        }
        FileOutputStream outputStream = new FileOutputStream(file);
        wb.write(outputStream);
        outputStream.flush();
        outputStream.close();
        latch.countDown();
    }

三、多线程插入数据 (类似分布式的TCC)

1、引入依赖


    org.springframework
    spring-jdbc
    5.2.9.RELEASE

2、定义线程池

@Bean(name = "asyncInsertDataExecutor")
public ThreadPoolTaskExecutor asyncUploadExcelExecutor() {
    ThreadPoolTaskExecutor threadPoolTaskExecutor =  new ThreadPoolTaskExecutor();
    // 设置核心线程数
    threadPoolTaskExecutor.setCorePoolSize(5);
    // 设置最大线程数
    threadPoolTaskExecutor.setMaxPoolSize(10);
    // 设置阻塞队列大小
    threadPoolTaskExecutor.setQueueCapacity(999);
    // 默认是 60s,这里设置30s
    threadPoolTaskExecutor.setKeepAliveSeconds(30);
    // 设置线程池中线程名前缀
    threadPoolTaskExecutor.setThreadNamePrefix("async-upload-excel");
    //当达到 MaxPoolSize 不再调用新线程,用调用者所在线程之星异步任务。
    threadPoolTaskExecutor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
    return threadPoolTaskExecutor;
}

3、Controller

@Autowired
private PlatformTransactionManager transactionManager;

public String insertData() throws InterruptedException {
    CountDownLatch latch = new CountDownLatch(10);
    AtomicReference rollback = new AtomicReference<>(false);
    // 先在开启多线程外面,定义一个同步集合:
    List transactionStatuses = Collections.synchronizedList(new ArrayList<>());
        // 调用线程方法
        for(int i=0;i<10;i++){
            exportDataToExcel(latch,rollback,transactionStatuses,new ArrayList<>());
        }
    // 阻塞 —— 等待全部执行完
    latch.await();
    // 如果出错回滚事务
    if (rollback.get()) {
        transactionStatuses.forEach(status -> transactionManager.rollback(status));
        return " 插入失败 ";
    } else {
        transactionStatuses.forEach(status -> transactionManager.commit(status));
        return " 插入成功 ";
    }
}

4、Service

@Async("asyncInsertDataExecutor")
public void exportDataToExcel(CountDownLatch latch,AtomicReference rollback,List transactionStatuses,List list) {
    try {
        // 开启事务(可封装成方法)
        DefaultTransactionDefinition def = new DefaultTransactionDefinition();
        def.setPropagationBehavior(TransactionDefinition.PROPAGATION_REQUIRES_NEW);
        TransactionStatus status = transactionManager.getTransaction(def);
        transactionStatuses.add(status);

        // ....  业务代码
        list.clear();

    } catch (Exception e) {
        rollback.set(true);
        e.printStackTrace();
    }
    latch.countDown();
} 
  

                            
                        
                    
                    
                    

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