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Prescription 6: The Rule Engine Is a Relational DBMS
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It is well known see, e.g., reference [2] that domains (or types) and relations are together both necessary and sufficient to represent absolutely any data whatsoever, at least at the conceptual level. It is also well known that the relational operators (join, etc.) are closely related to, and have their foundation in, the discipline of first-order predicate logic; they therefore provide an appropriate formalism for the declarative statement of rules, at least at the conceptual level. It follows that it is necessary and sufficient that the rule engine shall be, specifically, a relational DBMS,4 at least at the conceptual level.
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4. Not necessarily, and ultimately not even desirably, an SQL DBMS specifically. (Considered as an attempt at a concrete realization of the constructs of the abstract relational model, SQL is very seriously flawed. Again, see, e.g., reference [2].)
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CHAPTER 15 TWELVE RULES FOR BUSINESS RULES
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Here are some specific consequences of the foregoing: The Information Principle: The totality of data in the database shall be represented at the conceptual level by means of relations (and their underlying domains) only. To say the same thing in another way, the database at any given time shall consist of a collection of tuples; each such tuple shall represent a proposition that (a) is an instantiation of the predicate corresponding to the relation in which it appears and (b) is understood by convention to be TRUE. The Principle of Interchangeability of Views and Base Relations: The system shall support relational views, which, as far as the user is concerned, look and feel exactly like base relations; that is, as far as the user is concerned, views shall have all and only the properties that base relations have (e.g., the property of having at least one candidate key). In particular, views, like base relations, shall be updatable [1,2]. Database is a purely logical concept: The term database throughout this chapter refers to the database as perceived by the user, not to any kind of physical construct at the physical storage level. In the extreme, one logical database, as the term is used herein, might map to any number of physically stored databases, managed by any number of different DBMSs, running on any number of different machines, supported by any number of different operating systems, and connected together by any number of different communication networks. Overall, the rule engine shall function from the user s point of view as an abstract machine. It shall not be necessary to go to a lower level of detail in order to explain any part of the functioning of that abstract machine (i.e., the definition of that abstract machine shall be logically self-contained).
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Prescription 7: Rule Management
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Since rules are not just data but, more specifically, metadata, the portion of the database in which they are held shall conceptually be some kind of catalog. It is convenient to refer to that portion of the database as the rule catalog specifically. By definition, the rule catalog shall be relational. Suitably authorized users shall be able to access that catalog (for both retrieval and update purposes) by means of their regular data access interface. Note: This prescription does not prohibit the provision of additional, specialized interfaces for rule catalog access. To the maximum extent logically possible, the rule engine shall: Detect and reject cycles and conflicts in the rule catalog Optimize away redundancies in the rule catalog Permit rule catalog updates to be performed without disruption to other system activities, concurrent or otherwise See also the discussion of standard DBMS benefits under Prescription 5.
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CHAPTER 15 TWELVE RULES FOR BUSINESS RULES
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Prescription 8: Kinds of Constraints
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Integrity constraints shall be divisible into four kinds, as follows [1,2]: A type constraint is, logically speaking, nothing more nor less than a definition of the set of values that constitute the type (domain) in question. Such a constraint shall not mention any variables. Note: The constraint that one type is a subtype of another (which provides the basis for supporting inheritance of certain properties from one type to another, of course) is a special kind of type constraint [2]. That is, type constraints shall include what are sometimes called IS A constraints (not to be confused with HAS A constraints! again, see reference [2]) as a special case. An attribute constraint is a constraint on the values a given attribute is permitted to assume. More precisely, an attribute constraint shall specify that the attribute in question is of a given type (domain). A relation constraint5 is a constraint on the values a given relation is permitted to assume. Such a constraint shall be of arbitrary complexity, except that it shall mention exactly one variable (viz., the relation in question). A database constraint is a constraint on the values a given database is permitted to assume. Such a constraint shall be of arbitrary complexity, except that it shall mention at least two variables, and all variables mentioned shall be relations in the database. Note: The distinction between relation constraints and database constraints is primarily a matter of pragma it can be helpful in practice, but it is not all that important from a theoretical standpoint. In the case of database and relation constraints (only), the constraint shall also be allowed to constrain transitions from one value to another. A constraint that is not a transition constraint is a state constraint. In no case shall a constraint explicitly mention the update events that need to be monitored in order to enforce the constraint; rather, determining those events shall be the responsibility of the rule engine. All constraints shall be satisfied at statement boundaries. That is, no statement shall leave the database in such a state as to violate any state or transition constraint, loosely speaking. Note: See reference [2] for a more precise formulation of this requirement in particular, for a precise explanation of exactly what it is that constitutes a statement here. As well as enforcing constraints, the rule engine shall make its best attempt to use them for purposes of semantic optimization [1].
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5. More correctly referred to as a relation variable, or relvar, constraint (see references [1] and [2]). The term relation is unfortunately used in common database parlance to mean sometimes a relation value, sometimes a relation variable (i.e., a relvar). While this practice can lead to confusion, it is followed in the present chapter somewhat against my better judgment! for reasons of familiarity.
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