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Although in principle the generated stub is responsible for implementing the calling convention adopted by the native code receiving the function pointer, the CLR supports only the stdcall calling convention for marshalling function pointers Thus, the native code should adopt this calling convention when invoking the pointer; this is a restriction that may cause problems, but in general on the Windows platform the stdcall calling convention is widely used The following C function uses a function pointer to apply a function to an array of integers: typedef int (CALLBACK *TRANSFORM_CALLBACK)(int); void CINTEROPDLL_API transformArray(int* data, int count, TRANSFORM_CALLBACK fn) { int i; for (i = 0; i < count; i++) data[i] = fn(data[i]); } The TRANSFORM_CALLBACK type definition defines the prototype of the function pointer we are interested in here: a function taking an integer as the input argument and returning an integer as a result.

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As you can see, the creation of a pooled connection results in an actual physical connection being created. But the retrieval of a logical connection does not result in any new physical connection. Similarly, even after closing the logical connection, the physical connection created is retained for use across other sessions. Finally, when we close the pooled connection, the physical connection is also closed. In the next section, we ll look at a simple Oracle implementation of a connection cache using the connection pooling framework.

The CALLBACK macro is specific to the Microsoft Visual C++ compiler and expands to __stdcall in order to indicate that the function pointer, when invoked, should adopt the stdcall calling convention instead of the cdecl calling convention The transformArray function simply takes as input an array of integers with its length and the function to apply to its elements You now have to define the F# prototype for this function by introducing a delegate type with the same signature as TRANSFORM_CALLBACK: type Callback = delegate of int -> int [<DllImport("CInteropDLL", CallingConvention=CallingConventionCdecl)>] extern void transformArray(int[] data, int count, Callback transform); Now you can increment all the elements of an array by one using the C function: let data = [| 1; 2; 3 |] printf "%s\n" (stringJoin("; ", (Arraymap any_to_string data))) CInteroptransformArray(data, dataLength, new CInteropCallback(fun x -> x + 1)) printf "%s\n" (string.

Figure 1-2. A simple architecture for a managed web application In some cases, the UI layer calls the data access layer directly. Although this is a violation of the guidance provided by the layering pattern, in this case, it s acceptable as the business rules aren t that complex and, in many cases, would be nothing more than a pass-thru layer, providing nothing but an additional level to the call stack and bloating your code base, assembly sizes, and heap allocations unnecessarily.

As discussed earlier, a connection cache is a cache of physical connections maintained by the middle tier using the connection pooling framework just discussed. JDBC 2.0 does not specify any API specific to connection cache; it only specifies an API for the underlying connection pooling framework. Thus, the middle tier is free to implement the connection cache in any way. JDBC 3.0 does specify an API along with some connection cache related properties for implementation of a connection cache at the data source level. As discussed later in the section Oracle 10g Connection Caching, the new Oracle 10g caching is compliant with JDBC 3.0 requirements.

Join("; ", (Arraymap any_to_string data))).

Note The concept of connection caching is not relevant to the server-side internal driver, where you use

Even with this simple design, this application could scale out to handle additional load in the future. The requirements for what needs to be managed in state are minimal enough that they re easily implemented using cookies (good only for small amounts of data), and the database (more coding, but it s persistent, scalable, and available). Access to the database is synchronous, so any long-running queries would incur a delay in the responsiveness of the application for the user, as there s nothing in this design to address asynchronous operations. The recovery plan, should the server go down, is to drive to the office as fast as possible and repair or replace the machine. This results in a low availability guarantee, which is acceptable because the application isn t mission critical. Any requests in-process during a system crash would be lost. Deployment of new versions and fixes for this application are worry free. State information is tracked in the database, and correlated to users with a cookie value. Both of these stores survive the reboot of a web server. This architecture would obviously not work for all applications. There are a number of serious limitations. However, when the requirements are met by this solution, it s an excellent choice, because developing applications like these are extremely fast and very easy to learn, compared to a lot of n-tiered applications. We discuss strategies for reuse of code in the web presentation tier in 3. We cover using ADO.NET effectively in 10. And we examine the Data Access Layer Application block, a part of the Enterprise Library, in 11.

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