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DynaMat: a dynamic view management system for data warehouses
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Source International Conference on Management of Data archive
Proceedings of the 1999 ACM SIGMOD international conference on Management of data table of contents
Philadelphia, Pennsylvania, United States
Pages: 371 - 382  
Year of Publication: 1999
ISBN:1-58113-084-8
Also published in ...
Authors
Yannis Kotidis  Department of Computer Science, University of Maryland
Nick Roussopoulos  Department of Computer Science, University of Maryland
Sponsors
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGMOD: ACM Special Interest Group on Management of Data
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 12,   Downloads (12 Months): 94,   Citation Count: 32
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ABSTRACT

Pre-computation and materialization of views with aggregate functions is a common technique in Data Warehouses. Due to the complex structure of the warehouse and the different profiles of the users who submit queries, there is need for tools that will automate the selection and management of the materialized data. In this paper we present DynaMat, a system that dynamically materializes information at multiple levels of granularity in order to match the demand (workload) but also takes into account the maintenance restrictions for the warehouse, such as down time to update the views and space availability. DynaMat unifies the view selection and the view maintenance problems under a single framework using a novel “goodness” measure for the materialized views. DynaMat constantly monitors incoming queries and materializes the best set of views subject to the space constraints. During updates, DynaMat reconciles the current materialized view selection and refreshes the most beneficial subset of it within a given maintenance window. We compare DynaMat against a system that is given all queries in advance and the pre-computed optimal static view selection. The comparison is made based on a new metric, the Detailed Cost Savings Ratio introduced for quantifying the benefits of view materialization against incoming queries. These experiments show that DynaMat's dynamic view selection outperforms the optimal static view selection and thus, any sub-optimal static algorithm that has appeared in the literature.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  32

Collaborative Colleagues:
Yannis Kotidis: colleagues
Nick Roussopoulos: colleagues