pCube

Update-efficient online aggregation with progressive feedback and error bounds

Mirek Riedewald, Divyakant Agrawal, Amr El Abbadi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Citations (Scopus)

Abstract

Multidimensional data cubes are used in large data warehouses as a tool for online aggregation of information. As the number of dimensions increases, supporting efficient queries as well as updates to the data cube becomes difficult. Another problem that arises with increased dimensionality is the sparseness of the data space. In this paper we develop a new data structure referred to as the pCube (data cube for progressive querying), to support efficient querying and updating of multidimensional data cubes in large data warehouses. While the pCube concept is very general and can be applied to any type of query, we mainly focus on range queries that summarize the contents of regions of the data cube. pCube provides intermediate results with absolute error bounds (to allow trading accuracy for fast response time), efficient updates, scalability with increasing dimensionality, and pre-aggregation to support summarization of large ranges. We present both a general solution and an implementation of pCube and report the results of experimental evaluations.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Scientific and Statistical Database Management, SSDBM
Place of PublicationLos Alamitos, CA, United States
PublisherIEEE
Pages95-108
Number of pages14
Publication statusPublished - 3 Dec 2000
Externally publishedYes
EventSSDBM 2000: 12th International Conference on Scientific and Statistical Database Management - Berlin, Ger
Duration: 26 Jul 200028 Jul 2000

Other

OtherSSDBM 2000: 12th International Conference on Scientific and Statistical Database Management
CityBerlin, Ger
Period26/7/0028/7/00

Fingerprint

Data Cube
Data warehouses
Error Bounds
Aggregation
Agglomeration
Update
Feedback
Multidimensional Data
Data Warehouse
Large Data
Data structures
Scalability
Dimensionality
Query
Range Query
Summarization
Experimental Evaluation
General Solution
Response Time
Updating

ASJC Scopus subject areas

  • Software
  • Applied Mathematics

Cite this

Riedewald, M., Agrawal, D., & Abbadi, A. E. (2000). pCube: Update-efficient online aggregation with progressive feedback and error bounds. In Proceedings of the International Conference on Scientific and Statistical Database Management, SSDBM (pp. 95-108). Los Alamitos, CA, United States: IEEE.

pCube : Update-efficient online aggregation with progressive feedback and error bounds. / Riedewald, Mirek; Agrawal, Divyakant; Abbadi, Amr El.

Proceedings of the International Conference on Scientific and Statistical Database Management, SSDBM. Los Alamitos, CA, United States : IEEE, 2000. p. 95-108.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Riedewald, M, Agrawal, D & Abbadi, AE 2000, pCube: Update-efficient online aggregation with progressive feedback and error bounds. in Proceedings of the International Conference on Scientific and Statistical Database Management, SSDBM. IEEE, Los Alamitos, CA, United States, pp. 95-108, SSDBM 2000: 12th International Conference on Scientific and Statistical Database Management, Berlin, Ger, 26/7/00.
Riedewald M, Agrawal D, Abbadi AE. pCube: Update-efficient online aggregation with progressive feedback and error bounds. In Proceedings of the International Conference on Scientific and Statistical Database Management, SSDBM. Los Alamitos, CA, United States: IEEE. 2000. p. 95-108
Riedewald, Mirek ; Agrawal, Divyakant ; Abbadi, Amr El. / pCube : Update-efficient online aggregation with progressive feedback and error bounds. Proceedings of the International Conference on Scientific and Statistical Database Management, SSDBM. Los Alamitos, CA, United States : IEEE, 2000. pp. 95-108
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