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CHAPTER 5 ON THE LOGICAL DIFFERENCE BETWEEN MODEL AND IMPLEMENTATION
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Mary Loomis, ODBMS vs. Relational, Journal of Object-Oriented Programming, July/ August 1990: Relational database design is really a process of trying to figure out how to represent real-world objects within the confines of tables in such a way that good performance results and preserving data integrity is possible [note the confusion over logical vs. physical design here] ... [Many] normalized tables could be required to represent a single real-world object class ... This is exactly the root of the performance difficulties with relational DBMSs ... Users and programs typically want to access and manipulate objects, not tables. To manifest an object from its corresponding tables, an RDBMS must do joins. One of the slowest things that RDBMSs do is joins. The more joins there are, the slower the system is to the point of unacceptability. An ODBMS has no concept of joining. Such processing simply is not necessary when objects are stored as objects. John Taschek, ODBMSs Take On Relational Models [note that plural, by the way!], PCWeek, October 9th, 1995: Relational database servers also depend on primary and foreign keys to link data from separate tables. This means that database administrators must normalize the tables (an often complex process) so that queries can run efficiently and effectively. Databases that consist of a large number of tables are therefore difficult to manage and may be slower since the database engine must go through the complex process of filtering data from each table. The common thread running through these quotes is clearly the assumption or assertion, rather that joins are slow. I ve had occasion to address this claim in print before (see, e.g., the article Objects and Relations: Forty-Seven Points of Light in my book Relational Database Writings 1994 1997, Addison-Wesley, 1998, on which the following response is partly based). The fact is, anyone who advances such a claim is seriously confused over the logical difference between model and implementation. Let me elaborate: First of all, joins are a model concept, while performance is an implementation concept. Thus, the claim that joins are slow, as such, is simply nonsense; it s an apples-andoranges comparison. Now, we might legitimately claim that the way joins are implemented in some particular product isn t very efficient; we might even be correct in making such a claim; but the two claims are logically different things. All logical differences are big differences! Second, the joins are slow claim usually serves as lead-in to an argument that pointers are faster (Doug Barry makes such an argument explicitly, and the other writers quoted do so implicitly). In other words, advocates of the joins are slow position usually argue that following a pointer from the referencing table to the referenced table or vice versa is a good i.e., efficient implementation mechanism. Fine: I ll agree to this point for the sake of the argument (though only for the sake of the argument, please note!). But there s absolutely no reason why joins shouldn t be implemented by following pointers internally. Of course, I know they typically aren t implemented that way in today s SQL products, but that s a deficiency of those products; it s certainly not a defect in, or valid criticism of, the model. In other words, (1) implementing joins by pointers is very different from (2) exposing such pointers in the model. The fact that (1) might be a good idea doesn t imply that (2) is a good idea, and of course it categorically isn t.
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CHAPTER 5 ON THE LOGICAL DIFFERENCE BETWEEN MODEL AND IMPLEMENTATION
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Third, there s a tacit assumption underlying such claims (i.e., that joins are slow) that tables as seen by the user map one-to-one to chunks of contiguous storage on the disk with the implication that joining two tables means accessing two separate chunks of storage, and hence I/O overhead. This assumption isn t always valid, even today (witness, e.g., Oracle s hierarchic clustering feature). What s more, much more sophisticated facilities are likely to be available in this connection soon (i.e., DBMSs are likely to offer much more effective data-to-storage mapping capabilities in the near future). I plan to examine this latter possibility in writing very soon. Here s another quote on performance issues. Obviously it commits the same fundamental error (i.e., of thinking the model has something to do with performance), but it also manages to inject some novel errors of its own: Robin Bloor, All in the Name of Progress, DBMS Magazine, January 1995: [VMark s product] uniVerse ... is a post-relational database [sic] with multidimensional viewing capabilities. It implements the NF2 data model, which is non-first normal form. That is, it adheres to and implements all of the normalizations advocated by E. F. Codd, except for the first. As far as I know, the NF2 data model was invented by IBM in an attempt to address performance problems that occur with relational databases, and it is exceedingly useful when dealing with multidimensional arrays. Points arising: To do him credit, Bloor himself later in the same article objects to the use of the marketing term post-relational. So do I! see my article What Do You Mean, Post-Relational ( 21 in the present book). However, I also object to Bloor s use of the term database to mean DBMS another logical difference here, in fact, and one I ll probably come back to in some future writing. I discussed the NF2 data model more usually called the NF data model in my recent article What First Normal Form Really Means ( 8 in the present book). The claims that uniVerse supports that model and that it therefore adheres to ... all of the normalizations advocated by E. F. Codd, except for the first betrays a serious lack of understanding on Bloor s part, however. To be specific:
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If it supports repeating groups as I defined them in What First Normal Form Really Means which is what Bloor might mean when he says uniVerse supports the NF model then its basic data object isn t a relation at all, and the concept of all normalizations except the first simply doesn t apply. On the other hand, if it doesn t support such repeating groups, then it certainly does support first normal form, in the sense that its basic data objects do represent relations. (I m ignoring the possibility here that the product might commit some other error, not mentioned by Bloor, that would make the foregoing sentence invalid.)
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