Magic sets and other strange ways to implement logic programs (extended abstract)

Abstract

Several methods for implementing database queries expressed as logical rules are given and they are compared for efficiency. One method, called "magic sets," is a general algorithm for rewriting logical rules so that they may be implemented bottom-UP (= forward chaining) in a way that cuts down on the irrelevant facts that are generated.The advantage of this scheme is that by working bottom-up, we can take advantage of efficient methods for doing massive joins. Two other methods are ad hoc ways of implementing "linear" rules, i.e., rules where at most one predicate in any body is recursive. These methods are

Towards intelligent databases

“…1 We argue that both approaches have severe drawbacks. The first approach (the split of the original relation in two distinct smaller relation) examplifies an often criticized (although necessary) practice in relational database design: For reasons of storage (size) and coherency of the data (when updates are performed), the natural description of an application usually needs to be modified.…”

“…Since the first relational database systems were not capable of handling recursive views, deduction rules are 1 This representation is taken from the time table booklet published by Lufthansa.…”

“…Termination (or exhaustivity) is im portant in databases, for database users as opposed to programmers cannot be made responsible of termination of the queries they pose to a database. Finally, the speci fication given above provides with a simple formalization of the Alexander or Magic Set rewriting methods [1,2,57,7,55,4,21,8]: these rewritings are obtainable from the rule-based specification given above by partial evaluation (or partial deduction) [42,35,36,37,41]. These points are discussed in more detail in [13].…”

“…Instead of implementing several rewriting methods for, say, recursive query processing (e.g. [1,57,2,7,4]), for simplifying integrity constraints (e.g. [43,25,15]), for query optimization (e.g.…”

“…[17,18,1,2,4,7,55,57,60,61,67,13]), and how integrity constraints are checked when the database is updated (see e.g. [17,18,15,25,39,43,47,49,53,19]).…”