Star/snow-flake schema driven object-relational data warehouse design and query processing strategies
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Title of host publication | Data Warehousing and Knowledge Discovery |
Subtitle of host publication | 1st International Conference, DaWaK 1999, Proceedings |
Editors | A. Min Tjoa, Mukesh Mohania |
Publisher | Springer Verlag |
Pages | 11-22 |
Volume | 1676 |
ISBN (print) | 3540664580, 9783540664581 |
Publication status | Published - 1999 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 1676 |
ISSN (Print) | 0302-9743 |
ISSN (electronic) | 1611-3349 |
Conference
Title | 1st International Conference on Data Warehousing and Knowledge Discovery, DaWaK 1999 |
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Place | Italy |
City | Florence |
Period | 30 August - 1 September 1999 |
Link(s)
Abstract
The conventional star schema model of Data Warehouse (DW) has its limitations due to the nature of the relational data model. Firstly, this model cannot represent the semantics and operations of multi-dimensional data adequately. Due to the hidden semantics, it is difficult to efficiently address the problems of view design. Secondly, as we move up to higher levels of summary data (multiple complex aggregations), SQL queries do not portray the intuition needed to facilitate buildingand supporting efficient execution of complex queries on complex data. In light of these issues, we propose the Object- Relational View (ORV) design for DWs. Using Object-Oriented (O-O) methodology, we can explicitly represent the semantics and reuse view (class) definitions based on the ISA hierarchy and the class composition hierarchies, thereby resulting in a more efficient view mechanism. Part of the design involves providing a translation mechanism from the star/snowflake schema to an O-O representation. This is done by flattening the fact-dimension schema and converting it to a class-composition hierarchy in an O-O framework. Vertically partitioning this O-O schema further increases the efficiency of query execution by reducing disk access. We then build a Structural Join Index Hierarchy (SJIH) on this partitioned schema to facilitate complex object retrieval and avoid using a sequence of expensive pointer chasing (or join) operations.
Citation Format(s)
Star/snow-flake schema driven object-relational data warehouse design and query processing strategies. / Gopalkrishnan, Vivekanand; Li, Qing; Karlapalem, Kamalakar.
Data Warehousing and Knowledge Discovery: 1st International Conference, DaWaK 1999, Proceedings. ed. / A. Min Tjoa; Mukesh Mohania. Vol. 1676 Springer Verlag, 1999. p. 11-22 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1676).
Data Warehousing and Knowledge Discovery: 1st International Conference, DaWaK 1999, Proceedings. ed. / A. Min Tjoa; Mukesh Mohania. Vol. 1676 Springer Verlag, 1999. p. 11-22 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1676).
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review