visual basic barcode Common Security Scenarios in .NET
9 Dynamic SQL
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Other Uses for Stub Zones
quantity and price but not allow addition, which has no meaning in this context . This is an example of how a database management system could prevent meaningless operations by using specialized types for quantity and price that are more restrictive than generic number types . As you know, relational databases are based on set theory . A relation represents a set that is, a set of propositions . A set contains distinct members; therefore, you need a way to distinguish propositions . You need to define candidate keys, out of which you will choose one as the primary key . A key is a minimal set of attributes needed to uniquely identify any proposition . In addition, relations are associated through keys; a foreign key in one relation matches a key from another relation . Domains and keys are sufficient to implement all possible constraints . This is how the Domain-Key normal form (DKNF) is defined: a database is in Domain-Key Normal Form if every constraint in the database is a logical consequence of the definition of keys and domains . A relation in a DKNF database is free from all update anomalies . Of course, there is no simple algorithmic procedure to implement DKNF . Achieving DKNF would involve a lot of programming . Although achieving DKNF seems to be something you should pursue, it is not an easy task . Let me give you an example of an advanced constraint that would be very hard to implement with domains and keys only . You are probably already familiar with adjacency list for modeling graphs, trees, and hierarchies . If you are not familiar with this model yet, please refer to T-SQL Querying . In short, within an adjacency list, each tuple contains its own key and a key of the parent tuple, like in a bill of materials (BOM): BOM {partid, assemblyid, othercolumns} Just try to imagine how you would implement a constraint that the BOM has to be antisymmetric the assembly cannot be contained in a part it contains . Steve Kass suggested the following possible solution . Create a table named Containments, whose tuples have the form (first_part, second_part, direction) . Apply a domain constraint that restricts (first_part, second_part) to a domain two_parts_alphabetical, containing all pairs of parts (first_part, second_part) where first_part precedes second_part in some well-defined ordering of parts_domain elements . Apply another domain constraint to direction, limiting it to the set of values { 1, 1} . The predicate for the table would be (first_part is contained in second_part and direction = 1) OR (second_part is contained in first_part and direction = 1) . Two key constraints would be the foreign key constraints on first_part and second_part, and a third key constraint would be that (first_part, second_part) is the primary key of Containments . This latter key constraint, together with the domain constraint that first_part<second_part guarantees that the table does not represent both containment directions . Although this is a very clever solution, it would not be easy to use . Many times such advanced constraints are easier to implement with other means than a relational database management system provides, such as declarative constraints and triggers . Note You need to change the druby:// URL in the client example to match the URL given in output by
Categories of counters for monitoring performance
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