Deductive query processing with an object-oriented semantic network in a massively parallel environment

Sang Hyun Oh, Won Suk Lee

Research output: Contribution to journalArticle

Abstract

Most research related to parallel query processing has concentrated on how to properly partition and schedule operation-by-operation and tuple-by-tuple query processing jobs to available processors. As a result, because these operations should perform complex query optimization, tremendous overhead can be involved, especially in a massively parallel system with thousands of processors. Furthermore, there exist unnecessary dependencies among operations allocated in different processors, and a large amount of intermediate data must be exchanged among processors. This article proposes an effective deductive query processing method in a massively parallel system. For this, the facts and deductive rules of a deductive database are partitioned into fine-grain semantic elements based on the concepts of an object-oriented model. These semantic elements are used to construct an object-oriented semantic network (OOSN). Because all facts and deductive rules are mapped to the OOSN statically, a query can be evaluated effectively in a distributed manner without any complex query optimization.

Original languageEnglish
Pages (from-to)85-95
Number of pages11
JournalInternational Journal of Computers and Applications
Volume26
Issue number2
Publication statusPublished - 2004 Apr 23

Fingerprint

Query processing
Semantics

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

Cite this

@article{9f175e116e604e48bc19cab0c0930084,
title = "Deductive query processing with an object-oriented semantic network in a massively parallel environment",
abstract = "Most research related to parallel query processing has concentrated on how to properly partition and schedule operation-by-operation and tuple-by-tuple query processing jobs to available processors. As a result, because these operations should perform complex query optimization, tremendous overhead can be involved, especially in a massively parallel system with thousands of processors. Furthermore, there exist unnecessary dependencies among operations allocated in different processors, and a large amount of intermediate data must be exchanged among processors. This article proposes an effective deductive query processing method in a massively parallel system. For this, the facts and deductive rules of a deductive database are partitioned into fine-grain semantic elements based on the concepts of an object-oriented model. These semantic elements are used to construct an object-oriented semantic network (OOSN). Because all facts and deductive rules are mapped to the OOSN statically, a query can be evaluated effectively in a distributed manner without any complex query optimization.",
author = "Oh, {Sang Hyun} and Lee, {Won Suk}",
year = "2004",
month = "4",
day = "23",
language = "English",
volume = "26",
pages = "85--95",
journal = "International Journal of Computers and Applications",
issn = "1206-212X",
publisher = "ACTA Press",
number = "2",

}

Deductive query processing with an object-oriented semantic network in a massively parallel environment. / Oh, Sang Hyun; Lee, Won Suk.

In: International Journal of Computers and Applications, Vol. 26, No. 2, 23.04.2004, p. 85-95.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Deductive query processing with an object-oriented semantic network in a massively parallel environment

AU - Oh, Sang Hyun

AU - Lee, Won Suk

PY - 2004/4/23

Y1 - 2004/4/23

N2 - Most research related to parallel query processing has concentrated on how to properly partition and schedule operation-by-operation and tuple-by-tuple query processing jobs to available processors. As a result, because these operations should perform complex query optimization, tremendous overhead can be involved, especially in a massively parallel system with thousands of processors. Furthermore, there exist unnecessary dependencies among operations allocated in different processors, and a large amount of intermediate data must be exchanged among processors. This article proposes an effective deductive query processing method in a massively parallel system. For this, the facts and deductive rules of a deductive database are partitioned into fine-grain semantic elements based on the concepts of an object-oriented model. These semantic elements are used to construct an object-oriented semantic network (OOSN). Because all facts and deductive rules are mapped to the OOSN statically, a query can be evaluated effectively in a distributed manner without any complex query optimization.

AB - Most research related to parallel query processing has concentrated on how to properly partition and schedule operation-by-operation and tuple-by-tuple query processing jobs to available processors. As a result, because these operations should perform complex query optimization, tremendous overhead can be involved, especially in a massively parallel system with thousands of processors. Furthermore, there exist unnecessary dependencies among operations allocated in different processors, and a large amount of intermediate data must be exchanged among processors. This article proposes an effective deductive query processing method in a massively parallel system. For this, the facts and deductive rules of a deductive database are partitioned into fine-grain semantic elements based on the concepts of an object-oriented model. These semantic elements are used to construct an object-oriented semantic network (OOSN). Because all facts and deductive rules are mapped to the OOSN statically, a query can be evaluated effectively in a distributed manner without any complex query optimization.

UR - http://www.scopus.com/inward/record.url?scp=1842789752&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=1842789752&partnerID=8YFLogxK

M3 - Article

VL - 26

SP - 85

EP - 95

JO - International Journal of Computers and Applications

JF - International Journal of Computers and Applications

SN - 1206-212X

IS - 2

ER -