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And that s about it. The bulk of the processing on your site does not touch this column at all. When the customer is browsing your online catalogue, you are not retrieving their credit card information. When the customer is adding items to your shopping cart, you are not accessing the credit card data. When the customer is interacting with your online shopping help desk, you are not touching the credit card data. If and only if they checkout will you access it, and then only once. The overhead of encryption will only be felt at that exact point in time, which hardly ever happens (again, relatively speaking a very small percentage of the work processed by your application involves accessing the credit card number). On the other hand, what if the table you utilized was created as follows: Create table customer ( cust_id number primary key, number_of_page_views number encrypt, .. other data credit_card# varchar2(50) encrypt ); Assume in your application the column NUMBER_OF_PAGE_VIEWS represents a hit counter that you update each and every time a customer clicks on a page on your site. The cost of encrypting the NUMBER_OF_PAGE_VIEWS column would be very high because you would be accessing that column frequently with every page generated for a given user and you would be accessing it in a read/write fashion. This would require you to decrypt that column add one to its value and write that value back to the table, causing the newly-computed value to be encrypted. The overhead would be measurable. Fortunately though, the requirement to encrypt that specific column is probably very low.

The WebServicesProxy calls a web service, implemented in the Csla.Server.Hosts. WebServicePortal class. Unlike the other server-side host classes, this one doesn t implement IDataPortalServer. The interface exposed by the web service is quite different from IDataPortalServer, because the web service accepts and returns byte arrays rather than native .NET types. You ve already seen how the WebServicesProxy manually serializes and deserializes the data sent to and from the web service. Now let s look at the other end of the process. The same Serialize() and Deserialize() helper methods are used on the server too, as you can see in the Fetch() implementation: <WebMethod()> _ Public Function Fetch(ByVal requestData As Byte()) As Byte() Dim request As FetchRequest = _ DirectCast(Deserialize(requestData), FetchRequest) Dim portal As New Server.DataPortal Dim result As Object Try result = portal.Fetch(request.Criteria, request.Context) Catch ex As Exception result = ex End Try Return Serialize(result) End Function The method accepts a byte array as a parameter, which is immediately deserialized to create a server-side copy of the FetchRequest object created on the client: Dim request As FetchRequest = _ DirectCast(Deserialize(requestData), FetchRequest)

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Figure 19-12. Assignment compatibility means that you can assign a reference of a more derived type to a variable of a less derived type. Now let s look at a more interesting case by expanding the code in the following ways as shown following: This code adds a generic delegate named Factory, which takes a single type parameter T, takes no method parameters, and returns an object of type T.

for a fact that insert statement can t ever be reused later!!! If you use literals (constants) in the query, then every query is a brand-new query, never before seen by the database It will have to be parsed, qualified (names resolved), security-checked, optimized, and so on In short, each and every unique statement you execute will have to be compiled every time it is executed The second query uses a bind variable, :empno, the value of which is supplied at query execution time This query is compiled once and then the query plan is stored in a shared pool (the library cache), from which it can be retrieved and reused The difference between the two in terms of performance and scalability is huge, dramatic even.

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From the above description, it should be fairly obvious that parsing unique statements with hardcoded variables (called a hard parse) will take longer and consume many more resources than reusing an already parsed query plan (called a soft parse) What may not be so obvious is the extent to which the former will reduce the number of users your system can support Obviously, this is due in part to the increased resource consumption, but an even more significant factor arises due to the latching mechanisms for the library cache When you hard-parse a query, the database will spend more time holding certain low-level serialization devices called latches (see the chapter Locking and Latching for more details).

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