International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Development of Query Transformation Method by Cost Optimization

  • Received : 2015.12.08
  • Accepted : 2016.03.22
  • Published : 2016.03.25
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Abstract

The transformation time among queries in the database management system (DBMS) is responsible for the execution time of users' queries, because a conventional DBMS does not consider the transformation cost when queries are transformed for execution. To reduce the transformation time (cost reduction) during execution, we propose an optimal query transformation method by exploring queries from a cost-based point of view. This cost-based point of view means considering the cost whenever queries are transformed for execution. Toward that end, we explore and compare set off heuristic, linear, and exhaustive cost-based transformations. Further, we describe practical methods of cost-based transformation integration and some query transformation problems. Our results show that, some cost-based transformations significantly improve query execution time. For instance, linear and heuristic transformed queries work 43% and 74% better than exhaustive queries.

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References

  1. H. Garcia-Molina, J. D. Ullman, and J. Widom, Database System Implementation. Upper Saddle River, NJ: Prentice Hall, 2000.
  2. S. Chaudhuri and K. Shim, "Optimizing queries with aggregate views," in Proceedings of 5th International Conference on Extending Database Technology, Avignon, France, 1996, pp. 167-182. http://dx.doi.org/10.1007/BFb0014151
  3. C. Galindo-Legaria and A. Rosenthal, "Outerjoin simplification and reordering for query optimization," ACM Transactions on Database Systems, vol. 22, no. 1, pp. 43-74, 1997. http://dx.doi.org/10.1145/244810.244812
  4. C. Fraser, L. Giakoumakis, V. Hamine, and K. F. Moore-Smith, "Testing cardinality estimation models in SQL server," in Proceedings of 5th International Workshop on Testing Database Systems (DBTest'12), Scottsdale, AZ, 2012. http://dx.doi.org/10.1145/2304510.2304526
  5. T. Neumann, "Query simplification: graceful degradation for join-order optimization," in Proceedings of ACM SIGMOD International Conference on Management of data (SIGMOD'09), Providence, RI, 2009, pp. 403-414. http://dx.doi.org/10.1145/1559845.1559889
  6. T. Neumann and C. Galindo-Legaria, "Taking the edge off cardinality estimation errors using incremental execution," in Proceedings of Datenbanksysteme fur Business, Technologie und Web (BTW2013), Magdeburg, Germany, 2013, pp. 73-92.
  7. W. Wu, Y. Chi, S. Zhu, J. Tatemura, H. Hacigumus, and J. F. Naughton, "Predicting query execution time: are optimizer cost models really unusable?," in Proceedings of IEEE 29th International Conference on Data Engineering (ICDE'13), Brisbane, Australia, 2013, pp. 1081-1092. http://dx.doi.org/10.1109/ICDE.2013.6544899
  8. G. Lohman, "Is query optimization a "solved" problem?," Available http://wp.sigmod.org/?p=1075
  9. S. Chaudhuri, "Query optimizers: time to rethink the contract?," in Proceedings of ACM SIGMOD International Conference on Management of data (SIGMOD'09), Providence, RI, 2009, pp. 961-968. http://dx.doi.org/10.1145/1559845.1559955
  10. S. Bellamkonda, H. G. Li, U. Jagtap, Y. Zhu, V. Liang, and T. Cruanes, "Adaptive and big data scale parallel execution in oracle," Proceedings of the VLDB Endowment, vol. 6, no. 11, pp. 1102-1113, 2013. http://dx.doi.org/10.14778/2536222.2536235
  11. F. Liu and S. Blanas, "Forecasting the cost of processing multi-join queries via hashing for main-memory databases," in Proceedings of the 6th ACM Symposium on Cloud Computing (SoCC'15), Kohala Coast, HI, 2015, pp. 153-166. http://dx.doi.org/10.1145/2806777.2806944
  12. F. M. Waas, L. Giakoumakis, and S. Zhang, "Plan space analysis: an early warning system to detect plan regressions in cost-based optimizers," in Proceedings of the 4th International Workshop on Testing Database Systems (DBTest'11), Athens, Greece, 2011. http://dx.doi.org/10.1145/1988842.1988844