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Please use this identifier to cite or link to this item: http://dspace.library.iitb.ac.in/jspui/handle/100/1214

Title: Efficient and extensible algorithms for multi query optimization
Authors: ROY, P
SESHADRI, S
SUDARSHAN, S
BHOBE, S
Issue Date: 2000
Publisher: ASSOC COMPUTING MACHINERY
Citation: SIGMOD RECORD,29(2)249-260
Abstract: Complex queries are becoming commonplace, with the growing use of decision support systems. These complex queries often have a lot of common sub-expressions, either within a single query, or across multiple such queries run as a batch. Multiquery optimization aims at exploiting common sub-expressions to reduce evaluation cost. Multi-query optimization has hither-to been viewed as impractical, since earlier algorithms were exhaustive, and explore a doubly exponential search space. In this paper we demonstrate that multi-query optimization using heuristics is practical, and provides significant benefits. We propose 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. Our greedy heuristic incorporates novel optimizations that improve efficiency greatly Our algorithms are designed to be easily added to existing optimizers. We present a performance study comparing the algorithms, using workloads consisting of queries from the TPC-D benchmark. The study shows that our algorithms provide significant benefits over traditional optimization, at a very acceptable overhead in optimization time.
URI: http://dspace.library.iitb.ac.in/xmlui/handle/10054/14407
http://hdl.handle.net/100/1214
ISSN: 0163-5808
Appears in Collections:Proceedings papers

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