generate barcode in vb.net Lesson 1: Designing Database Tables in Visual C#.NET

Maker UPCA in Visual C#.NET Lesson 1: Designing Database Tables

Lesson 1: Designing Database Tables
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Further analysis determined that more than 80 percent of the total resources being consumed processor, memory, input/output (I/O) were involved in this conversion process. We created a simple test database that converted all the datetime columns into integers, along with stripping out all the conversion code, and then ran several tests. Queries that took seconds dropped to 50 millisec onds or less. Queries that took minutes dropped to a few seconds. In the most extreme case, a batch process that ran several times per day and could take as much as four hours in a given run now took less than five minutes to finish, regardless of the amount of data needing to be processed. Unfortunately, the application is still deployed with the data being stored in datetime columns and it is still spending 80 percent or more of the total resources consumed, converting this into a useable value for the application. It couldn t be changed because it would require a complete rewrite of more than 80 percent of the stored procedure code, along with affecting almost 100 percent of the tables in the database. Then there is also the larger issue of the database being for a packaged application, and customers had four different versions of the application running their businesses. Saying that the choice of a data type for a table really doesn t matter because stor age space is cheap really makes us wonder just how long it will take for perfor mance to become a problem (and a problem whose root cause can t be fixed because of business constraints). Although disk space is reasonably inexpensive and essentially limitless, all the data still has to be moved through memory and processors, and there is a maximum amount of memory and processors that cur rent hardware can support. Every byte that is wasted when data is stored need lessly consumes a byte of memory along with processor cycles when it is processed, although a single byte here or there won t affect anything. Losing a single byte per row in a table that contains millions of rows of data adds up quickly to memory pressure and high processor utilization.
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12
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Designing the Physical Database
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The first trade-off that you must consider when designing a database and its tables is whether to denormalize tables or not. Unfortunately, there isn t a straightforward for mula to determine whether denormalization can help. The end result of denormaliza tion is to reduce the number of tables that must be joined together. You are not saving storage space; you are saving processor cycles and memory space. Let s look at a simple example to understand the trade-offs you must evaluate when deciding to denormalize a database design. Fabrikam International has an order-entry system that tracks a variety of information such as orders, customers, addresses, and products. A customer is allowed to have more than one address but is allowed only a single address to be designated as the pri mary address. Orders can be shipped to any address and can contain multiple prod ucts, but an order can have only a single shipping address. The company has many requirements, some of which compete with each other:
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The data must consume the smallest amount of storage space possible. All queries must be as fast as possible while minimizing the number of tables that must be joined together. Read operations outweigh write operations by a 20-to-1 ratio. The primary address is used most frequently by customers and is always the address that is returned unless an order is being retrieved. All code used to access the data must be as simple as possible.
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At first thought, you might see some natural tables. The Customer table could contain all the customer information. The CustomerAddress table could contain all the addresses, along with a column to designate which address is the primary. The Orders table could contain order information and be linked to the Customer and Cus tomerAddress table. The OrderDetails table could be linked to the Orders and Prod ucts table. This design would certainly meet requirements to store data in as little storage space as possible by eliminating any data redundancies. However, with read operations outweighing write operations, and the primary address being required most often, you would have to join the Customers and CustomerAddress tables together while also picking out the primary address on a frequent basis. To solve the problem of having to join the Customers and CustomerAddress tables together, you decide to move the primary address into the Customers table. Now all the queries that require the primary address do not have to join to the CustomerAddress
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