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An aggregation is all the possible combinations of the members of one level from each attribute hierarchy in every dimension in a measure group Consider the three aggregations that could be created just from the Color and Size attribute hierarchies in the Product dimension and a single measure One aggregation would contain a single value equal to the summary value for all colors and all sizes A second aggregation would contain 10 values equal to the 10 different colors summarized for all sizes A third aggregation would contain 19 values equal to the 19 different sizes summarized for all colors Of course, this is a simple example The Product dimension contains other attribute hierarchies, and even the simple measure group used in this chapter contains other dimensions .

SQL Server Management Studio environment has the ability to display the execution plan that SQL Server 2005 s query optimizer chose when executing a particular T-SQL statement. This feature can help you determine whether your T-SQL statements are executing efficiently or whether corrective action is necessary. This typically involves either

rewriting the query or redesigning your indexing strategy. In certain cases, however, you will have to resort to overriding the optimizer through optimizer hints. (Make sure you always document the reasons for overriding the optimizer for future reference.) Note

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The execution plan describes how the query optimizer executed a T-SQL statement within a batch. The plan shows the different types of operations that needed to be performed, the order in which they were performed, and the data access method used to retrieve data from the tables (index scan, index seek, or table scan). It shows which steps consumed the most resources and/or time within both the T-SQL statement and batch. Watch out for expensive operations such as table scans and hash joins.

Remember that an aggregation contains summarized values for the members of one level of every attribute hierarchy in every dimension in a measure group Aggregations are physically stored in measure group partitions A partition in Analysis Services is the physical location of the data stored in a measure group Each measure group in a cube has one or more corresponding partitions Because every cube has at least one measure group, every cube has at least one partition Each time you create an additional measure group, another partition is created Queries run faster against a partitioned cube because Analysis Services only needs to read data from the partitions that contain the answers to the queries Queries can run even faster when the partition also stores aggregations, the precalculated totals for measures .

SQL Server Managment Studio has the ability to display both the estimated execution plan and the actual execution plan. With the estimated execution plan, your T-SQL script is only parsed and an execution plan estimated based on the best efforts of SQL Server Managment Studio. The actual execution plan, on the other hand, can be generated only when your T-SQL script is actually executed. Be careful of the estimated execution plan because SQL Server does not guarantee that it will be the same as the actual execution plan at runtime. Developers typically use the estimated execution plan as an indication of how their T-SQL query is going to perform without consuming the resources of the SQL Server instance, which could have a dramatic impact on performance in a production environment. To use SQL Server Managment Studio to view the actual execution plan of a T-SQL statement, follow these steps: 1. Start SQL Server Management Studio and connect to your SQL Server instance. Navigate to the database and click on it in Object Explorer. Click the New Query button on the top toolbar. Type the T-SQL statement you are interested in analyzing, click the Include Actual Execution Plan button (or press Ctl-M) on the top toolbar, and execute your T-SQL script. An execution plan, similar to that shown in Figure 30-41, should be seen in bottom pane of SQL Server Managment Studio. Note

There is a lot of rich information located in the graphical execution plan that can be easily overlooked. For example, the width of the arrows linking the various nodes together indicates the amount of the data that was passed from one operation to the other. Holding the mouse over one of these arrows actually shows you the actual number of rows generated amongst other information.

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2. To get more information about each individual step in the execution plan, hover your mouse over a particular operation. This causes a tool tip to appear, which will have more information about the operation as follows:

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