小编Arc*_*Arc的帖子

我有一个多级查询，包括：

var itemsToday = DatabaseContext.Items
                .Where(f => f.StartTime > DateTime.Today && f.StartTime < DateTime.Today.AddDays(1))
                .Include(x => x.LocalStats).ThenInclude(x=>x.StatType1)
                .Include(x => x.LocalStats).ThenInclude(x=>x.StatType2)
                .Include(x => x.LocalStats).ThenInclude(x=>x.StatType3)
                .Include(x => x.LocalStats).ThenInclude(x=>x.StatType4)
                .Include(x => x.LocalStats).ThenInclude(x=>x.StatType5)
                .Include(x => x.LocalStats).ThenInclude(x=>x.StatType6)
                .Include(x => x.LocalStats).ThenInclude(x=>x.StatType7)
                .Include(x => x.LocalStats).ThenInclude(x=>x.StatType8)
                .Include(x => x.LocalStats).ThenInclude(x=>x.StatType9)
                .Include(x => x.LocalDetails)
...
                .OrderBy(f=>f.SomeOrderingCriterion);

还有比这更多的包含。当然，这会导致 EF Core 3.0在 SQL 查询中生成许多连接，这意味着执行需要很长时间（25 秒以上才能检索 200 条记录）。

我曾尝试使用格式.Include(x => x.LocalStats.StatType1)而不是 Include 和 ThenInclude，但结果是一样的。

有什么方法可以使这更有效吗？文档建议：

具有大量Include运算符的LINQ 查询可能需要分解为多个单独的 LINQ 查询，以避免笛卡尔爆炸问题。

但是我没有看到有关如何实际完成此操作的任何解释。

我在尝试训练模型时遇到以下问题：

Inferring Columns ...
Creating Data loader ...
Loading data ...
Exploring multiple ML algorithms and settings to find you the best model for ML task: binary-classification
For further learning check: https://aka.ms/mlnet-cli
|     Trainer                              Accuracy      AUC    AUPRC  F1-score  Duration #Iteration             |
[Source=AutoML, Kind=Trace] Channel started
[Source=AutoML, Kind=Trace] Evaluating pipeline xf=ColumnConcatenating{ col=Features:V1,V2,V3,V4,V5,V6} xf=Normalizing{ col=Features:Features} tr=AveragedPerceptronBinary{}  cache=+
[Source=AutoML, Kind=Error] Pipeline crashed: xf=ColumnConcatenating{ col=Features:V1,V2,V3,V4,V5,V6} xf=Normalizing{ col=Features:Features} tr=AveragedPerceptronBinary{}  cache=+ . Exception: System.ArgumentOutOfRangeException: AUC is not definied when there is no positive class in the …