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An Alternative Storage Organization for ROLAP Aggregate Views Based on Cubetrees.

Yannis Kotidis, Nick Roussopoulos: An Alternative Storage Organization for ROLAP Aggregate Views Based on Cubetrees. SIGMOD Conference 1998: 249-258
@inproceedings{DBLP:conf/sigmod/KotidisR98,
  author    = {Yannis Kotidis and
               Nick Roussopoulos},
  editor    = {Laura M. Haas and
               Ashutosh Tiwary},
  title     = {An Alternative Storage Organization for ROLAP Aggregate Views
               Based on Cubetrees},
  booktitle = {SIGMOD 1998, Proceedings ACM SIGMOD International Conference
               on Management of Data, June 2-4, 1998, Seattle, Washington, USA},
  publisher = {ACM Press},
  year      = {1998},
  isbn      = {0-89791-995-5},
  pages     = {249-258},
  ee        = {http://doi.acm.org/10.1145/276304.276327, db/conf/sigmod/KotidisR98.html},
  crossref  = {DBLP:conf/sigmod/98},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

The Relational On-Line Analytical Processing (ROLAP) is emerging as the dominant approach in data warehousing with decision support applications. In order to enhance query performance, the ROLAP approach relies on selecting and materializing in summary tables appropriate subsets of aggregate views which are then engaged in speeding up OLAP queries. However, a straight forward relational storage implementation of materialized ROLAP views is immensely wasteful on storage and incredibly inadequate on query performance and incremental update speed. In this paper we propose the use of Cubetrees, a collection of packed and compressed R-trees, as an alternative storage and index organization for ROLAP views and provide an efficient algorithm for mapping an arbitrary set of OLAP views to a collection of Cubetrees that achieve excellent performance. Compared to a conventional (relational) storage organization of materialized OLAP views, Cubetrees offer at least a 2-1 storage reduction, a 10-1 better OLAP query performance, and a 100-1 faster updates. We compare the two alternative approaches with data generated from the TPC-D benchmark and stored in the Informix Universal Server (IUS). The straight forward implementation materializes the ROLAP views using IUS tables and conventional B-tree indexing. The Cubetree implementation materializes the same ROLAP views using a Cubetree Datablade developed for IUS. The experiments demonstrate that the Cubetree storage organization is superior in storage, query performance and update speed.

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Laura M. Haas, Ashutosh Tiwary (Eds.): SIGMOD 1998, Proceedings ACM SIGMOD International Conference on Management of Data, June 2-4, 1998, Seattle, Washington, USA. ACM Press 1998, ISBN 0-89791-995-5 BibTeX , SIGMOD Record 27(2), June 1998
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Referenced by

  1. Mirek Riedewald, Divyakant Agrawal, Amr El Abbadi: Flexible Data Cubes for Online Aggregation. ICDT 2001: 159-173
  2. Theodore Johnson, Dennis Shasha: Some Approaches to Index Design for Cude Forests. IEEE Data Eng. Bull. 22(4): 22-30(1999)
  3. Jianzhong Li, Doron Rotem, Jaideep Srivastava: Aggregation Algorithms for Very Large Compressed Data Warehouses. VLDB 1999: 651-662
  4. Nick Roussopoulos, Yannis Kotidis, Yannis Sismanis: The Active MultiSync Controller of the Cubetree Storage Organization. SIGMOD Conference 1999: 582-583
  5. Yannis Kotidis, Nick Roussopoulos: DynaMat: A Dynamic View Management System for Data Warehouses. SIGMOD Conference 1999: 371-382
BibTeX
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