Toward logical data independence: a relational query language without relations

  • Authors:

  • D. Maier;D. Rozenshtein;S. Salveter;J. Stein;D. S. Warren

  • Affiliations:

  • State University of New York at Stony Brook, Stony Brook, New York;State University of New York at Stony Brook, Stony Brook, New York;State University of New York at Stony Brook, Stony Brook, New York;State University of New York at Stony Brook, Stony Brook, New York;State University of New York at Stony Brook, Stony Brook, New York

  • Venue:
  • SIGMOD '82 Proceedings of the 1982 ACM SIGMOD international conference on Management of data
  • Year:
  • 1982

Quantified Score

Hi-index 0.00

Visualization

Abstract

One of the main goals of database systems, relational systems in particular, is to provide a degree of physical data independence for users and programs. Users should not need to know the exact physical storage structures to use the database, and should be protected from changes in those structures. We attempt to go a step further, to logical data independence. We want an interface to a relational database where a user need not be concerned with how the data has been partitioned into various relations. The natural relation schemes to be used, from a semantic point of view, may be decomposed in the database for normalization or redundancy reasons. Our approach essentially loads all the semantics onto the attributes. In our query language tuple variables are not bound to specific relations. Rather, the system uses the set of attributes, say X, that appear in a query with a tuple variable, say t, to combine the database relations to form a single relation with scheme X over which t ranges. We describe our method for constructing such a relation given the associated set of attributes X. When tuple variables are bound implicitly, the logical connectives 'and', 'or', and 'not' take on 'semantic overtones' since they can affect the binding. We discuss the motivation behind the chosen semantics for these connectives. Our goal is a powerful, yet concise, query language with natural semantics.