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13 Designing Aggregations
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11. Click Next . On the Completing The Wizard page, accept the default name, verify that Save The Aggregations But Do Not Process Them is selected, and click Finish . As you stepped through the pages of the Aggregation Design Wizard, the property values, attribute and partition record counts, and aggregation design were added to the XML files containing the design of the AdventureWorks cube, but the aggregations are not calculated and stored . Aggregations are not created until the measure group partition is processed . The Completing The Wizard page allows you to deploy the design changes you have made and process the aggregations, or you can just save the aggregation design but not deploy and process . It most instances, you will just save the aggregations, because you will often want to design aggregations for other partitions and measure groups before you deploy and process . The Aggregations tab of the Cube Designer now displays the aggregation design you have just created .
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The Standard View of the Aggregations tab shows in the Aggregations column that the aggregation design contains three aggregations . This is one more aggregation than was designed by the Aggregation Design Wizard . You can use the Advanced View on the Aggregation tab to view the individual aggregations in an aggregation design . Looking at the individual aggregations will help you understand why the aggregation design contains three aggregations . 12. On the Aggregations tab toolbar, click Advanced View .
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13. Verify that Reseller Sales is selected from the Measure Group list and select AggregationDesign from the Aggregation Design list . Expand the Employee, Product, and Date dimensions . The Advanced View should display three aggregations .
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The attribute and parent-child hierarchies in the measure group are displayed on rows and the three aggregations are represented by the columns A0, A1, and A2 . If a hierarchy is selected, then the corresponding aggregation contains the leaf level members of that hierarchy . Otherwise, the aggregation contains the members of the hierarchy s top level . This will be the All member, unless the hierarchy doesn t contain an All member . One of the aggregations has no selected hierarchies . This aggregation contains the top level of every hierarchy and so contains the most highly summarized values in the partition . This aggregation will frequently be added to an aggregation design, and the other two aggregations are the aggregations that were designed by the Aggregation Design Wizard .
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Attribute Relationships, User-Defined Hierarchies, and Aggregation Design
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In 4, Creating Dimensions, you learned how to create attribute relationships and user-defined hierarchies . This section will review why it is critically important to create attribute relationships and how attribute relationships and user-defined hierarchies affect aggregation design . Attribute relationships identify the natural hierarchies that exist in a dimension . In a natural hierarchy, each child member has only one parent member, so the value of any member at any level of a natural hierarchy can be calculated by aggregating the member s descendants at one of the lower levels of the hierarchy . For example, to find the value for a year, you can aggregate the quarters of that year . You can also aggregate the months or you can aggregate the individual days . Analysis Services can use natural hierarchies two ways to improve query performance . First, when you execute a query, Analysis Services checks to see if the needed aggregate values
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13 Designing Aggregations
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have been stored in memory cache . If not, Analysis Services will look in memory for the values of descendants that can be aggregated . Even if you don t create aggregations, you should still create attribute relationships so that Analysis Services can take advantage of descendant values stored in memory cache . Second, Analysis Services can use natural hierarchies to design aggregations that are stored on disk . Retrieving an aggregate value from disk (or retrieving and aggregating the aggregate values of members of a lower level of a natural hierarchy) is faster than retrieving and aggregating the lowest level of detail from disk . When you created aggregations in the procedure titled Design Aggregations earlier in the chapter, the Aggregation Design Wizard considered only four attributes Employee, Employees, Product ID, and Date because these are the only attributes in the pool of attributes eligible to be considered by the aggregation designer . You can make more attributes eligible to be considered for inclusion in an aggregation design by creating attribute relationships and user-defined hierarchies . Creating attribute relationships identifies the natural hierarchies that Analysis Services can use to create aggregations . Creating user-defined hierarchies signals to Analysis Services that you anticipate users will frequently query Analysis Services using that hierarchy . In the simplified database used in this chapter, all attributes are related to the dimension s key attribute, and all user-defined hierarchies have been removed . In the next two procedures, you will create attribute relationships and user-defined hierarchies . Then, in the procedure titled Redesign Aggregations, you use the Aggregation Design Wizard and find that more attributes are available for aggregation and that the aggregation design contains more aggregations .
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