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QCache 是什么？

这是 Qt 官方为 LRU 设计的容器，稳定、高效、代码最少。LRU 缓存‌（Least Recently Used，最近最少使用）是一种常见的‌缓存淘汰策略‌，其核心思想是：当缓存空间不足时，优先淘汰最久未被访问的数据项‌，以保留近期可能再次被使用的数据。

LRU核心原理

• 基于‌时间局部性原理‌：最近被访问的数据，在未来短时间内被再次访问的概率较高。
• 维护数据的‌访问顺序‌：最近使用的数据放在“前面”，最久未使用的放在“后面”。
• 缓存满时，‌移除尾部（最久未用）的数据‌，为新数据腾出空间。

常见应用场景

• 浏览器缓存‌：只保留最近访问的网页资源，自动清理旧内容。
• 操作系统内存管理‌：保留最近使用的页面，淘汰不活跃页面。
• 数据库查询缓存‌：缓存最近执行的查询结果，提升响应速度。
• CPU 多级缓存（L1/L2/L3）‌：利用高速缓存减少 CPU 等待时间。

QCache应用示例

#include<QCoreApplication>#include<QDateTime>#include<QDebug>#include<QCache>#include<QThread>qint64generateTaskId(){staticqint64 counter=0;return(QDateTime::currentMSecsSinceEpoch()<<20)|((++counter)&0xFFFFF);}structTaskResult{boolsuccess;QString message;TaskResult(bools=false,constQString&m=QString()):success(s),message(m){}};QCache<qint64,TaskResult>m_resultCache(10);//QCache<qint64, QPair<bool, QString>> m_resultCache2(10);boolgetTaskResult(qint64 taskId,TaskResult&res){TaskResult*result=m_resultCache.object(taskId);if(!result){returnfalse;}res.success=result->success;res.message=result->message;returntrue;}voidprocessTask(qint64 taskId){boolsuccess=QDateTime::currentMSecsSinceEpoch()%2;QString temp=QDateTime::currentDateTime().toString("yyyy/MM/dd hh:mm:ss.zzz");qDebug()<<QString("taskId=%1, success=%2, message=%3").arg(taskId).arg(success).arg(temp);// 插入新任务(自动成为最近使用)m_resultCache.insert(taskId,newTaskResult(success,temp));//m_resultCache2.insert(taskId, new QPair<bool, QString>(true, temp));qDebug()<<"Cache size:"<<m_resultCache.size();}intmain(intargc,char*argv[]){QCoreApplicationa(argc,argv);for(inti=0;i<15;++i){qint64 taskId=generateTaskId();processTask(taskId);QThread::msleep(10);}// 验证淘汰结果qDebug()<<"Final cache count:"<<m_resultCache.size()<<"-------------------";for(autok:m_resultCache.keys()){TaskResult result;boolread=getTaskResult(k,result);qDebug()<<QString("read %1, taskId=%2, success=%3, message=%4").arg(read).arg(k).arg(result.success).arg(result.message);}returna.exec();}

执行结果

"taskId=1864600921498976257, success=1, message=2026/05/08 14:33:29.181"Cache size:1"taskId=1864600921530433538, success=1, message=2026/05/08 14:33:29.211"Cache size:2"taskId=1864600921547210755, success=1, message=2026/05/08 14:33:29.227"Cache size:3"taskId=1864600921562939396, success=0, message=2026/05/08 14:33:29.242"Cache size:4"taskId=1864600921580765189, success=1, message=2026/05/08 14:33:29.259"Cache size:5"taskId=1864600921596493830, success=0, message=2026/05/08 14:33:29.274"Cache size:6"taskId=1864600921613271047, success=0, message=2026/05/08 14:33:29.290"Cache size:7"taskId=1864600921628999688, success=1, message=2026/05/08 14:33:29.305"Cache size:8"taskId=1864600921645776905, success=1, message=2026/05/08 14:33:29.321"Cache size:9"taskId=1864600921661505546, success=0, message=2026/05/08 14:33:29.336"Cache size:10"taskId=1864600921678282763, success=0, message=2026/05/08 14:33:29.352"Cache size:10"taskId=1864600921694011404, success=1, message=2026/05/08 14:33:29.367"Cache size:10"taskId=1864600921711837197, success=0, message=2026/05/08 14:33:29.384"Cache size:10"taskId=1864600921727565838, success=1, message=2026/05/08 14:33:29.399"Cache size:10"taskId=1864600921744343055, success=1, message=2026/05/08 14:33:29.415"Cache size:10Final cache count:10-------------------"read 1, taskId=1864600921596493830, success=0, message=2026/05/08 14:33:29.274""read 1, taskId=1864600921744343055, success=1, message=2026/05/08 14:33:29.415""read 1, taskId=1864600921628999688, success=1, message=2026/05/08 14:33:29.305""read 1, taskId=1864600921613271047, success=0, message=2026/05/08 14:33:29.290""read 1, taskId=1864600921645776905, success=1, message=2026/05/08 14:33:29.321""read 1, taskId=1864600921678282763, success=0, message=2026/05/08 14:33:29.352""read 1, taskId=1864600921661505546, success=0, message=2026/05/08 14:33:29.336""read 1, taskId=1864600921711837197, success=0, message=2026/05/08 14:33:29.384""read 1, taskId=1864600921694011404, success=1, message=2026/05/08 14:33:29.367""read 1, taskId=1864600921727565838, success=1, message=2026/05/08 14:33:29.399"