Performance Evaluation of Parallel GroupBy-Before-Join Query Processing in High Performance Database Systems

  • David Taniar
  • J. Wenny Rahayu
  • Hero Ekonomosa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2110)


Strategic decision making process uses a lot of GroupBy clauses and join operations queries. As the source of information in this type of application to these queries is commonly very huge, then parallelization of GroupBy-Join queries is unavoidable in order to speed up query processing time. In this paper, we investigate three parallelization techniques for GroupBy-Join queries, particularly the queries where the group-by clause can be performed before the join operation. We subsequently call this query “GroupBy-Before-Join” queries. Performance evaluation of the three parallel processing methods is also carried out and presented here.


Query Processing Replication Scheme Partitioning Scheme Aggregate Function Selectivity Ratio 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Bedell J.A. “Outstanding Challenges in OLAP”, Proceedings of 14th International Conference on Data Engineering, 1998.Google Scholar
  2. 2.
    Bultzingsloewen G., “Translating and optimizing SQL queries having aggregate”, Proceedings of the 13th International Conference on Very Large Data Bases, 1987.Google Scholar
  3. 3.
    Datta A. and Moon B., “A case for parallelism in data warehousing and OLAP”, Proc. of 9th International Workshop on Database and Expert Systems Applications, 1998.Google Scholar
  4. 4.
    Dayal U., “Of nests and trees: a unified approach to processing queries that contain nested subqueries, aggregates, and quantifiers”, Proceedings of the 13th International Conference on Very Large Data Bases, Brighton, UK, 1987.Google Scholar
  5. 5.
    DeWitt, D.J. and Gray, J., “Parallel Database Systems: The Future of High Performance Database Systems”, Communication of the ACM, vol. 35,no. 6, pp. 85–98, 1992.CrossRefGoogle Scholar
  6. 6.
    Kim, W., “On optimizing an SQL-like nested query”, ACM TODS, 7(3), Sept. 1982.Google Scholar
  7. 7.
    Ramakrishnan, R., Database Management Systems, McGraw Hill, 1998.Google Scholar
  8. 8.
    Taniar, D., and Rahayu, J.W., “Parallel Processing of Aggregate Queries in a Cluster Architecture”, Proc. of the 7th Australasian Conf. on Parallel and Real-Time Systems PART’2000, Springer-Verlag, 2000.Google Scholar
  9. 9.
    Taniar, D., Jiang, Y., Liu, K.H., and Leung, C.H.C., “Aggregate-Join Query Processing in Parallel Database Systems”, Proc. of The 4 th Intl Conf on High Performance Computing in Asia-Pacific HPC-Asia2000, vol. 2, IEEE CS Press, pp. 824–829, 2000.CrossRefGoogle Scholar
  10. 10.
    Yan W.P. and P. Larson, “Performing group-by before join”, Proceedings of the International Conference on Data Engineering, 1994.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • David Taniar
    • 1
  • J. Wenny Rahayu
    • 2
  • Hero Ekonomosa
    • 3
  1. 1.School of Business SystemsMonash UniversityVicAustralia
  2. 2.Department of Computer Science and EngineeringLa Trobe UniversityAustralia
  3. 3.Department of Computer Science & ITUniversity Tenaga NasionalMalaysia

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