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An integer linear programming approach to database design
 In SMDB ’07, ICDE Workshop on SelfManaging Databases
, 2007
"... Existing index selection tools rely on heuristics to efficiently search within the large space of alternative solutions and to minimize the overhead of using the query optimizer for cost estimation. Index selection heuristics, despite being practical, are hard to analyze and formally compute how clo ..."
Abstract

Cited by 8 (2 self)
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Existing index selection tools rely on heuristics to efficiently search within the large space of alternative solutions and to minimize the overhead of using the query optimizer for cost estimation. Index selection heuristics, despite being practical, are hard to analyze and formally compute how close they get to the optimal solution. In this paper we propose a model for index selection based on Integer Linear Programming (ILP). The ILP formulation enables a wealth of combinatorial optimization techniques for providing quality guarantees, approximate solutions and even for computing optimal solutions. We present a system architecture for ILPbased index selection, in the context of commercial database systems. Our ILPbased approach offers higher solution quality, efficiency and scalability without sacrificing any of the precision offered by existing index selection tools. 1.
Automated Database Design for LargeScale Scientific Applications
, 2007
"... CCF0326453, IIS0133686, and CCF0205544, as well as through the NASA AISR Program. The views and conclusions contained in this document are those of the author and should not be interpreted as representing the official policies, either expressed or implied, of any sponsoring institution, ..."
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CCF0326453, IIS0133686, and CCF0205544, as well as through the NASA AISR Program. The views and conclusions contained in this document are those of the author and should not be interpreted as representing the official policies, either expressed or implied, of any sponsoring institution,
Analysis and Indexing—Indexing methods
"... Query substitution is an important problem in information retrieval. Much work focuses on how to find substitutes for any given query. In this paper, we study how to efficiently process a keyword query whose substitutes are defined by a given taxonomy. This problem is challenging because each term i ..."
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Query substitution is an important problem in information retrieval. Much work focuses on how to find substitutes for any given query. In this paper, we study how to efficiently process a keyword query whose substitutes are defined by a given taxonomy. This problem is challenging because each term in a query can have a large number of substitutes, and the original query can be rewritten into any of their combinations. We propose to build an additional index (besides inverted index) to efficiently process queries. For a query workload, we formulate an optimization problem which chooses the additional index structure, aiming at minimizing the query evaluation cost, under given index space constraints. We show the NPhardness of the problem, and propose a pseudopolynomial time algorithm using dynamic programming, as well as an 1 4 (1−1/e)approximation algorithm to solve the problem. Experimental results show that, with only 10 % additional index space, our approach can greatly reduce the query evaluation cost.
An Integer Linear Programming Approach to Database Design
"... Existing index selection tools rely on heuristics to efficiently search within the large space of alternative solutions and to minimize the overhead of using the query optimizer for cost estimation. Index selection heuristics, despite being practical, are hard to analyze and formally compute how clo ..."
Abstract
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Existing index selection tools rely on heuristics to efficiently search within the large space of alternative solutions and to minimize the overhead of using the query optimizer for cost estimation. Index selection heuristics, despite being practical, are hard to analyze and formally compute how close they get to the optimal solution. In this paper we propose a model for index selection based on Integer Linear Programming (ILP). The ILP formulation enables a wealth of combinatorial optimization techniques for providing quality guarantees, approximate solutions and even for computing optimal solutions. We present a system architecture for ILPbased index selection, in the context of commercial database systems. Our ILPbased approach offers higher solution quality, efficiency and scalability without sacrificing any of the precision offered by existing index selection tools. 1.