ABSTRACT
Database researchers have made significant progress on several research issues related to multidimensional data analysis, including the development of fast cubing algorithms, efficient schemes for creating and maintaining precomputed group-bys, and the design of efficient storage structures for multidimensional data. However, to date there has been little or no work on multidimensional query optimization. Recently, Microsoft has proposed “OLE DB for OLAP” as a standard multidimensional interface for databases. OLE DB for OLAP defines Multi-Dimensional Expressions (MDX), which have the interesting and challenging feature of allowing clients to ask several related dimensional queries in a single MDX expression. In this paper, we present three algorithms to optimize multiple related dimensional queries. Two of the algorithms focus on how to generate a global plan from several related local plans. The third algorithm focuses on generating a good global plan without first generating local plans. We also present three new query evaluation primitives that allow related query plans to share portions of their evaluation. Our initial performance results suggest that the exploitation of common subtask evaluation and global optimization can yield substantial performance improvements when relational database systems are used as data sources for multidimensional analysis.
- CS94.S. Chaudhuri and K. Shim. "Including groupby in query optimization". In VLDB Conference, page 354-366, 1994. Google ScholarDigital Library
- CR96.Damianos Chatziantoniou, Kenneth A. Ross. Querying Multiple Features of Groups in Relational Databases". Multidimensional Aggregates". In Proceedings of the 22nd International Conference on Very Large Databases, Mumbai (Bombay), pp295-306. Google ScholarDigital Library
- DKLPY94.D.J. DeWitt, N. Kabra, J. Luo, j.M. Patel, J. Yu. "Client-Server Paradise." Proceedings of the 20th VLDB Conference, Santiago, Chile, 1994. Google ScholarDigital Library
- HRU96.V. Harinarayan, A. Rajaraman, and J.D. Ullman. " Implementing Data Cubes Efficiently", Proc. ACM SIGMOD '96. Google ScholarDigital Library
- GHQ95.A. Gupta, V Harinarayan, D. Quass. "Aggregate-Query Processing in Data Warehousing Environments", Proceedings of the 21st VLDB Conference Zurich, Swizerland, 1995. Google ScholarDigital Library
- MS.Microsoft Corporated. "OLE DB for OLAP Design Specification- Beta 2". http://www, mlcrosoft, corn / data/ oledb / olap / pro dinfo, ht mlGoogle Scholar
- OQ97.Patrick O'Neil and Dallan Quass. "Improved Query Performance with Variant indexes." Proc. of the 1997 SIGMOD Conference, May, 1997. Google ScholarDigital Library
- PS88.J. Park and A Segev "Using common subexpressions to optimize multiple queries". In Proc. 4th Intern. Conf. on Data Engineering, pages 311-319, February, 1988. Google ScholarDigital Library
- S88.Timos K. Sellis. "Multiple-Query Optimization". ACM Transactions on Database Systems, VoI 13, No.l, March 1988, Pages 23-52. Google ScholarDigital Library
- SS94.K. Shim and T.Sellis, "Improvements on a Heuristic Algorithm for Multiple- Query Optimization", Data and Knowledge Engineering, Vol. 12, No.2, March 1994. Google ScholarDigital Library
- SM94.Sunita Sarawagi, Michael Stonebraker, "Efficient Organization of Large Multidimensional Arrays". in Proceedings o/the Eleventh International Conference on Data Engineering, Houston, TX, February 1994. Google ScholarDigital Library
- Su96.Prakash Sundaresan. "Data Warehousing Features in Infbrmix OnLine XFS." Presentation at the Fourth International PDIS Conference, December 18-20, 1996, Miami Beach, Florida. Google ScholarDigital Library
- YL95.W.P. Yan and P. Larson. "Eager aggregation and lazy aggregation". In VLDB Conference, page 345-357, 1995. Google ScholarDigital Library
- ZTN96.Y.H. Zhao, K. Tufte, and J.F. Naughton. "On the Performance of an Array-Based ADT for OLAP Workloads". Technical Report CS-TR-96-1313, University of Wisconsin-Madison, CS Department, May 1996.Google Scholar
Index Terms
- Simultaneous optimization and evaluation of multiple dimensional queries
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