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完善积木报表的集成
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@ -0,0 +1,28 @@
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package cn.iocoder.yudao.module.pay.framework.job.config;
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import org.springframework.context.annotation.Bean;
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import org.springframework.context.annotation.Configuration;
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import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;
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import java.util.concurrent.ThreadPoolExecutor;
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@Configuration
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public class PayJobConfiguration {
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public static final String NOTIFY_THREAD_POOL_TASK_EXECUTOR = "NOTIFY_THREAD_POOL_TASK_EXECUTOR";
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@Bean(NOTIFY_THREAD_POOL_TASK_EXECUTOR)
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public ThreadPoolTaskExecutor notifyThreadPoolTaskExecutor() {
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ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
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executor.setCorePoolSize(8); // 设置核心线程数
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executor.setMaxPoolSize(16); // 设置最大线程数
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executor.setKeepAliveSeconds(60); // 设置空闲时间
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executor.setQueueCapacity(100); // 设置队列大小
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executor.setThreadNamePrefix("notify-task-"); // 配置线程池的前缀
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executor.setRejectedExecutionHandler(new ThreadPoolExecutor.CallerRunsPolicy());
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// 进行加载
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executor.initialize();
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return executor;
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}
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}
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@ -0,0 +1,4 @@
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/**
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* 占位
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*/
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package cn.iocoder.yudao.module.pay.framework.job.core;
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@ -0,0 +1,6 @@
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/**
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* 属于 pay 模块的 framework 封装
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*
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* @author 芋道源码
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*/
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package cn.iocoder.yudao.module.pay.framework;
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@ -36,6 +36,8 @@ import java.util.Objects;
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import java.util.concurrent.CountDownLatch;
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import java.util.concurrent.TimeUnit;
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import static cn.iocoder.yudao.module.pay.framework.job.config.PayJobConfiguration.NOTIFY_THREAD_POOL_TASK_EXECUTOR;
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/**
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* 支付通知 Core Service 实现类
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*
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@ -67,9 +69,8 @@ public class PayNotifyServiceImpl implements PayNotifyService {
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@Resource
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private PayNotifyLogCoreMapper payNotifyLogCoreMapper;
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@Resource
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@Lazy
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private ThreadPoolTaskExecutor threadPoolTaskExecutor; // TODO 芋艿:未来提供独立的线程池
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@Resource(name = NOTIFY_THREAD_POOL_TASK_EXECUTOR)
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private ThreadPoolTaskExecutor threadPoolTaskExecutor;
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@Resource
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private PayNotifyLockRedisDAO payNotifyLockCoreRedisDAO;
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@ -120,7 +121,7 @@ public class PayNotifyServiceImpl implements PayNotifyService {
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}
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}));
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// 等待完成
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this.awaitExecuteNotify(latch);
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awaitExecuteNotify(latch);
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// 返回执行完成的任务数(成功 + 失败)
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return tasks.size();
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}
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