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In order to develop the conceptual basis for database planning we have used relations as the basic units and classi ed ve types of relations in order to describe the required choices Many other models to aid database design have been developed and have in uenced the concepts presented here The relational model which provides the basis for the conceptual view presented in this chapter allows a great deal of formal analysis Several early papers (Langefors63 , Levien67 , and Childs68 ) suggested the use of a model based on set theory to describe le and database structures Most of the current activity was kicked o by EF Codd, who, in a series of papers (Codd70,74 , and in Rustin72) , presented the relational model in terms of its relevance to database design and implementation In a second paper in Rustin72 , Codd describes the required operations and their power Associated early contributions are Heath and Date in Codd71 , Delobel73 , Armstrong74 , Wang75 , and Forsyth in King75 , which provided mathematically oriented criteria for the optimization, manipulation, and demonstration of the correctness of the manipulations in relational models Fagin77 de ned multivalued dependencies and a fourth normal form Up to seven normalizations have been proposed (Beeri78 ) Issues of relational decomposition are summarized by Maier80 The mathematical theory of dependencies in databases is now a sub eld of its own, with a rapidly exploding literature The set of axioms de ning transformations is due to Armstrong74 A basic text is Ullman82 and recent results may be found in journals, see for instance, Sadri82 and in the proceedings of the ACM-PODS conferences (Aho82 )

RAID Level 3 has a single check disk with parity information Thus, the reliability overhead for RAID Level 3 is a single disk, the lowest overhead possible The performance characteristics of RAID Level 2 and RAID Level 3 are very similar RAID Level 3 can also process only one I/O at a time, the minimum transfer unit is D blocks, and a write requires a read-modify-write cycle

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The double and float types hold fractional values Although double is larger than float, and you would think that float would suffice most of the time, the compiler assumes that any number with a decimal point in it is a double unless you follow the number with the letter f That is, 47 is assumed to be double, but 47f is a float The decimal value type was added to the language to support scientific and financial applications; to use it, you append an m to the end, just as you do with the f for a float.

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The float and double types have a very slight amount of imprecision to them if the values are very large or very small not something you ll need to worry about in this book, certainly, but it might cause problems if you were trying to do very precise scientific or financial calculations, which is why decimal is there Typically, you decide which size integer to use (short, int, or long) based on the magnitude of the value you want to store For example, a ushort can only hold values from 0 through 65,535, whereas a uint can hold values from 0 through 4,294,967,295 That being said, in real life most of the time you ll simply declare your numeric variables to be of type int, unless there is a good reason to do otherwise (Most programmers choose signed types unless they have a good reason to use an unsigned value.

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