Maintaining materialized views for data warehouses with multiple remote sources
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AbstractA data warehouse is a data repository which collects and maintains a large amount of data from multiple distributed, autonomous and possibly heterogeneous data sources. Often the data is stored in the form of materialized views in order to provide fast access to the integrated data. However, to maintain the data in the warehouse consistent with the source data is a challenging task in a multiple remote source environment. Transactions containing multiple updates at one or more sources further complicate the consistency issue. In this paper we first consider improving the refresh time of select-project-join (SPJ) type materialized views in a data warehouse by presenting a frequency-partitioned based algorithm, which takes into account the source update frequencies and the total space for auxiliary data. We then propose a solution in the design of data warehouses which can handle a variety of materialized views with different refreshment requirements.
All Author(s) ListLiang WF, Johnson C, Yu JX
Name of Conference1st International Conference on Web-Age Information Management (WAIM 2000)
Start Date of Conference21/06/2000
End Date of Conference23/06/2000
Place of ConferenceSHANGHAI
Journal nameLecture Notes in Artificial Intelligence
Volume Number1846
Pages299 - 310
LanguagesEnglish-United Kingdom
Web of Science Subject CategoriesComputer Science; Computer Science, Information Systems; Computer Science, Theory & Methods

Last updated on 2021-13-01 at 23:43