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winners�察�the table would need to be modified like this�此�



2000。05。31 nobody 5 6 13 23 25 37 43 

2000。06。03 jack jill 7 10 11 18 32 41 5 

2000。06。07 nobody 15 23 24 28 38 39 45 

2000。06。10 jack 1 3 12 23 29 33 27 

2000。06。14 nobody 2 4 13 19 39 45 26 

2000。06。17 nobody 3 8 17 19 21 25 35 


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                Here�察�another field indicates Jill as the second winner of the draw。 Adding another field  

           throws a monkey wrench into the entire table structure and makes processing much more  

           plicated�察�because the parsing routines will need to verify if another field is present。 This  

           breaks the nice grid structure and is plain wrong。 

                Another approach using the text file would be to create a third file that cross´references the  

          winners with the dates。 So the lottery file would go back to the original version�此�



           2000。05。31 5 6 13 23 25 37 43 

           2000。06。03 7 10 11 18 32 41 5 

           2000。06。07 15 23 24 28 38 39 45 

           2000。06。10 1 3 12 23 29 33 27 

           2000。06。14 2 4 13 19 39 45 26 

           2000。06。17 3 8 17 19 21 25 35 



                And a winners table would be created�此�



           2000。06。03 jack 

           2000。06。03 jill 

           2000。06。10 jack 



                The winners table is a grid of draw dates and winners on those dates。 Notice how there is  

           no entry for nobody�察�so only draw dates with winners are included。  



           *Note  These three tables are an example of correctly normalized data。 When the data is well normalized�察 �

           each table contains unique data。 In this example�察�one table contains all of the lottery drawings�察�but who the  

           winners are is stored in another table。 Using database relations�察�the winners and lottery data are related�察�yet  

           neither table needs to know about the other table。 



                Now what happens if two different people named Jack are lottery winners�拭�The data might  

           look like this�此�



           2000。05。31 nobody 5 6 13 23 25 37 43 

           2000。06。03 nobody 7 10 11 18 32 41 5 

           2000。06。07 nobody 15 23 24 28 38 39 45 

           2000。06。10 jack 1 3 12 23 29 33 27 

           2000。06。14 jack 2 4 13 19 39 45 26 

           2000。06。17 nobody 3 8 17 19 21 25 35 



                We know the two jack entries are not for the same Jack。 So now we have an additional  

           problem of uniqueness。 Uniqueness is not unusual when dealing with relational databases�察 �

           and the mon technique is to identify each Jack with a unique key。 For example�察�a unique  

           key could be jack_1 or jack_2。 The problem with using jack_1 and jack_2 is that you need to  

           search the database to see if there is a jack entry�察�and then find out the last jack entry。 Those  

           steps are resource´intensive and typically avoided。 Another solution is to use a database

           provided field that generates a unique key�察�which could be a row number or globally unique  

           identifier ��GUID��。 If the unique identifier were to be puter´generated�察�the table might look  

           as follows�此�


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                                            C HA P TE R   1 4   *    L E AR N I N G   AB O U T  R E L AT IO N A L   D AT AB A SE   D A TA 375 



2000。05。31 1877_ds 5 6 13 23 25 37 43 

2000。06。03 1877_ds 7 10 11 18 32 41 5 

2000。06。07 1877_ds 15 23 24 28 38 39 45 

2000。06。10 1023_ad 1 3 12 23 29 33 27 

2000。06。14 1022_xy 4 13 19 39 45 26 

2000。06。17 1877_ds 3 8 17 19 21 25 35 



      In the modified table�察�you would have no idea who the identifiers represent。 The way to  

find out is to take a key and open its associated field!say 1877_ds and the file 1877_ds。txt。  

Upon opening the file�察�you would know that the winner is nobody。 The process of finding out  

who the winner is involves more steps�察�but a relational database knows how to manage these  

types of relations quite effectively。  



                 WHY THE THOUSANDS OF APIS�察�LIBRARIES�察�AND TECHNIQUES�拭�



   In the space of 12 years�察�the following data´access technologies have emerged�此�Open Database Connectivity  

   ��ODBC���察�Remote Data Objects ��RDO���察�the Jet Database Engine�察�Data Access Object ��DAO���察�ActiveX Data Object  

   ��ADO���察�Object Linking and Embedding�察�Database ��OLE DB���察�ADO�察�and Language Integrated Query ��LINQ��。  

   This means that every 2 years�察�a new database technology is introduced。 Each database technology has libraries to  

   make it easier to write code。 The result is an amazing number of ways to access a piece of technology that is  

   nearly 40 years old。 

         So why do we have so many ways to access and manipulate the database�拭�Wouldn¨t we�察�as developers�察 �

   get our act together and work toward a mon approach to manipulating a relational database�拭�I can¨t give  

   a logical and accepted answer as to why there are so many data´access technologies。 But I can tell you what  

   I think。 

         For any real production application�察�it is not unmon to have tables that have 30 columns。 When  

   writing code to add�察�delete�察�and modify a row in a table that has 30 fields�察�you are�察�for the most part�察�trying to  

   figure out which field goes to which piece of data。 Thus�察�people try to automate the job。 After all�察�it is more  

   interesting to work through a threading bug than an incorrect´field´placement bug。 

         Another issue is a technology mismatch between a programming language and a relational database。 A  

   relational database treats data as a set。 There are no individual pieces of data in a relational database。 Programming  

   languages treat data as individuals。 Even in a collection class�察�you have an individual class managing a set of  

   individual references。 This causes a mismatch�察�and trying to bind to the two technologies is difficult。 

         So when you are writing database code�察�you are trying to automate the fitting of a square peg into a round  

   hole。 You get many extremely creative ideas and results�察�but at the end of the day�察�you are still fitting a square  

   peg into a round hole。  

         The essence of the problem when dealing with sets of data in a programming language is how to  

   integrate the two。 There is light at the end of the tunnel�察�in the form of programming language alterations  

   such as LINQ。 LINQ will be discussed in the next chapter。  



Accessing Relational Databases 



Regardless of the database implementation that you use�察�a mon architecture is employed�察 �

as illustrated in Figure 14´1。 


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           Figure 14´1。 mon database architecture 



                Most relational database servers are separate applications that run on their own。 To interact  

           with a running relational database�察�the database vendor provides a database driver。 In �察�a  

           database driver is a piece of proprietary code that talks to the relational database server�察�but  

           exposes its functionality using the ADO layer。 

                The ADO layer is a technology that abstracts the database client into a neutral set of  

           interfaces。 By itself�察�ADO does not implement any technologies�察�but it defines the inter

           faces that a database needs to have implemented。 ADO is similar to the lighting manager  

           application introduced in Chapter 8�察�where specific lighting implementations need to imple

           ment interfaces。 

                The ADO code can be accessed directly in your application by your code。 However�察 �

  
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