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CHAPTER 12 DATA REDUNDANCY AND DATABASE DESIGN
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The general form of the REFRESH clause is REFRESH EVERY <now and then> where <now and then> might be, for example, MONTH or WEEK or DAY or HOUR or n MINUTES or MONDAY or WEEKDAY (and so on). In particular, the specification REFRESH [ON] EVERY UPDATE means the snapshot is kept permanently in synch with the relvar(s) from which it is derived which is presumably just what we want, in the case of Example 12. Now, in this section so far I ve concentrated on Example 12 and derived data. However, the fact is that all forms of redundancy can be thought of as derived data: If x is redundant, then by definition x can be derived from something else in the database. (Limiting use of the term derived data to the kind of situation illustrated by Example 12 is thus misleading and not recommended.) It follows that the foregoing analysis in particular, the four different approaches to dealing with derived data can be generalized to apply to all kinds of redundancy, at least in principle. Note in particular that the third and fourth of those approaches, using views and snapshots respectively, both constitute examples of what s sometimes called controlled redundancy. Redundancy is said to be controlled if it does exist (and the user is aware of it), but the task of propagating updates to ensure that it never leads to any inconsistencies is managed by the system, not the user. Uncontrolled redundancy can be a problem, but controlled redundancy shouldn t be. In fact, I want to go further I want to say that while it s probably impossible, and possibly not even desirable, to eliminate redundancy one hundred percent, any redundancy that isn t eliminated ought at least to be controlled. We need support for snapshots!
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Concluding Remarks
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Near the beginning of this chapter, I mentioned some attempts at characterizing the notion of redundancy. I m still not sure we have a good operational definition of the term in principle, it s surely the case that something involves redundancy if and only if it can be made smaller in some way but this statement isn t much use as any kind of guidance on how to deal with the problem. On balance, I think the most useful statement is:25 The database involves some redundancy if and only if the same proposition can be derived from it in two different ways. In particular, we don t want the same tuple t to appear in two different places if those two appearances denote the same proposition. (Obviously we d like to prohibit duplicate propositions as such; unfortunately, however, the DBMS doesn t understand propositions.) But it s all right for the same tuple to appear twice if those two appearances don t denote the same proposition; and in any case we can have redundancy without any tuple appearing twice at all, as we ve seen. Normalization and orthogonality seem to be all we have by way of a scientific attack on the issue at the present time. Unfortunately, we ve seen that normalization and orthogonality don t solve the whole problem they can be used to reduce redundancy, but they can t eliminate it entirely, in general. (In the section Other Kinds of Redundancy, we saw several examples of designs that fully conformed to the principles of normalization and orthogonality and yet involved redundancy, and that section was certainly far from exhaustive.) We need more science!
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25. But see 13.
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CHAPTER 12 DATA REDUNDANCY AND DATABASE DESIGN
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Given the foregoing state of affairs, it seems that redundancy will definitely exist in most databases. If it does: It should at least be controlled, in the sense that the DBMS should take responsibility for guaranteeing that it will never lead to inconsistency. If it can t be controlled, then appropriate constraints should at least be declared and enforced to ensure (again) that it never leads to inconsistency. If it can t be controlled and constraints can t be declared and enforced, then you re on your own and woe betide you if you make any mistakes. Sadly, this last scenario is the one most likely to apply in practice, given the state of today s commercial implementations. I ll close with a couple of acknowledgments. First, I d like to thank Hugh Darwen for continually prodding me to tighten up my thinking on this topic. His criticisms of, and objections to, orthogonality in particular were what spurred me to get my thoughts on the subject into some kind of order and to write the present chapter (which he also reviewed, and I thank him for that review, too). Second, I want to acknowledge the contributions of David McGoveran in this area. It was David who originally came up with The Principle of Orthogonal Design, which he and I first described in a joint paper, A New Database Design Principle, in my book Relational Database Writings 1991 1994 (Addison-Wesley, 1995). I need to warn you, however, that the definition of orthogonality has changed over the years, and I have reason to believe that David s definition and mine now differ somewhat. Please note too that all remarks in the present chapter regarding my own definition are subject to refinement as explained in the next! Caveat lector.
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