Abstract
In OLAP models, or data cubes, aggregates have to be recalculated when the underlying base data changes. This may cause performance problems in real-time OLAP systems, which continuously accommodate huge amounts of measurement data. To optimize the aggregate computations, a new consistency criterion called the tolerance invariant is proposed. Lazy aggregates are aggregates that are recalculated only when the tolerance invariant is violated, i.e., the error of the previously calculated aggregate exceeds the given tolerance. An industrial case study is presented. The prototype implementation is described, together with the performance results.
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References
S. Agarwal, R. Agrawal, P. M. Deshpandre, A. Gupta, J. F. Naughton, R. Ramakrishnan, S. Sarawagi. On the Computation of Multidimensional Aggregates. Proc. of the 22nd VLDB Conference, Bombay, India, 1996, pp. 506–521.
PPS 200: The papermaker’s Drive. ABB Industry Oy, 1998, Helsinki, Finland.
F. Codd, et al. Providing OLAP to User-Analysts: An IT Mandate. TR, E.F. Codd & Associates, 1993 (http://www.arborsoft.com/essbase/wht_ppr/ coddTOC.html)
J. Gray, A. Bosworth, A. Layman, H. Pirahesh. Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals. Proc. of 12th Internat. Conf. on Data Engineering, New Orleans, Louisiana, U.S.A., 1996, pp. 152–159.
V. Harinarayan, A. Rajaman, J. D. Ullman. Implementing Data Cubes Efficiently. SIGMOD Record, Vol. 25, No. 2, June 1996, pp. 205–216.
R. Moore. Interval Analysis, Prentice Hall, 1966.
I. S. Mumick, D. Quass, B. S. Mumick. Maintenance of Data Cubes and Summary Tables in a Warehouse. Proc. of the 1997 SIGMOD. Conf., Tucson. AZ, U.S.A., pp. 100–111.
K. Ramamritham. Real-Time Databases. Distributed and Parallel Databases, 1(2), April 1993, pp. 199–226.
J. Widom, S. Ceri (eds.). Active Database Systems: Triggers and Rules for Advanced Database Processing. Morgan Kaufmann, 1996.
A. Wolski, J. Arminen, J. Kiviniemi, A. Pesonen. Design of Rubic, Version 1.0. Research Report TTE1-1-99, VTT Information Technology, January 1999. (http://www.vtt.fi/-tte/projects/industrialdb/publs/rubic-design.pdf)
A. Wolski, J. Karvonen, A. Puolakka. The RAPID Case Study: Requirements for and the Design of a Fast-response Database System. Proceedings of the First Workshop on real-Time Databases (RTDB’96), Newport Beach, CA, USA, 1996, pp. 32–39 (http://www.vtt.fi/tte/projects/industrialdb/publs/case.pdf)
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© 1999 Springer-Verlag Berlin Heidelberg
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Kiviniemi, J., Wolski, A., Pesonen, A., Arminen, J. (1999). Lazy Aggregates for Real-Time OLAP. In: Mohania, M., Tjoa, A.M. (eds) DataWarehousing and Knowledge Discovery. DaWaK 1999. Lecture Notes in Computer Science, vol 1676. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48298-9_18
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DOI: https://doi.org/10.1007/3-540-48298-9_18
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