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Simulation of hierarchical multiprocessor database systems

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The paper is dedicated to issues concerning simulation and analysis of hierarchical multiprocessor systems oriented to database applications. Requirements for a parallel database system model are given. A survey and comparative analysis of known parallel database system models are presented. A new multiprocessor database system model is introduced. This model allows us to simulate and evaluate arbitrary hierarchical multiprocessor configurations in the context of the OLTP class database applications. Examples of using the database multiprocessor model for simulation study of multiprocessor database systems are presented.

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References

  1. Agrawal, R., Ailamaki, A., Bernstein, P.A., et al., The Claremont Report on Database Research, Commun. ACM, 2009, vol. 52, no. 6, pp. 56–65.

    Article  Google Scholar 

  2. Agrawal, R., Carey, M.J., and Livny, M., Concurrency Control Performance Modeling: Alternatives and Implications, ACM Trans. Database Systems, 1987, vol. 12, no. 4, pp. 609–654.

    Article  Google Scholar 

  3. Alfawair, M., Aldabbas, et al., Grid Evolution, Proc. of the IEEE Int. Conf. on Computer Engineering & Systems (Cairo, Egypt, 2007), IEEE Comput. Soc., 2007, pp. 158–163.

  4. Gray, J. et al., Scientific Data Management in the Coming Decade, SIGMOD Record, 2005, vol. 34, no. 4, pp. 34–41.

    Article  Google Scholar 

  5. Becla, J. and Wang, D.L. Lessons Learned from Managing a Petabyte, CIDR 2005, Second Biennial Conf. on Innovative Data Systems Research, Asilomar, CA, USA, 2005. Online Proceedings, 2005, pp. 70–83. http://www.cidrdb.org/cidr2005. Accessed November 8, 2009.

  6. Bell, G., Gray, J., and Szalay, A.S., Petascale Computational Systems, IEEE Comput., 2006, vol. 39, no. 1, pp. 110–112.

    Article  Google Scholar 

  7. Bhide, A., An Analysis of Three Transaction Processing Architectures, Proc. of the Fourteenth Int. Conf. on Very Large Data Bases (VLDB’88) (Los Angeles, 1988), Morgan Kaufmann, 1988, pp. 339–350.

  8. Bhide, A. and Stonebraker, M., A Performance Comparison of Two Architectures for Fast Transaction Processing, Proc. of the Fourth Int. Conf. on Data Engineering (Los Angeles, 1988), IEEE Comput. Soc., 1988, pp. 536–545.

  9. Bhide, A. and Stonebraker, M., Performance Issues in High Performance Transaction Processing Architectures, Proc. of the 2nd Int. Workshop on High Performance Transaction Systems (Asilomar, 1987), Springer, 1989, vol. 359, pp. 277–299.

    Article  Google Scholar 

  10. Carey, M.J. and Livny, M., Distributed Concurrency Control Performance: A Study of Algorithms, Distribution, and Replication, Proc. of the VLDB Conf. (Los Angeles, 1988), Morgan Kaufmann, 1988, pp. 13–25.

  11. Carey, M.J. and Livny, M., Parallelism and Concurrency Control Performance in Distributed Database Machines, Proc. of the 1989 ACM SIGMOD Int. Conf. on the Management of Data, Portland, 1989; ACM, 1989, vol. 18, no. 2, pp. 122–133.

    Google Scholar 

  12. Carey, M. and Stonebraker, M., The Performance of Concurrency Control Algorithms for Database Management Systems, Proc. of the 10th VLDB Conf. (Singapore, 1984), Morgan Kaufmann, 1984, pp. 107–118.

  13. DeWitt, D.J., Ghandeharizadeh, S., Schneider, D., Bricker, A., Hsiao, H.I., and Rasmussen, R., The Gamma Database Machine Project, IEEE Trans. Knowledge Data Eng., 1990, vol. 2, no. 1, pp. 44–62.

    Article  Google Scholar 

  14. Ghazal, A. et al., Exploiting Interactions among Query Rewrite Rules in the Teradata DBMS, Proc. of the 19th Int. Conf. “Database and Expert Systems Applications” (DEXA 2008) (Turin, 2008), Springer, 2008, vol. 5181, pp. 596–609.

    Article  Google Scholar 

  15. Hanlon, M., Klein, J., Linden, R., and Zeller, H., Publish/Subscribe in NonStop SQL: Transactional Streams in a Relational Context, Proc. of the 20th Int. Conf. on Data Engineering (Boston, 2004), IEEE Comput. Soc., 2004, pp. 821–825.

  16. Hsiao, H.I. and DeWitt, D.J., A Performance Study of Three High Availability Data Replication Strategies, Distributed Parallel Databases, 1993, vol. 1, no. 1, pp. 53–80.

    Article  Google Scholar 

  17. Hughes, C.J., Changkyu, K., and Yen-Kuang, C., Performance and Energy Implications of Many-Core Caches for Throughput Computing, IEEE Micro, 2010, vol. 3, no. 6, pp. 25–35.

    Article  Google Scholar 

  18. Lakshmi, M.S. and Yu, P.S., Effect of Skew on Join Performance in Parallel Architectures, Proc. of the First Int. Symp. on Databases in Parallel and Distributed Systems (Austin, Texas, 1988), IEEE Comput. Soc., 1988, pp. 107–120.

  19. Livny, M., DeNet User’s Guide, Version 1.0, Comp. Sci. Dept., Univ. of Wisconsin, Madison, 1988.

    Google Scholar 

  20. Maertens, H., A Classification of Skew Effects in Parallel Database Systems, Proc. of the 7th Int. Euro-Par Conf. (Manchester, UK, 2001), Springer, 2001, vol. 2150, pp. 291–300.

    Google Scholar 

  21. Raman, V., Han, W., and Narang, I., Parallel Querying with Non-Dedicated Computers, Proc. of the 31st Int. Conf. on Very Large Data Bases, Trondheim, Norway, 2005; ACM, 2005, pp. 61–72.

  22. Talwadker, A.S., Survey of Performance Issues in Parallel Database Systems, J. Computing Sci. Colleges, 2003, vol. 18, no. 6, pp. 5–9.

    Google Scholar 

  23. Rahm, E., Parallel Query Processing in Shared Disk Database Systems, ACM SIGMOD Record, 1993, vol. 22, no. 4, pp. 32–37.

    Article  Google Scholar 

  24. Xu, Y. and Dandamudi, S.P., Performance Evaluation of a Two-Level Hierarchical Parallel Database System, Proc. of the Int. Conf. Computers and Their Applications, Tempe, Arizona, 1997, pp. 242–247.

  25. Zhang, Y., Chen, G., Sun, G., and Miao, Q., Models of Parallel Computation: A Survey and Classification, Frontiers Comput. Sci. China, 2007, vol. 1, no. 2, pp. 156–165.

    Article  Google Scholar 

  26. Kostenetkii, P.S., Simulation of Parallel Database Systems for Computational Clusters, Trudy Vserossiiskoi nauchnoi konferentsii “Nauchnyi servis v seti Internet: masshtabiruemost’, parallel’nost’, effektivnost’” (Proc. of the All-Russian Scientific Conf. “Scientific Service in the Internet: Scalability, Concurrency, and Efficiency,” Novorossiisk, 2009), Moscow: Izd. MGU, 2009, pp. 300–304.

    Google Scholar 

  27. Kostenetkii, P.S., Lepikhov, A.V., and Sokolinskii, L.B., Technologies of Parallel Database Systems for Hierarchical Multiprocessor Environments, Automation Remote Control, 2007, vol. 68, no. 5, pp. 847–859.

    Article  Google Scholar 

  28. Sokolinsky, L.B., Survey of Architectures of Parallel Database Systems, Programming Comput. Software, 2004, vol. 30, no. 6, pp. 337–346.

    Article  MATH  Google Scholar 

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Correspondence to P. S. Kostenetskii.

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Original Russian Text © P.S. Kostenetskii, L.B. Sokolinsky, 2013, published in Programmirovanie, 2013, Vol. 39, No. 1.

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Kostenetskii, P.S., Sokolinsky, L.B. Simulation of hierarchical multiprocessor database systems. Program Comput Soft 39, 10–24 (2013). https://doi.org/10.1134/S0361768813010040

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