GridMatch

A basis for integrating production systems with relational databases

Jack S Eddy Tan, Manish Maheshwari, Jaideep Srivastava

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

GridMatch, an efficient algorithm for evaluating left hand side bindings in a secondary memory environment, is described. Matching is incremental and the algorithm is state saving. Since the working-memory database and matching state are too large to fit in the main memory, careful implementation becomes crucial. GridMatch uses partitioned storage to reduce matching time. The time and space complexity of the algorithm is analyzed in detail. The algorithm was implemented in a file system environment. Results show that substantial savings in matching cost are obtained with little space overhead. As expected, matching becomes very computationally intensive in a secondary memory environment, and efficient algorithms are a must for successful integration of production systems and databases. The well-known optimization of common subcondition evaluation is applicable to GridMatch, and it is also easily parallelizable.

Original languageEnglish
Title of host publicationProc 2 Int IEEE Conf Tools Artif Intell
Place of PublicationPiscataway, NJ, United States
PublisherPubl by IEEE
Pages400-407
Number of pages8
ISBN (Print)0818620846
Publication statusPublished - 1990
Externally publishedYes
EventProceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence - Herndon, VA, USA
Duration: 6 Nov 19909 Nov 1990

Other

OtherProceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence
CityHerndon, VA, USA
Period6/11/909/11/90

Fingerprint

Data storage equipment
Costs

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Tan, J. S. E., Maheshwari, M., & Srivastava, J. (1990). GridMatch: A basis for integrating production systems with relational databases. In Proc 2 Int IEEE Conf Tools Artif Intell (pp. 400-407). Piscataway, NJ, United States: Publ by IEEE.

GridMatch : A basis for integrating production systems with relational databases. / Tan, Jack S Eddy; Maheshwari, Manish; Srivastava, Jaideep.

Proc 2 Int IEEE Conf Tools Artif Intell. Piscataway, NJ, United States : Publ by IEEE, 1990. p. 400-407.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Tan, JSE, Maheshwari, M & Srivastava, J 1990, GridMatch: A basis for integrating production systems with relational databases. in Proc 2 Int IEEE Conf Tools Artif Intell. Publ by IEEE, Piscataway, NJ, United States, pp. 400-407, Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence, Herndon, VA, USA, 6/11/90.
Tan JSE, Maheshwari M, Srivastava J. GridMatch: A basis for integrating production systems with relational databases. In Proc 2 Int IEEE Conf Tools Artif Intell. Piscataway, NJ, United States: Publ by IEEE. 1990. p. 400-407
Tan, Jack S Eddy ; Maheshwari, Manish ; Srivastava, Jaideep. / GridMatch : A basis for integrating production systems with relational databases. Proc 2 Int IEEE Conf Tools Artif Intell. Piscataway, NJ, United States : Publ by IEEE, 1990. pp. 400-407
@inproceedings{90ea306677774f42a25bc4b4c4d4ecbd,
title = "GridMatch: A basis for integrating production systems with relational databases",
abstract = "GridMatch, an efficient algorithm for evaluating left hand side bindings in a secondary memory environment, is described. Matching is incremental and the algorithm is state saving. Since the working-memory database and matching state are too large to fit in the main memory, careful implementation becomes crucial. GridMatch uses partitioned storage to reduce matching time. The time and space complexity of the algorithm is analyzed in detail. The algorithm was implemented in a file system environment. Results show that substantial savings in matching cost are obtained with little space overhead. As expected, matching becomes very computationally intensive in a secondary memory environment, and efficient algorithms are a must for successful integration of production systems and databases. The well-known optimization of common subcondition evaluation is applicable to GridMatch, and it is also easily parallelizable.",
author = "Tan, {Jack S Eddy} and Manish Maheshwari and Jaideep Srivastava",
year = "1990",
language = "English",
isbn = "0818620846",
pages = "400--407",
booktitle = "Proc 2 Int IEEE Conf Tools Artif Intell",
publisher = "Publ by IEEE",

}

TY - GEN

T1 - GridMatch

T2 - A basis for integrating production systems with relational databases

AU - Tan, Jack S Eddy

AU - Maheshwari, Manish

AU - Srivastava, Jaideep

PY - 1990

Y1 - 1990

N2 - GridMatch, an efficient algorithm for evaluating left hand side bindings in a secondary memory environment, is described. Matching is incremental and the algorithm is state saving. Since the working-memory database and matching state are too large to fit in the main memory, careful implementation becomes crucial. GridMatch uses partitioned storage to reduce matching time. The time and space complexity of the algorithm is analyzed in detail. The algorithm was implemented in a file system environment. Results show that substantial savings in matching cost are obtained with little space overhead. As expected, matching becomes very computationally intensive in a secondary memory environment, and efficient algorithms are a must for successful integration of production systems and databases. The well-known optimization of common subcondition evaluation is applicable to GridMatch, and it is also easily parallelizable.

AB - GridMatch, an efficient algorithm for evaluating left hand side bindings in a secondary memory environment, is described. Matching is incremental and the algorithm is state saving. Since the working-memory database and matching state are too large to fit in the main memory, careful implementation becomes crucial. GridMatch uses partitioned storage to reduce matching time. The time and space complexity of the algorithm is analyzed in detail. The algorithm was implemented in a file system environment. Results show that substantial savings in matching cost are obtained with little space overhead. As expected, matching becomes very computationally intensive in a secondary memory environment, and efficient algorithms are a must for successful integration of production systems and databases. The well-known optimization of common subcondition evaluation is applicable to GridMatch, and it is also easily parallelizable.

UR - http://www.scopus.com/inward/record.url?scp=0025538434&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0025538434&partnerID=8YFLogxK

M3 - Conference contribution

SN - 0818620846

SP - 400

EP - 407

BT - Proc 2 Int IEEE Conf Tools Artif Intell

PB - Publ by IEEE

CY - Piscataway, NJ, United States

ER -