集算器行列转换实现高效率大数据分组

报表内要通过各种混合算浪费大量内存及关联时间

可以把数据集改为集算器数据集，所有的数据处理经脚本来做。另外，可用封装的函数对数据特殊处理，此例中用pivot行列互换改变报表需通过各种条件关联才可实现的取数逻辑，大大减少取数及计算的时间，如下：

/=file("tj.xls").importxls@t().sort(参数业务ID,条件名称).select(申请编号!=null)

=connect("218eos75")
=B2.sort(参数业务ID,条件名称).pivot(参数业务ID,组ID,申请编号,样品编号,样品名称,样品大类,样品小类,样品品牌,样品归属轮胎类型,参数名称,检测日期,检测参数组结果值;条件名称,条件实际值;"试验温度","测试载荷","轮胎安装方式","试验负荷","纵向加载速度","空气流速","试验气压","试验周期","环境湿度","放大镜观测倍数","恒温调节时间","读数维持时间","混合气比例","试验速度","结束时间","湿度","环境温度（℃）","测试气压","轮胎旋转方向","激励信号","拉伸方式","最大伸长率","拉伸频率","起始时间","转速","扭转速度","老化周期","轮胎停放开始时间","敲击方向","环境温度","臭氧浓度","试验湿度","温度","气压调节方式","激励方式","径向加载速度","预压次数","测试实验室","边界条件","横向加载速度","首次龟裂时间")
/clear B2
>A2.close()
result A3