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    <p>The classic design approach would be (the star denotes the primary key column):</p> <pre><code>Product ProductId* CategoryId: FK to Category.CategroyId Name Category CategoryId* Name Property PropertyId* Name Type CategoryProperty CategoryId*: FK to Category.CategoryId PropertyId*: FK to Property.PropertyId ProductProperty ProductId*: FK to Product.ProductId PropertyId*: FK to Property.PropertyId ValueAsString </code></pre> <p>If you can live with the fact that every property value would go to the DB as a string and type conversion info is stored in the Property table, this layout would be enough.</p> <p>The query would go something like this:</p> <pre><code>SELECT Product.ProductId, Product.Name AS ProductName, Category.CategoryId, Category.Name AS CategoryName, Property.PropertyId, Property.Name AS PropertyName, Property.Type AS PropertyType, ProductProperty.ValueAsString FROM Product INNER JOIN Category ON Category.CategoryId = Product.CategoryId INENR JOIN CategoryProperty ON CategoryProperty.CategoryId = Category.CategoryId INNER JOIN Property ON Property.PropertyId = CategoryProperty.PropertyId INNER JOIN ProductProperty ON ProductProperty.PropertyId = Property.PropertyId AND ProductProperty.ProductId = Product.ProductId WHERE Product.ProductId = 1 </code></pre> <p>The more WHERE conditions you supply (conjunctively, e.g. using AND), the faster the query will be. If you have properly indexed your tables, that is. </p> <p>As it is, the solution is not ideal for a full text indexing situation. An additional table that stores all the text associated with a ProductId in a more denormalized way could help here. This table would need updating through triggers that listen for changes in the ProductProperty table.</p>
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