Conference Paper

Relative prefix sums: an efficient approach for querying dynamic OLAP data cubes

Dept. of Comput. Sci., California Univ., Santa Barbara, CA
DOI: 10.1109/ICDE.1999.754948 Conference: Data Engineering, 1999. Proceedings., 15th International Conference on
Source: DBLP

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

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    ABSTRACT: An Object Oriented Conceptual Model Data Cube is described, on the basis of an example for storage, extraction and analysis of data derived from tests of ship models, conducted in the Bulgarian Ship Hydrodynamics Center - Varna. The main storage parameters as well as the structure of the system are presented. The dynamical level in an object oriented class definition of data cube is described. Future problems of OLAP operations and data analysis methods, included in the UML class definition are outlined.
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    ABSTRACT: The goal of this article is to depict Object Oriented Conceptual Model Data Cube using it as an example. In short, the paper has described: 1) Structural level in object oriented class definition of data cube; 2) The basic methods for computing data cube from relational database by select operator; 3) To set tasks for future work to develop appropriate methods of class to construct data cube in different way from relational operator.
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    ABSTRACT: In a data warehouse, users typically search for trends, patterns, or unusual data behaviors by issuing queries interactively. The OLAP range-sum query is widely used in finding trends and in discovering relationships among attributes in the data warehouse. In a recent environment of enterprises, data elements in a data cube are frequently changed. The problem is that the cost of updating a prefix sum cube is very high. In this paper, we propose a novel algorithm which reduces the update cost significantly by an index structure called the Δ-tree. Also, we propose a hybrid method to provide either approximate or precise results to reduce the overall cost of queries. It is highly beneficial for various applications that need quick approximate answers rather than time consuming accurate ones, such as decision support systems. An extensive experiment shows that our method performs very efficiently on diverse dimensionalities, compared to other methods. ??? ? ??? ?千? ??? ? ??? ??? ? ??? ??? 섂 ?돀遠?? ??? 肴?? ??? ? ?돐 ??? ??? /???? ? ?덐  ? ? N?? a?? ? a?? a?? a?? ? 飢?? ? 飢?? ??? ? ??? ??? ? ??? ??? ? ??? ??? ? ??? ??? ? ? ???? ?? ?? ??? ?? ? ?돐遠?? ??? ??? ??? ? ?돐 ??? ??? 낕?? 뤏 ?덐 삕?? 렏 ? ??? ? ??? ??? ? ??? ??? ? ??? ??? ? ??? ??? ?? ??? ??? ?? ??? ? ???
    The KIPS Transactions PartD 01/2003; 10D(3).


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