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CHAPTER 12 DATA REDUNDANCY AND DATABASE DESIGN
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particular kind of redundancy isn t present. With this possibility ruled out, then, it s tempting to set a stake in the ground and say again that redundancy at the logical level is always undesirable. In order to adopt such a position, however, we need to be able to say what we mean by redundancy for otherwise the position can t possibly make sense. And even if we can come up with a good definition of the term, is the position that redundancy at the logical level is always bad really tenable Is it possible to eliminate all redundancy Is it even desirable These are questions of considerable pragmatic importance, of course. Indeed, I think it s noteworthy that Codd called his very first paper on the relational model Derivability, Redundancy, and Consistency of Relations Stored in Large Data Banks (IBM Research Report RJ599, August 19th, 1969; emphasis added). And his second paper, A Relational Model of Data for Large Shared Data Banks (CACM 13, No. 6, June 1970) this is the one that s usually regarded as the seminal paper in the field, though that characterization is a little unfair to its 1969 predecessor was in two parts of almost equal length, the second of which was called Redundancy and Consistency (the first was Relational Model and Normal Form ). In both of these papers, in other words, Codd regarded his thoughts on redundancy as a major part of the contribution of his relational work: rightly so, in my opinion, since he did at least provide us with a framework in which we could begin to address the issue precisely and systematically. Here then are some attempts at pinning down the notion of redundancy a little more precisely: The database involves some redundancy if and only if it can be divided into two disjoint partitions such that the very same relation can be derived from both. The database involves some redundancy if and only if there exists at least one relation or attribute or tuple that can be removed without having any effect on the set of relations that can be derived from it (the database, that is). The database involves some redundancy if and only if it says the same thing twice. (As a matter of fact this attempt isn t too bad, if only we can pin down precisely what it means for the database to say something. Part of the purpose of this chapter is to address this very issue.) Other characterizations are doubtless possible, too. Without further ado, therefore, let s embark on our investigation.2
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I ll base most of my examples on the usual suppliers-and-parts database. Definitions of the relvars in that database, expressed in Tutorial D (see the next section), follow immediately; sample values are shown in Figure 12-1.
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2. Investigation is indeed the mot juste here; the chapter is far from definitive. In particular, you shouldn t read it without reading the further thoughts in the next chapter as well.
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CHAPTER 12 DATA REDUNDANCY AND DATABASE DESIGN
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VAR S BASE RELATION /* suppliers */ { S# S#, SNAME NAME, STATUS INTEGER, CITY CHAR } KEY { S# } ; VAR P BASE RELATION /* parts */ { P# P#, PNAME NAME, COLOR COLOR, WEIGHT WEIGHT, CITY CHAR } KEY { P# } ; VAR SP BASE RELATION /* shipments */ { S# S#, P# P#, QTY QTY } KEY { S#, P# } FOREIGN KEY { S# } REFERENCES S FOREIGN KEY { P# } REFERENCES P ;
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Some Prerequisites
In order to keep this chapter to a comparatively reasonable length, I m going to have to assume you re familiar with the relational model in general and all of the following in particular: The logical difference between relation values (relations for short) and relation variables (relvars for short) The logical difference between base and derived relvars, and the fact that views or virtual relvars in particular are derived
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