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This is an interesting approach, and it is the one we look at in detail in this section At first glance, it may seem that issuing a query every time the user clicks Next or Previous would result in unnecessary network traffic Though this is true, in many cases this disadvantage is more than compensated for by the following advantages: Your query doesn t need to hold the connection across requests in the case of webbased applications Your query doesn t have any restrictions mentioned in the section Result Set Limitations and Downgrade Rules that a scrollable result set would impose You don t need to cache the rows in the middle tier, so this approach scales far better with large result sets For sorting, you don t need to sort in the middle tier (which is required if you take the approach of caching in the middle tier).

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Like other .NET languages, F# directly supports two-dimensional array values that are stored flat, that is, where an array of dimensions (N, M) is stored using a contiguous array of N * M elements. The types for these values are written using [,], such as in int[,] and double[,], and these types also support slicing syntax. Values of these types are created and manipulated using the values in the Array2 module. Likewise, there is a module for manipulating three-dimensional array values whose types are written int[,,]. You can also use the code in those modules as a template for defining code to manipulate arrays of higher dimension.

Instead of sorting in the middle tier, you can simply issue the same query with an appropriate order by clause This means less code to write and fewer maintenance headaches The sorting code in the middle tier can get pretty hairy if your requirement is to be able to sort on one or more columns in ascending or descending order We will use the following well-known template1 for writing queries that gets n out of m rows for a given query: select * from ( select /*+ FIRST_ROWS */ a*, rownum rnum from ( YOUR_QUERY_TEXT ) a where rownum <= :max_row_number ) where rnum >= :min_row_number;.

The .NET Framework comes equipped with an excellent set of imperative collections under the namespace System.Collections.Generic. You have seen some of these already. In the following sections, we ll take a look at some simple uses of these collections.

Security attempts to prevent nefarious persons from performing nefarious acts, and simpleminded fools from the tools they shouldn t use. This runs a wide range of activities, from detecting and preventing a denial of service attack on a public web server, to keeping a known user from accessing a function he s not meant to. You ll also need to establish what happens once a security breach does occur. Do you have enough information to detect what happens Do you have enough to recover Can you restore your data to a previously known, good state There are three main steps to security: authentication, authorization, and auditing. Authentication involves identifying the users of your system, and denying access to functionality to those users who cannot identify themselves. Authorization concerns making sure authenticated users have permissions to run the function or see the data they re attempting to access. Auditing ensures your ability to investigate and recover if something goes wrong with

Tom Kyte, Effective Oracle by Design (Emeryville, CA: Osborne McGraw-Hill, 2003), p. 496. This code is also available from http://asktom.oracle.com/~tkyte/paginate.html.

As mentioned in 3, the .NET Framework comes with a type System.Collections. Generic.List<'a>, which, although named List, is better described as a resizeable array. The F# library includes the following type abbreviation for this purpose: type ResizeArray<'a> = System.Collections.Generic.List<'a> Here is a simple example of using this data structure: > let names = new ResizeArray<string>();; val names : ResizeArray<string> > for name in ["Claire"; "Sophie"; "Jane"] do names.Add(name);; val it : unit = () > names.Count;; val it : int = 3 > names.[0];; val it : string = "Claire"

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