Materialized view selection and maintenance using multi-query optimization
Hoshi Mistry,Prasan Roy,Sundararajarao Sudarshan,Krithi Ramamritham +3 more
- 01 May 2001
- Vol. 30, Iss: 2, pp 307-318
TL;DR: This paper shows how to find an efficient plan for the maintenance of a set of materialized views, by exploiting common subexpressions between different view maintenance expressions, and develops a framework that cleanly integrates the various choices in a systematic and efficient manner.
read more
Abstract: Materialized views have been found to be very effective at speeding up queries, and are increasingly being supported by commercial databases and data warehouse systems. However, whereas the amount of data entering a warehouse and the number of materialized views are rapidly increasing, the time window available for maintaining materialized views is shrinking. These trends necessitate efficient techniques for the maintenance of materialized views.In this paper, we show how to find an efficient plan for the maintenance of a set of materialized views, by exploiting common subexpressions between different view maintenance expressions. In particular, we show how to efficiently select (a) expressions and indices that can be effectively shared, by transient materialization; (b) additional expressions and indices for permanent materialization; and (c) the best maintenance plan — incremental or recomputation — for each view. These three decisions are highly interdependent, and the choice of one affects the choice of the others. We develop a framework that cleanly integrates the various choices in a systematic and efficient manner. Our evaluations show that many-fold improvement in view maintenance time can be achieved using our techniques. Our algorithms can also be used to efficiently select materialized views to speed up workloads containing queries and updates.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Continuously adaptive continuous queries over streams
Samuel Madden,Mehul A. Shah,Joseph M. Hellerstein,Vijayshankar Raman +3 more
- 03 Jun 2002
TL;DR: This work presents a continuously adaptive, continuous query (CACQ) implementation based on the eddy query processing framework that provides significant performance benefits over existing approaches to evaluating continuous queries, not only because of its adaptivity, but also because of the aggressive cross-query sharing of work and space that it enables.
Efficient exploitation of similar subexpressions for query processing
Jingren Zhou,Per-Ake Larson,Johann-Christoph Freytag,Wolfgang Lehner +3 more
- 11 Jun 2007
TL;DR: This work introduces a light-weight and effective mechanism to detect potential sharing opportunities among expressions and presents the first comprehensive solution covering all aspects of the problem: detection, construction, and cost-based optimization.
136
The design and evaluation of a query processing architecture for sensor networks
Samuel Madden,Michael J. Franklin +1 more
- 01 Jan 2003
TL;DR: This dissertation summarizes the issues and opportunities associated with collecting and processing information from these wireless sensor networks, focusing on the performance and ease-of-use advantages of a declarative, query-based approach.
116
Design and evaluation of alternative selection placement strategies in optimizing continuous queries
Jianjun Chen,David J. DeWitt,Jeffrey F. Naughton +2 more
- 07 Aug 2002
TL;DR: In this paper, the authors design and evaluate alternative selection placement strategies for optimizing a very large number of continuous queries in an Internet environment, and propose two grouping strategies, PushDown and PullUp, in which selections are either pushed below, or pulled above, joins.
Recommending materialized views and indexes with the IBM DB2 design advisor
Daniel C. Zilio,Calisto Zuzarte,Sam Lightstone,Wenbin Ma,Guy M. Lohman,Roberta Jo Cochrane,Hamid Pirahesh,Latha S. Colby,Jarek Gryz,E. Alton,G. Valentin +10 more
- 17 May 2004
TL;DR: This paper presents an advanced tool that uses the query optimizer itself to both suggest and evaluate candidate MVs and indexes, and a simple, practical, and effective algorithm for rapidly finding good solutions even for large workloads.
References
Implementing data cubes efficiently
Venky Harinarayan,Anand Rajaraman,Jeffrey D. Ullman +2 more
- 01 Jun 1996
TL;DR: In this article, a lattice framework is used to express dependencies among views and greedy algorithms are presented to determine a good set of views to materialize, with a small constant factor of optimal.
Multiple-query optimization
TL;DR: The results show that using multiple- query processing algorithms may reduce execution cost considerably, and the presentation and analysis of algorithms that can be used for multiple-query optimization are presented.
•Book
Maintenance of materialized views: problems, techniques, and applications
Ashish Gupta,Inderpal Singh Mumick +1 more
- 01 Jun 1999
TL;DR: This chapter contains sections titled: Introduction, The Idea Behind View Maintenance, Using Full Information, Using Partial Information, Open Problems, Acknowledgments.
770
The Volcano optimizer generator: extensibility and efficient search
Goetz Graefe,William J. McKenna +1 more
- 19 Apr 1993
TL;DR: The Volcano project, which provides efficient, extensible tools for query and request processing, particularly for object-oriented and scientific database systems, is reviewed, and it is shown that the search engine of the Volcano optimizer generator is more extensible and powerful.
•Posted Content
Efficient and Extensible Algorithms for Multi Query Optimization
TL;DR: This paper proposes three cost-based heuristic algorithms: Volcano-SH and Volcano-RU, which are based on simple modifications to the Volcano search strategy, and a greedy heuristic that incorporates novel optimizations that improve efficiency greatly.
400