RPC-ICDE99 - Page 1 Algorithms for the Relative Prefix Sum...

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Page 1 Algorithms for the Relative Prefix Sum Approach to Range Sum Queries in Data Cubes S. Geffner D. Agrawal A. El Abbadi T. Smith Department of Computer Science University of California Santa Barbara, CA 93106 {sgeffner, agrawal, amr, smithtr}@cs.ucsb.edu Abstract Range sum queries on data cubes are a powerful tool for analysis. A range sum query applies an aggregation operation (e.g., SUM) over all selected cells in a data cube, where the selection is specified by providing ranges of values for numeric dimensions. Many application domains require that information provided by analysis tools be current or "near-current." Existing techniques for range sum queries on data cubes, however, can incur update costs on the order of the size of the data cube. Since the size of a data cube is exponential in the number of its dimensions, rebuilding the entire data cube can be very costly. We present an approach that achieves constant time range sum queries while constraining update costs. Our method reduces the overall complexity of the range sum problem. 1 Introduction The data cube [GBLP96], also known in the OLAP community as the multidimensional database [OLA96][AGS97], is designed to provide aggregate information that can be used to analyze the contents of databases and data warehouses. A data cube is constructed from a subset of attributes in the database. Certain attributes are chosen to be measure attributes , i.e., the attributes whose values are of interest. Other attributes are selected as dimensions or functional attributes . The measure attributes are aggregated according to the dimensions. For example, consider a hypothetical database maintained by an insurance company. One may construct a data cube from the database with SALES as a measure attribute, and CUSTOMER_AGE and DATE_OF_SALE as dimensions; such a data cube provides aggregated total sales figures for all combinations of region and date. Range sum queries are useful analysis tools when applied to data cubes. A range sum query sums the measure attribute within the range of the query; an example is find the total sales for customers with an age from 37 to 52, over the past three months. Queries of this form can be very useful in finding trends This research is partially supported by NSF under grant number IRI94-11330. To appear in the Proceedings of ICDE'99. Portions of this document are Copyright 1999 IEEE. The material in this paper is patent pending. For information, contact Mathew L. Grell, University of California Office of Technology Transfer, 1111 Franklin Street, Fifth Floor, Oakland, CA 95607-5200 Email: [email protected]
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Page 2 and in discovering relationships between attributes in the database. Range sum queries over data cubes thus provide a useful tool for analysis. Efficient range-sum querying is becoming more important with the growing interest in database analysis, particularly in On-Line Analytical Processing (OLAP).
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RPC-ICDE99 - Page 1 Algorithms for the Relative Prefix Sum...

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