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CHAPTER 4 s DATA ACCESS AND SECURITY
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When troubleshooting pivot table problems, it may help if you know what formulas are in the pivot Tip
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Note that the NUM_COL returns the exact number we provided as input. There are fewer than 38 significant digits in the input number (I supplied a number with 20 significant digits), so the exact number is preserved. The FLOAT_COL, however, using the new BINARY_FLOAT type, was not able to accurately represent this number. In fact, it preserved only 7 digits accurately. The DBL_COL fared much better, accurately representing the number in this case out to 17 digits. Overall, though, this should be a good indication that the BINARY_FLOAT and BINARY_DOUBLE types will not be appropriate for financial applications! If you play around with different values, you ll see different results: ops$tkyte@ORA11GR2> delete from t; 1 row deleted. ops$tkyte@ORA11GR2> insert into t ( num_col, float_col, dbl_col ) 2 values ( 9999999999.9999999999, 3 9999999999.9999999999, 4 9999999999.9999999999 ); 1 row created. ops$tkyte@ORA11GR2> select * from t; NUM_COL FLOAT_COL DBL_COL ------------------------ ------------------------ -----------------------9999999999.99999999990 10000000000.00000000000 10000000000.00000000000 Once again, the NUM_COL accurately represented the number, but the FLOAT_COL and DBL_COL did not. This does not mean that the NUMBER type is able to store things with infinite accuracy/precision just that it has a much larger precision associated with it. It is easy to observe similar results from the NUMBER type: ops$tkyte@ORA11GR2> delete from t; 1 row deleted. ops$tkyte@ORA11GR2> insert into t ( num_col ) 2 values ( 123 * 1e20 + 123*1e-20 ) ; 1 row created. ops$tkyte@ORA11GR2> set numformat 999999999999999999999999.999999999999999999999999 ops$tkyte@ORA11GR2> select num_col, 123*1e20, 123*1e-20 from t; NUM_COL -------------------------------------------------123*1E20 -------------------------------------------------123*1E-20 -------------------------------------------------12300000000000000000000.000000000000000000000000 12300000000000000000000.000000000000000000000000 .000000000000000001230000 As you can see, when we put together a very large number (123*1e20) and a very small number (123*1e-20), we lost precision because this arithmetic requires more than 38 digits of precision. The large number by itself can be faithfully represented, as can the small number, but the result of the larger plus the smaller cannot. We can verify this is not just a display/formatting issue as follows:
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Figure 6-47. Draw an Ellipse on the workspace roughly 400 400.
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Name/value lists are read-only collections that expose a list of child objects. Each child object contains a name and a value. Of course, the framework doesn t know the data types of the name and value ahead of time, but generics can help overcome that issue. A nested NameValuePair class will be declared within NameValueListBase, using generic type parameters to define the types for the name and value. The NameValueListBase class takes two generic type parameters, one for the name (key) and the other for the value: <Serializable()> _ Public MustInherit Class NameValueListBase(Of K, V) Inherits Core.ReadOnlyBindingList(Of NameValuePair) Implements ICloneable Implements Core.IBusinessObject It also inherits from Csla.Core.ReadOnlyBindingList, specifying that the type of item contained in the collection is NameValueListBase(Of K, V).NameValuePair.
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CHAPTER 1 s INTRODUCING AJAX
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Gathers signatures needed to complete an Office document. Manages document expiration and retention by allowing participants to decide whether to retain or delete expired documents.
http://msdn.microsoft.com/webservices/understanding/specs/default .aspx pull=/library/en-us/dnglobspec/html/ws-security-kerberos.asp
hen you add date fields to a pivot table, you can show the dates individually, or group them into larger units, such as years, quarters, or months. This adds flexibility to the pivot table, and enables you to do things like comparing the results from one year to another, or creating a running total by quarter. You can also group numeric fields, when you add them to the Row Labels or Column Labels area of the pivot table. By using this feature, you can group the numbers into larger chunks, such as groups of 10 or 25. If comparing test scores, or results by age, you can look at larger segments of the population, instead of individual scores or ages. It s also possible to manually group text items in the Row Labels and Column Labels areas, so you can group cities into a region, or employees into teams, and summarize the data for the group. Most of the time, grouping goes smoothly, but you may hit snags, or see error messages when you try to group the data in your pivot table. This chapter addresses those problems, and provides solutions or workarounds for the issues you might encounter. This chapter also covers problems that may arise when summarizing pivot table results in subtotals and grand totals, and when summarizing fields in the Values area. Except where noted, the problems in this chapter are based on the Stores.xlsx sample workbook.
In May 2002, Juval Lowy wrote an article for MSDN magazine in which he described how to create custom .NET security objects that merge NT domain or AD groups and COM+ roles so that both are available to the application.2
Description
Figure 9-4. The flow of control through a switch statement
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