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Materialized view selection in a data warehouse using evolutionary algorithms

Jorng‐Tzong Horng, Yu-Jan Chang, Baw‐Jhiune Liu, Cheng-Yuan Kao

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Abstract

A data warehouse stores lots of materialized views to provide an efficient decision-support or OLAP queries. The view-selection problem addresses to select a fittest set of materialized views from a variety of MVPPs (Yang, 1997) forms a challenge in data warehouse research. In this paper, we present genetic algorithm to choose materialized views. We also use experiments to demonstrate the power of our approach.

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What this paper is about

A data warehouse stores lots of materialized views to provide an efficient decision-support or OLAP queries. The view-selection problem addresses to select a fittest set of materialized views from a variety of MVPPs (Yang, 1997) forms a challenge in data warehouse research. In this paper, we present genetic algorithm to choose materialized views. We also use experiments to demonstrate the power of our approach.

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Available abstract

A data warehouse stores lots of materialized views to provide an efficient decision-support or OLAP queries. The view-selection problem addresses to select a fittest set of materialized views from a variety of MVPPs (Yang, 1997) forms a challenge in data warehouse research. In this paper, we present genetic algorithm to choose materialized views. We also use experiments to demonstrate the power of our approach.

Key concepts: Materialized view, Data warehouse, Online analytical processing, Computer science, Selection (genetic algorithm), Variety (cybernetics), Genetic algorithm, Set (abstract data type)

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