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Issue No.04 - April (2008 vol.41)
pp: 69-77
Cyrus Shahabi , University of Southern California
Mehrdad Jahangiri , University of Southern California
Farnoush Banaei-Kashani , University of Southern California
ProDA employs wavelets to support exact, approximate, and progressive OLAP queries on large multidimensional datasets, while keeping update costs relatively low. ProDA not only supports online execution of ad hoc analytical queries on massive datasets, but also extends the set of supported analytical queries to include the entire family of polynomial aggregate queries as well as the new class of plot queries.
data-intensive computing, database management, scientific applications, online query processing, wavelet transformation, range aggregate queries, information technology and systems, OLAP tools
Cyrus Shahabi, Mehrdad Jahangiri, Farnoush Banaei-Kashani, "ProDA: An End-to-End Wavelet-Based OLAP System for Massive Datasets", Computer, vol.41, no. 4, pp. 69-77, April 2008, doi:10.1109/MC.2008.130
1. M. Stonebraker et al., "The Lowell Database Research Self-Assessment," Comm. ACM, vol. 48, no. 5, 2005, pp. 111–118.
2. M. Jahangiri and C. Shahabi, Wolap: Wavelet-Based Range Aggregate Query Processing, tech. report, Dept. Computer Science, Univ. of Southern California, 2007.
3. R. Schmidt and C. Shahabi, "Propolyne: A Fast Wavelet-Based Technique for Progressive Evaluation of Polynomial Range-Sum Queries," Proc. Extending Database Technology Conf. (EDBT 02), Springer, 2002, pp. 664–681.
4. C. Shahabi and R. Schmidt, Wavelet Disk Placement for Efficient Querying of Large Multidimensional Data Sets, tech. report, Dept. of Computer Science, Univ. of Southern California, 2004.
5. M. Jahangiri, D. Sacharidis, and C. Shahabi, "SHIFT-SPLIT: I/O Efficient Maintenance of Wavelet-Transformed Multidimensional Data," Proc. ACM SIGMOD, ACM Press, 2005, pp. 275–286.
6. R. Schmidt and C. Shahabi, "How to Evaluate Multiple Range-Sum Queries Progressively," Proc. ACM PODS, ACM Press, 2002, pp. 133–141.
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