Query Performance Tuning - Expert Cube Development with SSAS Multidimensional Models - page 216

Note that attributes with AttributeHierarchyEnabled set to False will have no
aggregations designed for them anyway.

• Unrestricted : This means that the attribute may be included in the
aggregations designed, depending on whether the algorithm used
by the wizard considers it to be useful or not.
• Default : The default option applies a complex set of rules, which are:
• The granularity attribute (usually the key attribute, unless you specified
otherwise in the dimension usage tab) is treated as Unrestricted.
° All attributes on dimensions involved in many-to-many
relationships, unmaterialized referenced relationships, and data
mining dimensions are treated as None . Aggregations may still
be built at the root granularity that is the intersection of every All
Members on every attribute.
° All attributes that are used as levels in natural user hierarchies are
treated as Unrestricted .
° Attributes with IsAggregatable set to False are treated as Full .
° All other attributes are treated as None .

The next step in the wizard asks you to verify the number of EstimatedRows and
EstimatedCount properties we've already talked about, and gives the option of
setting a similar property that shows the estimated number of members from an
attribute that appear in any one partition. This can be an important property to set; if
you are partitioning by Month, although you may have 36 members on your Month
attribute, a partition will only contain data for one of them.

On the Set Aggregation Options step you finally reach the point where some
aggregations can be built. Here you can apply one last set of restrictions on the set of
aggregations that will be built, choosing to either:

• Estimated Storage Reaches : This means you build aggregations to fill a given

amount of disk space.

• Performance Gain Reaches : This is the most useful option. It does not mean

that all queries will run n percent faster, nor does it mean that a query that
hits an aggregation directly will run n percent faster. Think of it like this: if
the wizard built all the aggregations it thought were useful to build (note:
this is not the same thing as all of the possible aggregations that could be
built on the cube) then, in general, performance would be better.