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To normalize data in one or more existing data tables, do the following: 1. Identify data fields with repeating data values or multipart data values (for example, contact name and address data values or product name and manufacturer data values contained in the same data field). Break these data values into multiple data fields (for example, separate data fields for name, address, product name, or manufacturer data values). 2. Group data fields with related data values into separate data tables (for example, a data table for contacts, a data table for products, or a data table for manufacturers). 3. Eliminate repeating data values in each data table (for example, a repeated address or a repeated product name). 4. Assign a primary key data field to each data table and a unique identifier for each data record in that data table (for example, a unique contact identification number or a unique product part number). 5. Add foreign key data fields as needed to cross-reference related data records contained in multiple data tables (for example, foreign key data fields describing the relationships between products and manufacturers, cross-referencing primary key data values in the separate product and manufacturer data tables). 6. Create additional data tables and use foreign keys as needed to store data records containing unique facts and figures (for example, a product sales transaction data table containing individual sales transaction details, cross-referencing primary key data values in the product/manufacturer data table).

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they depend on and storing them away until needed. In optimized F# code, the F# compiler often avoids this and instead passes extra arguments to the function implementations. Closure is a powerful technique that is used frequently in this book. It s often used in conjunction with functions, as in this chapter, but is also used with object expressions, sequence expressions, and class definitions.

< php $db = DBManagerFactory::getInstance(); $res = $db->query("select * from users"); while ( $row = $db->fetchByAssoc($res) ) { // remove the admin privilege from any non-active users if ( $row['status'] != 'Active' ) { $db->query("update users set is_admin = 0 where id = '{$row['id']}'"); } }

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The function remap from the previous section generates values of type Point -> Point You can think of this type as a way of representing the family of transformations for the type Point Many useful concepts can be modeled using function types and values For example: The type unit -> unit is frequently used to model actions: operations that run and perform some unspecified side effect For example, consider the expression (fun () -> printfn "Hello World") Types of the form type -> type -> int are frequently used to model comparison functions over the type type You also see type * type -> int used for this purpose, where a tuple is accepted as the first argument In both cases, a negative result indicates less than, zero indicates equals, and a positive result indicates greater than Many collection types accept such a value as a configuration parameter.

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