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Compressed Data Cube for Approximate OLAP Query Processing 被引量：3

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摘要 Approximate query processing has emerged as an approach to dealing with thehuge data volume and complex queries in the environment of data warehouse. In this paper,we present a novel method that provides approximate answers to OLAP queries. Our methodis based on building a compressed (approximate) data cube by a clustering technique and usingthis compressed data cube to provide answers to queries directly, so it improves the performanceof the queries. We also provide the algorithm of the OLAP queries and the confidence intervalsof query results. An extensive experimental study with the OLAP council benchmark showsthe effectiveness and scalability of our cluster-based approach compared to sampling.
作者 冯玉 王珊
机构地区 SchoolofInformation
出处 《Journal of Computer Science & Technology》 SCIE EI CSCD 2002年第5期625-635,共11页 计算机科学技术学报（英文版）
基金 国家自然科学基金，国家重点基础研究发展计划(973计划)
关键词 OLAP 数据处理 决策支持系统
分类号 TP399 [自动化与计算机技术—计算机应用技术] C934 [经济管理—管理学]
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参考文献11

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  • 4The OLAP Council. The OLAP benchmark, http://www.olapcouncil.org
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同被引文献19

  • 1Markl Volker,Ramsak Frank,Bayer Rudolf. Improving OLAP performance by multidimensional hierarchical clustering[C]. Proceedings of the International Database Engineering and Applications Symposium.1999:165-177.
  • 2Codd E F. Providing OLAP(on-line analytical processing) to user-analysts:an IT mandate[R]. Technical Report. E F Codd and Associates, 1993.
  • 3Zhao Y H, Deshpande P M, Naughton J F. An array-based algorithm for simultaneous multidimensional aggregates [J].ACM SIGMOD Record, 1997,26 (2):159-170.
  • 4Mumick I S, Quass D, Mumick B S. Maintenance of data cubes and summary tables in a warehouse [J]. ACM SIGMOD Record,1997,26(2): 100-111.
  • 5Ho C, Agrawal R, Megiddo N, Srikant R. Range queries in OLAP data cubes[J]. ACM SIGMOD Record, 1997,26 (2):73-88.
  • 6Geffner S, Agrawal D, Abbadi A E1, Smith T. Relative prefix sums: An efficient approach for querying dynamic OLAP data cubes[A]. In:Kitsuregawa M, ed. Proceedings of the 15th International Conference on Data Engineering[C]. New Orleans:IEEE Computer Society, 1999,328-335.
  • 7Geffner S, Agrawal D, Abbadi A E1. The dynamic data cubes [A]. In: Zaniolo C, ed. Proceedings of 7th International Conference on Extending Database Technology [C]. Heidelberg:Springer, 2000, 237-253.
  • 8Liang W, Wang H, Orlowska M E. Range queries in dynamic OLAP data cubes[J]. Data & Knowledge Engineering , 2000,34(1):21-38.
  • 9Riedewald M, Agrawal D, Abbadi A El. Fiexible data cubes for online aggregation[A]. In: Bussche J V, ed. Proceedings of the 8th International Conference on Database Theory [C]. Heidelberg:Springer, 2001, 159-173.
  • 10Wang W, Lu H J, Feng J L et al. Condensed cube: an effective approach to reducing data cube size[A]. In: Jose S, Agrawal C R, Dittrich K, eds. Proc. of the 18th International Conference on Data Engineering[C]. Los Alamitos :IEEE Computer Society Press, 2002, 155-165.

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Journal of Computer Science & Technology
2002年 第5期

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