Last week I was doing some performance tuning on SSAS Multidimensional and saw something very strange: when the MDX Script of the cube was executed (as always happens after the cache has been cleared, or processing has taken place – you can monitor this via the Execute MDX Script Begin/End events in Profiler) the Calculate() statement was taking just over four seconds. I’d never seen this before so I asked the nice people on the SSAS dev team what was going on, and Akshai Mirchandani very kindly filled me in on the details.
There are two types of calculation on an SSAS cube: those explicitly defined in the MDX Script (ie those seen on the Calculations tab of the cube editor); and semi-additive measures, unary operators and custom rollups, which are defined in the model itself. This second type of calculation is added to the cube when the Calculate() statement fires, and the more of them there are the longer it takes SSAS to work out where they should be applied in the space of the cube. In my customer’s case there were several large (80000+ members) parent/child hierarchies with unary operators as well as a few semi-additive measures and so this was the reason why Calculate() was so slow. Up to now I had only known that Calculate() triggers the aggregation of data up through the cube, which is why if you delete it the cube seems to contain no data.