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in department (Dept#), and was hired on (Hiredate). The four terms in parentheses are placeholders or parameters that correspond to the four values in the preceding proposition. When you substitute parameters with speci c values, a predicate reduces to an individual proposition. Here are the values for the parameters that reduce the predicate above to the proposition that precedes it: (17; Fernando; D1; July 19th, 2003) You can see that the parameters form a tuple. I wanted you to see that tuples in a relation actually represent propositions. Just as tuples represent propositions, relation headers represent the predicates for those propositions. I like this approach because it is very close to natural language. Just describe a business problem, nd predicates, and write them down you have your data model. Of course, you need a tool that converts predicates to relations. This natural language approach to modeling is called object-role modeling. It is described in Information Modeling and Relational Databases, 2nd edition by Terry Halpin and Tony Morgan (Morgan Kaufmann, 2008). But this is not a modeling book. You just need to understand what relations mean. You can think of them as containers of real-world entities or as predicates and propositions from natural language. Note that for the predicates I ve mentioned so far, there are no constraints on the tuple values that turn them into propositions, except that they must be values of the attribute types. I will deal with constraints shortly; for now, let me offer an informal, generic statement of the kind of rule you enforce with constraints: A proposition that evaluates false for the relation predicate (header) cannot be a part of the relation at any time.



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Views (and Other Virtual Relations)

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Views are an important part of a relational database. Also, an important part of queries in an application are temporary relations (or rowsets in SQL Server terminology). A view is a virtual relation; it is actually a stored query that is evaluated at run time when needed. A database user, application developer, or application should not be able to distinguish a view from a table. This is an important principle the principle of interchangeability, which states that there should be no distinction between actual (sometimes called base) relations and virtual relations. This principle provides logical data independence in a relational database. Logical data independence can help you a lot with two problems: growth and restructuring. If a table in a database grows too large, resulting in poor performance, you can subdivide it manually into several new tables, then unite those tables into a view whose name is the original table name. The new tables can even be in separate databases or on separate servers. If you need to restructure a table and cannot change an application that uses it, you can create a view that returns the original structure to the application. An application uses a view without knowing it is a virtual relation. However, views cannot provide total data independence. If you cannot hide all the changes of a table s structure from an application with a view, you have to change the application as well. For example, you might need to add an attribute that has to be inserted by end users manually.

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In this case, the page was simply submitted, causing only the Page_Load to be executed . Page_Load displays both the sessionString member variable (which is empty because it lives and dies with the page) and the data from the Session object (which lives independently of the page) . As you can see, session state is pretty convenient . However, you wouldn t get very far if all you could do was store simple strings and scalars . Fortunately, the session dictionary stores all manner of CLR objects .

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For the most part, dealing with remote objects is just like dealing with local objects, but in some situations this is not the case.

This concept of interchangeability can be extended further to table expressions queries that return relations inside outer queries. You probably already know about derived tables and common table expressions; you ll learn how to use them ef ciently in 6, Subqueries, Table Expressions, and Ranking Functions.

Naming conventions help you make more intuitive designs and write clearer code Your choice of convention is not as important as choosing a convention and using it consistently; I do not want to force a particular one on you Conventions are a matter of history, taste, system limitations, and so on Database designers tend to get really passionate about naming conventions I like the predicate-and-propositions approach to the meaning of relations For example, I am repeating the proposition I already mentioned: The employee with ID number 17 is named Fernando, works in department D1, and was hired on July 19th, 2003 I suggest that you should always be able to re-create the predicates and the propositions A tuple that represents this proposition is written in a relation with values only, like (17, Fernando, D1, 2003-07-19) It is easy to recreate this proposition if its predicate, ie.

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