ACM SIGMOD Anthology VLDB dblp.uni-trier.de

The Glue-Nail Deductive Database System: Design, Implementation, and Evaluation.

Marcia A. Derr, Shinichi Morishita, Geoffrey Phipps: The Glue-Nail Deductive Database System: Design, Implementation, and Evaluation. VLDB J. 3(2): 123-160(1994)
@article{DBLP:journals/vldb/DerrMP94,
  author    = {Marcia A. Derr and
               Shinichi Morishita and
               Geoffrey Phipps},
  title     = {The Glue-Nail Deductive Database System: Design, Implementation,
               and Evaluation},
  journal   = {VLDB J.},
  volume    = {3},
  number    = {2},
  year      = {1994},
  pages     = {123-160},
  ee        = {db/journals/vldb/DerrMP94.html},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

We describe the design and implementation of the Glue-Nail deductive database system. Nail is a purely declarative query language; Glue is a procedural language used for non-query activities. The two languages combined are sufficient to write a complete application. Nail and Glue code are both compiled into the target language IGlue. The Nail compiler uses variants of the magic sets algorithm and supports well-founded models. The Glue compiler's static optimizer uses peephole techniques and data flow analysis to improve code. The IGlue interpreter features a run-time adaptive optimizer that reoptimizes queries and automatically selects indexes. We also describe the Glue-Nail benchmark suite, a set of applications developed to evaluate the Glue-Nail language and to measure the performance of the system.

Copyright © 1994 by the VLDB Endowment. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by the permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment.

Key Words

Language, performance, query optimization.

Online Paper

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