Journal of KIISE:Computing Practices and Letters (한국정보과학회논문지:컴퓨팅의 실제 및 레터)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Implementation and Evaluation of Time Interval Partitioning Algorithm in Temporal Databases

시간 데이타베이스에서 시간 간격 분할 알고리즘의 구현 및 평가

  • 이광규 (신흥대학 컴퓨터정보계열) ;
  • 신예호 (충북대학교 전자계산학과) ;
  • 류근호 (충북대학교 컴퓨터과학과) ;
  • 김홍기 (충북대학교 컴퓨터과학과)
  • Published : 2002.02.01
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Abstract

Join operation exert a great effect on the performance of system in temporal database as in the relational database. Especially, as for the temporal join, the optimization of interval partition decides the performance of query processing. In this paper, to improve the efficiency of parallel join query in temporal database. I proposed Minimum Interval Partition(MIP) scheme that time interval partitioning. The validity of this MIP algorithm that decides minimum breakpoint of the partition is proved by example scenario and I confirmed improved efficiency as compared with existing partition algorithm.

조인 연산은 관계형 데이타베이스에서와 같이 시간 데이타베이스에서도 시스템 성능에 큰 영향을 미친다. 특히, 시간 조인은 조인 연산 단계 이전에 간격 분할의 최적화가 질의 처리 성능을 결정한다. 이 논문에서는 시간 데이타베이스의 병렬 조인 질의 처리 성능을 개선하기 위해 시간 조인 연산을 위한 시간 간격을 분할하는 최소 분할 기법을 제안하였고, 제안된 간격 분할의 최소 분할점을 결정하는 최소 간격 분할 알고리즘의 유효성은 예제 시나리오를 통해 검증하였으며, 기존 분할 알고리즘에 비해 성능 개선 효과가 있음을 확인하였다.

Keywords

References

  1. Snodgrass, R The temporal query language TQul. ACM Transactions on Database System, 12(2):247-298.1987 https://doi.org/10.1145/22952.22956
  2. M. Soo, R. Snodgrass, and C. Jensen.Efficient Evaluation of the Valid-Time Natural Join. In Proc. of the 10th Int. Conf. on Data Engineering. Houston https://doi.org/10.1109/ICDE.1994.283042
  3. C. Breiteneder, S. Gibbs, and D. Tsichritzis. 'Modelling of Audio/Video Data', In Proceedings of the 11th International Conference on the Entity-Relationship Approach. Karlsruhe, Germany, pp. 322-339, Oct. 1992
  4. E. Ardizzone, M. L. Cascie, 'Automatic Video Database Indexing and Retrieval'. Multimedia Tools and Applications, Vol.4, No.1. pp. 29-56, Jan. 1997 https://doi.org/10.1023/A:1009630331620
  5. N.Lorentzos and Y.Mitsopoulos. SQL Extension for Interval Data. Technical Rep. 105, Informatics Lab., Agricultural University of Athens, 1994
  6. R. Snodgrass, editor. The TSQL2 Temporal Query Language. Kluwer, Sept. 1995
  7. Clifford. J. Dyresson, C, Snodgrass, R., Isakowitz. T. and Jensen, Now in TSQL2. A TSQL2 Commentary. C.(1994)
  8. T. Leung and R.Muntz. 'Temporal Query Processing and Optimization in Multiprocessor Database Machines'. In Proc.18th Int. Conf. onVLDB, vancounver, Canada, pp.383-394, Aug. 1992
  9. Dewitt. D. and Gerber, Multiprocessor hash-based join algorithms. In Proc. of the 11th Int Conf. on Very Large Data Base(VLDB), Stockholm, Sweden. pages 151-164. R.1985
  10. Lo, M.-L. and Ravishankar, C. Spatial Hash-Joins. In Proceedings ACM SIGMOD Conference em Management of Data, Montreal, Canada, pages 247-258. 1996 https://doi.org/10.1145/235968.233337
  11. X.Jeffrey, Yu and Kian-Lee Tan, Scheduling Issues in Partitioned Temporal join, Joint Computer Science Technical Report Series, May 1995
  12. H. Gunadhi and A. Segev. Ouery Processing Algorithms for Temporal Intersection Joins. In Proc. of the IEEE int Conf. on Data Engineering, pages 336-344, 1991 https://doi.org/10.1109/ICDE.1991.131481
  13. H. Lu, B.-C. Ooi, and K.-L. Tan. On Spatially Partitioned Temporal Join. In Proc. of the 20th Internet Conf. on Very Large Data Bases(VLDB), Santiago de Chile, pages 63-113, Mar, Sept. 1994
  14. H.Zhou. Two-stage m-way graph partitioning. Parallel Computing, 19(12) pp. 1359-1373, Dec. 1993 https://doi.org/10.1016/0167-8191(93)90081-U
  15. P. Misnra and M. Eich. Join Processing in Relational Databases. ACM Computing Surveys, pages 63-113. Mar.1992 https://doi.org/10.1145/128762.128764
  16. R. Elmasri, G.Wuu, and V. Kouramajian. The Time Index and the Monotonic B+-tree. In Tanser and et al. [10]. chapter 18. pages 433-456
  17. H. Gunadhi and A. Segev. Efficient Indexing Methods for Temporal Relations. IEEE Transactions on Knowledge and Data Engineering, 5(3):496-509, June. 1993 https://doi.org/10.1109/69.224200
  18. Rana, S. and Fotouhi, F.(1993). Efficient Processing of Time-Joins in Temporal Data Bases. In Proc. of the 3rd Internet. Symposium on Database System for Advanced Applications, pages 427-432
  19. 김동호, 이인홍, 류근호, '주기억장치에서 시간지원 데이타베이스의 집계함수 설계 및 구현' 한국정보과학회 논문지, 제21권, 제8호, pp.1405-1415, 1994
  20. J. David, F.Jeffrey, A. Donovan, S.Seshadri. Practical Skew Handling in Parallel Joins. In Proc. 18th VLDB, pp.27-40, Aug.1992
  21. R. Snodgrass, K. Nick, 'Aggregate in TSQL2' The TSQL2 Language Design Committee, Mar. 1994