An efficient method for maintaining data cubes incrementally
DC Field | Value | Language |
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dc.contributor.author | Lee, Ki Yong | - |
dc.contributor.author | Chung, Yon Dohn | - |
dc.contributor.author | Kim, Myung Ho | - |
dc.date.accessioned | 2022-04-19T10:45:24Z | - |
dc.date.available | 2022-04-19T10:45:24Z | - |
dc.date.issued | 2010-03 | - |
dc.identifier.issn | 0020-0255 | - |
dc.identifier.issn | 1872-6291 | - |
dc.identifier.uri | https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/147966 | - |
dc.description.abstract | The data cube operator computes group-bys for all possible combinations of a set of dimension attributes. Since computing a data Cube typically incurs a considerable cost, the data Cube is often precomputed and stored as materialized views in data warehouses. A materialized data cube needs to be updated when the source relations are changed. The incremental maintenance of a data cube is to compute and propagate only its changes, rather than recompute the entire data Cube from scratch. For n dimension attributes, the data cube consists of 2(n) group-bys. each of which is called a cuboid To incrementally maintain a data cube with 2(n) cuboids, the conventional methods Compute 2(n) delta cuboids, each of which represents the change of a cuboid In this paper. we propose an efficient incremental maintenance method that can maintain a data cube using only a subset of 2(n) delta cuboids We formulate an optimization problem to find the optimal subset of 2(n) delta cuboids that minimizes the total maintenance cost, and propose a heuristic solution that allows LIS to maintain a data cube using only (n inverted right perpendicularn/2inverted left perpendicular)delta cuboids. As a result, the cost of maintaining a data cube is substantially reduced Through various experiments, we show the performance advantages of the propo | - |
dc.format.extent | 21 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | ELSEVIER SCIENCE INC | - |
dc.title | An efficient method for maintaining data cubes incrementally | - |
dc.type | Article | - |
dc.publisher.location | 네델란드 | - |
dc.identifier.doi | 10.1016/j.ins.2009.11.037 | - |
dc.identifier.scopusid | 2-s2.0-73149085051 | - |
dc.identifier.wosid | 000274351300012 | - |
dc.identifier.bibliographicCitation | INFORMATION SCIENCES, v.180, no.6, pp 928 - 948 | - |
dc.citation.title | INFORMATION SCIENCES | - |
dc.citation.volume | 180 | - |
dc.citation.number | 6 | - |
dc.citation.startPage | 928 | - |
dc.citation.endPage | 948 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | sci | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | Data cube | - |
dc.subject.keywordAuthor | Data warehouse | - |
dc.subject.keywordAuthor | Materialized view | - |
dc.subject.keywordAuthor | OLAP | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0020025509005076 | - |
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