Sitecore solr在不同的VM中设置(Sitecore solr setup in a different VM)

 为简单起见，我将首先在2D中解释它，即具有两个角度特征。 在这种情况下，你将有b ^ 2箱，而不是b * 2。 
 
 特征空间分为常规网格。 特征根据它们在2D（或3D）空间中的位置进行分箱，而不是沿每个维度独立分区。 请参阅以下示例，其中包含两个要素尺寸和b = 4，其中要素被分箱到标有#的单元格中： 
 
^ phi
|
+-+-+-+-+
| | | | |
+-+-+-+-+
| | | | |
+-+-+-+-+
| | | |#|
+-+-+-+-+
| | | | |
+-+-+-+-+-> alpha
 
 该特征被分箱到单元格中，其中alpha在给定的间隔中，而phi在另一个区间中。 您理解的关键区别在于尺寸不是独立处理的。 每个单元格指定所有维度的间隔，而不是单个维度。 （这将在3D中以相同的方式工作，只是你将拥有theta的另一个维度和3D网格而不是2D网格。） 
 
 这种分箱方式导致2D情况的b ^ 2个区间，因为alpha维度中的每个区间与phi维度中的所有区间组合，导致数字的平方，而不是加倍。 添加另一个维度，您可以获得立方体而不是三倍，就像您的问题一样。 

For simplicity, I'll first explain it in 2D, i.e. with two angular features. In that case, you would have b^2 bins, not b*2. 
 
The feature space is divided into a regular grid. Features are binned according to their position in the 2D (or 3D) space, not independently along each dimension. See the following example with two feature dimensions and b=4, where the feature is binned into the cell marked with #:
 
^ phi
|
+-+-+-+-+
| | | | |
+-+-+-+-+
| | | | |
+-+-+-+-+
| | | |#|
+-+-+-+-+
| | | | |
+-+-+-+-+-> alpha
 
The feature is binned into the cell where alpha is in a given interval AND phi in another interval. The key difference to your understanding is that the dimensions are not treated independently. Each cell specifies an interval on all the dimensions, not a single one. (This would work the same way in 3D, only that you would have another dimension for theta and a 3D grid instead of a 2D one.)
 
This way of binning results in b^2 bins for the 2D case, since each interval in the alpha dimension is combined with ALL intervals in the phi dimension, resulting in a squaring of the number, not a doubling. Add another dimension, and you get the cubing instead of the tripling, as in your question.