日志写入自定义参数，MDC写入参数

获取
 %X{aop01}

            <pattern>%d{yyyy-MM-dd HH:mm:ss.SSS} %X{aop01}[ %thread ] - [ %-5level ] [ %logger{50}.%M : %line ] - %msg%n</pattern>

 

private  Map<String, String> COPY_OF_CONTEXT_MAP = MDC.getCopyOfContextMap();

public  Map<String, String> getMDCMap(){
    if(Objects.isNull(COPY_OF_CONTEXT_MAP)){
        COPY_OF_CONTEXT_MAP=MDC.getCopyOfContextMap();
        return COPY_OF_CONTEXT_MAP;
    }
    return COPY_OF_CONTEXT_MAP;
}
public  void addMDC(String key, String val) {
    MDC.put(key, val);
    getMDCMap().put(key,val);
}

带入线程池

在子线程下也可以获取到

        threadPoolTaskExecutor.execute(() -> {
            MDC.setContextMap(COPY_OF_CONTEXT_MAP);
            }
        });

 

 

 

 

 

 线程池配置方式

import org.slf4j.MDC;
import org.springframework.core.task.TaskDecorator;
import java.util.Map;
 
public class MdcTaskDecorator implements TaskDecorator {
    @Override
    public Runnable decorate(Runnable runnable) {
        Map<String, String> contextMap = MDC.getCopyOfContextMap();
        return () -> {
            try {
                MDC.setContextMap(contextMap);
                runnable.run();
            } finally {
                MDC.clear(); // 清理MDC
            }
        };
    }
}

import org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
 
@Configuration
public class AsyncConfig {
 
    @Bean(name = "threadPoolTaskExecutor")
    public ThreadPoolTaskExecutor threadPoolTaskExecutor() {
        ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
　　　　　//执行前、执行后-记录mdc请求唯一值，方便查看整个请求链路日志　　
        executor.setTaskDecorator(new MdcTaskDecorator());
        // 设置executor的其他属性，如核心线程池大小、最大线程池大小等
        executor.initialize();
        return executor;
    }
}