The KIPS Transactions:PartD (정보처리학회논문지D)

Korea Information Processing Society (한국정보처리학회)
권호 표지
DOI QR코드

DOI QR Code

A Condition Processing System of Active Rules Using Analyzing Condition Predicates

조건 술어 분석을 이용한 능동규칙의 조건부 처리 시스템

  • Published : 2002.02.01
Download PDF
⟨ Previous Next ⟩

Abstract

The active database system introduces the active rules detecting specified state. As the condition evaluation of the active rules is performed every time an event occurs, the performance of the system has a great influence, depending on the conditions processing method. In this paper, we propose the conditions processing system with the preprocessor which determines the delta tree structure, constructs the classification tree, and generates the aggregate function table. Due to the characteristics of the active database through which the active rules can be comprehended beforehand, the preprocessor can be introduced. In this paper, the delta tree which can effectively process the join, selection operations, and the aggregate function is suggested, and it can enhance the condition evaluation performance. And we propose the classification tree which effectively processes the join operation and the aggregate function table processing the aggregate function which demands high cost. In this paper, the conditions processing system can be expected to enhance the performance of conditions processing in the active rules as the number of conditions comparison decreases because of the structure which is made in the preprocessor.

능동 데이터베이스 시스템은 특정한 상태를 탐지하는 능동규칙을 도입한다. 조건부 평가는 사건이 발생할 때마다 수행되기 때문에 조건부를 처리하는 방법에 따라 시스템의 성능에 중요한 영향을 미친다. 본 논문에서는 차이트리 구조, 분류트리, 그리고 집계함수 테이블을 생성하는 전처리 기능을 갖는 조건부 처리 시스템을 제안한다. 전처리는 능동규칙을 미리 파악할 수 있는 능동 데이터베이스의 특징 때문에 도입될 수 있다. 본 논문에서는 선택연산, 조인연산, 그리고 집계함수를 효율적으로 처리할 수 있는 차이트리를 제안하고 조건부의 처리 성능을 높인다. 그리고 조인연산을 효과적으로 처리하는 분류트리와 높은 처리비용을 요구하는 집계함수를 처리하는 집계함수 테이블을 제안한다. 본 논문의 조건부 처리 시스템은 전처리 기능에서 만들어진 조건부 처리 구조 때문에 조건 비교의 횟수를 감소시켜 능동규칙에서 조건부 처리의 성능 향상을 기대할 수 있다.

Keywords

References

  1. Dayal. U., 'The HiPAC Project : Combining Active Databases and Timing Constraints,' ACM SIGMOD record. 17(1), pp.51-70, 1988 https://doi.org/10.1145/44203.44208
  2. Chaudhuri. S. and Shim. K., 'Optimization of Queries with User-Defined Predicates,' ACM Transactions on Database System, 24(2), June, 1999 https://doi.org/10.1145/320248.320249
  3. Fabret. F., Regnier. M. and Simon. E., 'An Adaptive Algorithm for Incremental Evaluation of Production Rules in Databases,' In Proceedings of the 19th International Conference on Very Large Data Bases, pp.455-467, Dublin, Ireland, August, 1993
  4. Risch. T., 'Monitoring Database Objects,' In Proceedings of the 15th International Conference on VLDB, pp.445-453, 1989
  5. Widom. J. and Ceri. S., Active Database Systems : Triggers and Rules for Advanced Database Processing. Morgan Kaufmann Publishers, Inc., pp.73-80, 1995
  6. Rosenthal. A., Chakravarthy. S., Blaustein. B., and Blakeley. J., 'Situation monitoring for active databases,' In Proceedings of the 15th International Conference on Very Large Data Bases, pp.455-464, Amsterdam, The Netherlands, August, 1989
  7. Simon. E., Kiernan. J. and de Maindreville. C., 'Implementing High Level Active Rules on Top of a Relational DBMS,' In Proceedings of the 18th International Conference on Very Large Data Bases, pp.315-326, Vancouver, British Columbia, August, 1992
  8. Baralis. E. and Widom. J., 'Using Delta Relations to Optimize Condition Evaluation in Active Databases,' RIDS'95 (Rules in Database Systems), Springer Lecture Notes in Computer Science, pp.292-308, Athens, Greece, September, 1995 https://doi.org/10.1007/3-540-60365-4_134
  9. Hanson. E. N., 'Rule Condition Testing and Action Execution in Ariel,' In Proceedings of the ACM SIGMOD International Conference on Management of Data, pp.49-58. San Diego, California, June, 1992 https://doi.org/10.1145/130283.130295
  10. Hanson. E. N., Bodagala. S., Hasan. M., Kulkarni. G., and Rangarajan. J., 'Optimized Rule Condition Testing in Ariel using Gator Network,' Technical Report TR-95-027, University of Florida CIS Dept., 1995
  11. Schor. M. I., Daly. T. P., Lee. H. S. and Tibbitts. B. R., 'Advances in RETE Pattern Matching,' In Proceedings of the 5th National Conference on Artificial Intelligence, pp. 226-232, Philadelphia, Pennsylvania, August, 1986
  12. Miranker. D. P., 'TREAT: A Better Match Algorithm for AI Production Systems,' In Proceedings of the AAAI National Conference on Artificial Intelligence, pp.42-47, August, 1987