Last week I wrote an article about Natural Hierarchies in Power Pivot and Tabular where I show why it is important creating natural hierarchies for performance reasons. I’d like to spend a few words about the reasons why this is so important, so you might read the article in advance before moving forward.

I had to investigate on a performance issue in a Tabular model of a customer. Initially, I wasn’t able to reproduce the issue creating a similar query in a test environment, because I didn’t focused my attention on the presence of the hierarchy, and I was generating similar queries without the hierarchy at all. Once I realized that the problem was present only in MDX and not in DAX, I started analyzing the query created by Excel and I found a number of workarounds teaching users how to avoid dangerous combinations of attributes on the rows of a pivot table. After more investigations and some help from people in MS (thanks Marius!) I realized that the problem was the use of unnatural hierarchies. I was aware of the problem (I always explain to use natural hierarchies whenever possible), but I was not aware of the order of magnitude of the problem in certain conditions, as I described in the article.

So, I think it is interesting to highlight how to detect the problem when you just look at the Profiler. If the data model uses unnatural hierarchies, you will find in MDX code that certain members have names such as:

[Date].[Calendar].[Year].&[2007].&[1]
[Date].[Calendar].[Year].&[2007].&[1].&[1]
[Date].[Calendar].[Year].&[2007].&[1].&[1].&[March]

These names, when you use a natural hierarchy, will be:

[Date].[Calendar].[Semester].&[H1-2007]

[Date].[Calendar].[Quarter].&[Q1-2007]

[Date].[Calendar].[Month].&[March 2007]

The reason why performance might be slow and the query starts consuming memory is because of the Non Empty operation performed by the engine in order to eliminate tuples that are not included in the result. It is important to know that this does not happen for any query, and is very sensitive to the number of combinations resulting by the Cartesian product of all the attributes included in an axis of the MDX query. For example, if you use the Country name instead of the City in the example that I included in the article, also the unnatural hierarchy works in a reasonable time.

Lesson learned: always use natural hierarchies also in Power Pivot and SSAS Tabular!