Histogram Techniques for Cost Estimation in Query Optimization: A Study in Relational Database Systems - Couverture souple

Yu, Xiaohui

 
9783639379068: Histogram Techniques for Cost Estimation in Query Optimization: A Study in Relational Database Systems
Couverture souple
ISBN 10 : 3639379063 ISBN 13 : 9783639379068
Editeur : VDM Verlag Dr. Müller, 2011

Synopsis

Query optimization is an important task of Relational Database Management Systems. A typical query optimizer estimates the cost of various execution plans for a given query, and selects the one with the lowest cost. The accuracy of cost estimation is crucial in that it directly affects the quality of the decisions made by query optimizers. Seletivity estimation is an important part of cost estimation. Many commercial DBMSs maintain histograms to summarize the contents of relations in order to perform efficient selectivity estimations. In this book, we review the various existing histogram techniques, and propose two new types of histograms: the piecewise linear histogram and the A- Optimal histogram. Experiements show that they perform better than existing histogram in many cases. We also consider the problem of building global histograms. By adaptively allocate the given storage space to individual histograms according to their skewness, we can reduce the overall estimation error. Finally, we address the dynamic maintenance of histograms, and propose an efficient maintenance method for the piecewise linear histogram based on the probabilistic counting technique.

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Présentation de l'éditeur

Query optimization is an important task of Relational Database Management Systems. A typical query optimizer estimates the cost of various execution plans for a given query, and selects the one with the lowest cost. The accuracy of cost estimation is crucial in that it directly affects the quality of the decisions made by query optimizers. Seletivity estimation is an important part of cost estimation. Many commercial DBMSs maintain histograms to summarize the contents of relations in order to perform efficient selectivity estimations. In this book, we review the various existing histogram techniques, and propose two new types of histograms: the piecewise linear histogram and the A- Optimal histogram. Experiements show that they perform better than existing histogram in many cases. We also consider the problem of building global histograms. By adaptively allocate the given storage space to individual histograms according to their skewness, we can reduce the overall estimation error. Finally, we address the dynamic maintenance of histograms, and propose an efficient maintenance method for the piecewise linear histogram based on the probabilistic counting technique.

Biographie de l'auteur

Dr. Xiaohui Yu holds a B.Sc. from Nanjing University, China, a M.Phil. from the Chinese University of Hong Kong, and a Ph.D. from the University of Toronto, Canada. His research interests include databases, data mining, and the Web.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
VDM Verlag Dr. Müller
Date d'édition
2011
Langue
anglais
ISBN 10 
3639379063
ISBN 13 
9783639379068
Reliure
Broché
Nombre de pages
128
Coordonnées du fabricant
non disponible
Personne responsable
non disponible