Download Applications of Logic Databases by Oris Friesen, Gilles Gauthier-Villars (auth.), Raghu PDF

By Oris Friesen, Gilles Gauthier-Villars (auth.), Raghu Ramakrishnan (eds.)

The premise in the back of constructing strong declarative database languages is compelling: by means of allowing clients to specify their queries (and their integrity constraints) in a transparent, non-operational approach, they make the user's activity more uncomplicated, and supply the database procedure with extra possibilities for optimization. Relational database platforms provide a amazing evidence that this premise is certainly legitimate. the preferred relational question language, SQL, relies upon relational algebra and calculus, i.e., a small fragment of first-order good judgment, and the benefit of writing queries in SQL (in comparability to extra navigational languages) has been a huge consider the economic good fortune of relational databases. it's famous that SQL has a few vital barriers, inspite of its luck and recognition. particularly, the question language is non-recursive, and aid for integrity constraints is proscribed. certainly, spotting those difficulties, the newest ordinary, SQL-92, offers elevated help for integrity constraints, and it's expected that the successor to the SQL-92 usual, known as SQL3, RECURSIVE UNION operation [1]. good judgment database platforms have will contain a focused on those extensions to the relational database paradigm, and a few platforms (e.g., Bull's DEL prototype) have even integrated object-oriented gains (another extension more likely to look in SQL3).

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We present our conclusions in Section 6. Q-Data: Improving Data Quality 2 27 RELATED WORK Our investigation in data validation and cleanup is driven by specific needs of our clients. These needs are similar to those discussed (albeit at a high-level) in [10] and [16]. [10] discusses developing a (new) corporate subject database consisting of customer information by cleaning up data from multiple legacy systems. One application discussed in [16] involves verifying that related data in three legacy application systems are consistent.

Prolog does not guarentee that any particular query will terminate. • Prolog does not guarantee that any particular query will return all matching data items. Prolog for string matching: Advantages Another major sub-task in Q-Data was to determine whether two strings were duplicates of each other. A special kind of rule called a "soft string match" was needed which would match two strings even if there were misspellings, abbreviations, letter transpositions and/or different word order in the two strings.

The rest of this chapter is organized as follows. Section 2 briefly discusses some of the related work. Section 3 describes the overall data cleanup problem faced by a typical customer, and identifies several specific data cleanup tasks that are used as examples. Section 4 describes the software architecture for the Q-Data prototype system. Our experiences analyzing available technologies as components of Q-Data, and designing, building, and testing the prototype are discussed. We also describe in greater depth the strengths and weaknesses of LDL, Prolog, c++ and SQL languages and their implementations, for searching and control, database access, and rule specifications.

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