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fter the chapter on tablescans, you may have expected a chapter on indexed access paths. But the predicted number of rows (cardinality) generated by an operation plays a crucial part in selecting initial join orders and optimum choice of indexes, so it is useful to have a good understanding of how the optimizer estimates the number of rows that are going to be produced at each step of a plan. The reason why this chapter s title includes the term selectivity, rather than cardinality, is that the optimizer s calculations of cardinality are based on estimating the expected fraction of the rows in the current data set that would pass a particular test. That fraction is the number we call the selectivity. After you ve worked out the selectivity, the cardinality is simply selectivity * (number of input rows). Depending on the circumstances, one concept is sometimes more convenient, or intuitive, to use than the other, so I will switch between them fairly freely in the course of the book. I have made a couple of comments about histograms in this chapter, but in most cases this chapter describes the calculations that the optimizer uses when there are no histograms in place. The effects of histograms are examined in 7.

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[CA] while for tuples composed of multiple members, the name would be something of the form ([Store][All Stores][USA][CA],[Customers][All Customers][USA][CA]) The names are matched against mondrianolapMembergetUniqueName() A data mapping yields the cell value if the data label is Data, and yields the cell s formatted value if the label is FormattedData Following are some data mapping examples: Data: Yields the cell value corresponding to the current axis positions; all the result axes will be iterated in this case Data([Measures][Unit Sales], ): Yields the cell value corresponding to the [Measures][Unit Sales] member on the Columns axis and the current position on the Rows axis; only the Rows axis will be iterated in this case FormattedData(Rows[Store][Store State])([Measures][Customer Count], ): Yields the formatted cell value at the Store State level on the Rows axis (and corresponding to the [Measures].

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At a recent conference, I managed to draw an audience of 1,200 people. How many of them do you think were born in December If you ve decided that the answer is about 100, then you ve just performed a perfect imitation of the CBO. (I lied about the audience size to keep the numbers simple, by the way.)

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Having looked at the steps required to install the Friends Reunion web application onto a different machine manually, you should now have a good understanding of what any automated installer will need to do. With that in mind, let s look at the project type VS .NET provides for installing web applications. This is the setup project, and it is found under the Setup and Deployment Projects node of the New Project dialog box. A VS .NET setup project creates a single Microsoft Windows Installer file (with the .msi file extension, which we ll refer to as MSI file in this chapter). This MSI file offers the user a friendly GUI for directing installation, which includes copying files, configuring the environment, and installing components into COM+, if necessary. In addition to the manageability of a single file, such MSI files also offer the benefit of remote deployment over earlier installer technologies (such as cabinet, or .cab, file-based installers). This allows them to be installed on remote machines by system administrators, making their management far quicker and easier. A setup project combines the output files from other VS .NET projects, along with any other necessary files, to create an installation file that can be copied and run on the system that is to host the application. Just for reference, Table 13-1 describes the types of VS .NET projects you can use for deployment.

There are 12 possible months in the year. Dates of birth are (probably) evenly scattered through the year. One-twelfth of the audience will be born in any one month. The request was for one specific month. The requested month does actually exist in the calendar. There are 1,200 people in the audience. The answer is one twelfth of 1,200, which is 100. -- known reference -- assumption -- month s selectivity -- predicate -- boundary check -- base cardinality -- computed cardinality

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