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Figure 1 The Aggregation Design Wizard
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It is important to understand how Analysis Services makes its decisions so you can influence them appropriately. Keep in mind that the following information relates to indicating aggregation candidates. The ADW will ultimately determine what aggregations are worth designing based on the input that you provide. The better the input, the more efficient your resulting aggregation design will be. Fundamentally, you can provide Analysis Services with a list of candidate attributes for aggregation, their member counts in the cube data source, the performance target, and, optionally, a list of queries to optimize. I ll talk about the first topic in this section and the others later in the chapter. There are several techniques for influencing the aggregation design. The first is to indicate to Analysis Services the attribute dimensions to consider for aggregation. By default, Analysis Services uses a number of conditions to determine which dimension attributes will be candidates. Attributes that are included in a natural hierarchy are automatically considered, unless you indicate that they should not be. Attributes that are not included in a natural hierarchy are usually not included.
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A natural hierarchy is a user-defined hierarchy that contains two or more attributes that are related to each other by a one-to-many relationship from each level to the next. Excellent examples are calendar hierarchies (Year > Quarter > Month > Day) or geography hierarchies (Country > State > City).
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The AggregationUsage property of a dimension attribute is an indication of which attributes the ADW will consider in the design. The default is Default. A number of conditions go into considering whether an attribute with this AggregationUsage value will be considered. For a good discussion on this, consult the Microsoft SQL Server 2005 (or 2008) Analysis Services Performance Guide, available from http:/ /www.microsoft.com. In most cases, all attributes in a natural hierarchy are considered, as well as the All level and the dimension key. None should be used for attributes that are rarely queried. Commonly queried attributes should be changed to Unrestricted. This tells the ADW to consider the attribute, but the wizard will ultimately determine if the attribute will be valuable in an aggregation design, based on the number of members, its relationship to other attributes, and the query load (for the usagebased optimizer). The final choice is Full, which forces all aggregations to use this attribute or an attribute lower in a hierarchy, if contained in a natural hierarchy. This property should seldom be used. When you are not sure whether an attribute is flagged as a candidate for aggregation or not, open the ADW and go to the Specify Object Counts page. You can expand each dimension to view a list of attributes. The attributes displayed in bold are aggregation candidates. If you feel that one of the unbolded attributes should be a candidate, just change the AggregationUsage property to Unrestricted in the cube designer in BIDS. Analysis Services 2008 includes some nifty wizards for aggregation design. Because these wizards are backwards compatible with Analysis Services 2005, you can install the SQL Server 2008 client tools to leverage these wizards even before you are ready to upgrade your cubes. Figure 2 shows a part of the updated ADW in 2008, which can be used to review and update the AggregationUsage property across all attributes in the cube at once.
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Attribute relationships
Analysis Services 2005 and 2008 have a core concept that I have yet to mention, though it is a critical one. If you read anything on performance in Analysis Services, you will likely read about the importance of indicating appropriate relationships between attributes in your user-defined hierarchies. Simply creating a user-defined hierarchy in a dimension does not perform this automatically because it cannot be assumed. You probably see a lot of visual tips about creating relationships when in the dimension designer. These tips provide feedback to let you know that something is potentially wrong with your design. Attribute relationships tell Analysis Services how attributes relate to one another. By default, all attributes are directly related to the dimension key. For example, consider a Time dimension where we have a user-defined hierarchy named Calendar. This may consist of the levels Year, Qtr, Month, and Day. Even if you create a userdefined hierarchy with one below the other, no assumptions are made about Calendar Calendar Calendar the relationship from one to another. Year Qtr Month Because all attributes are directly related to the key, Analysis Services sees the user-defined hierarchy like Day the illustration on the right.
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