- Efficient Approximation of Optimization Queries Under Parametric Aggregation Constraints

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This chapter introduces a new class of queries, optimization under parametric aggregation constraint (OPAC) queries. Such queries aim to identify sets of database tuples constituting solutions to a large class of optimization problems involving the database tuples. The chapter introduces algorithms that pre-process relations and construct indexes to efficiently provide answers to such queries. This chapter analytically quantified the accuracy guarantees of the construction and a thorough evaluation highlighting the impact of various parameters on the performance of the schemes is presented. The constraints and the objective function are specified in terms of aggregate functions of relational attributes, and the parameter values identify the constants used in the aggregation constraints. Results indicate that the methodology is effective and can be deployed easily, utilizing index structures such as R-trees.

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