Una Implementación para el Agrupamiento Difuso en SQL

Ana Isabel Aguilera-Faraco; Marlene Goncalves-Da Silva

Ana Isabel Aguilera-Faraco Escuela de Ingeniería Informática, Facultad de Ingeniería, Universidad de Valparaíso, Valparaíso 2340000, Chile
Marlene Goncalves-Da Silva Departamento de Computación y Tecnología de la Información, Universidad Simón Bolívar, Caracas, Venezuela, Apartado 89000, Caracas, Venezuela.

Palabras clave: Fuzzy Group By, PostgreSQLf, arquitectura fuertemente acoplada / Fuzzy Group By, tight coupled architecture

Resumen

Resumen

Los sistemas de gestión de bases de datos (SGBD) relacionales tienen una gran utilidad en el almacenamiento eficiente de grandes volúmenes de datos. En este sentido, se han propuesto algunas extensiones de los SGBD basadas en la lógica difusa, para mejorar la expresividad de los lenguajes de consulta, entre ellos, el lenguaje SQLf (extensión de SQL que soporta condiciones difusas). Por otra parte, el Group-By es un operador de base de datos ampliamente utilizado en el análisis de datos y en los sistemas de apoyo a la toma de decisiones. En muchos casos, parece útil agrupar los valores según su similitud con un determinado concepto, en lugar de establecer la agrupación sobre la base de valores iguales. En este contexto, se ha propuesto una nueva estructura de SQLf denominada Fuzzy Group By (FGB), para apoyar una agrupación basada en particiones difusas. En este trabajo, se incorporó la agrupación difusa en PostgreSQLf, que es una extensión del SGBD PostgreSQL, para el manejo de consultas difusas utilizando el lenguaje SQLf con una arquitectura fuertemente acoplada (directamente en el SGBD). Se propone un algoritmo basado en un hash para evaluar el operador FGB y también se evalúa empíricamente el rendimiento de PostgreSQLf sobre el Benchmark™ TPC-H.

Abstract

Relational DataBase management systems (DBMS) have a great utility in the efficient storage of large data volumes. Also, some DBMS extensions based on fuzzy logic have been proposed to improve the expressiveness of query languages. Among which SQLf is an extension of SQL that supports fuzzy conditions. Separately, the Group-By is a database operator widely used in data analysis and decision support systems. In many cases, it seems useful to group values according to their similarity to a certain concept rather than establishing grouping on the basis of equal values. In this context, a new SQLf structure called Fuzzy Group By (FGB) has been proposed to support a grouping based on fuzzy partitions. In this work, we incorporated the fuzzy grouping in PostgreSQLf, which is an extension of the PostgreSQL DBMS for the handling of fuzzy queries using the SQLf language on the basis of a tight coupled architecture, i.e., directly into the DBMS. We have proposed an algorithm based on a hash to evaluate the FGB operator and also empirically assessed the performance of PostgreSQLf over the TPC Benchmark™ -H (TPC-H).

https://doi.org/10.22209/rt.v44n1a05

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Biografía del autor/a

Ana Isabel Aguilera-Faraco, Escuela de Ingeniería Informática, Facultad de Ingeniería, Universidad de Valparaíso, Valparaíso 2340000, Chile

Ana Aguilera was born in Lara, Venezuela. She received the B.S. in Computer Science Engineer from Universidad Centrooccidental Lisandro Alvarado (UCLA) of Barquisimeto, Venezuela, in 1994, M.S. degree in Computer science from the Universidad Simon Bolívar of Caracas, Venezuela, in 1998 and the Ph. D. degree in medical informatics from Université de Rennes I, Rennes, France, in 2008. She was Full Professor 1997-2018 and Head of Centre of Analysis, Treatment and Data Modeling, FACYT at Universidad de Carabobo, Venezuela. She is currently Full Professor at Universidad de Valparaíso, Facultad de Ingeniería, Escuela de Ingeniería Civil Informática, Valparaíso, Chile. Her research interest includes the fuzzy databases, data mining and medical informatics. Mrs. Aguilera obtained the BSc. honors degree in Computer Engineering, Magna Cum Laude Award from UCLA and “Très honorable” Award in the PhD thesis from Rennes I. She participated in Fulbright program, 2012 at the James Madison University, Harrisonburg, VA and Visitor Professor at Université de Valenciennes. France 2009-2012. She has shared in the welcome venue panel for youth girls to Informatics Engineering, Universidad de Valparaiso, 2018 and in The Chilean Women Meeting in Computer Engineering, Chile WiC 2018, ACM,2018, UTFSM, Valparaíso.

Marlene Goncalves-Da Silva, Departamento de Computación y Tecnología de la Información, Universidad Simón Bolívar, Caracas, Venezuela, Apartado 89000, Caracas, Venezuela.

Marlene Goncalves was born in Caracas, Venezuela. She received the B.S. in Computer Science from Universidad Central de Venezuela (UCV), Caracas, Venezuela, 1998, M.S. degree in Computer science from the Universidad Simón Bolívar (USB), Caracas, Venezuela, 2001, the Ph. D. degree in Computer Science, Universidad Simón Bolívar (USB), Caracas, Venezuela, 2009. She is a Full Professor and Member of the Academic Staff of the USB (since 2002). She has the ONCTI Researcher Promotion Program (PPI) Accreditation as a Researcher Level I (2009). She has received the distinction of Meritorious Professor from CONABA (2004). Visiting Researcher in Youngstown State University. USA (2009-2010). Short term post-doc stay: Escuela Universitaria Politécnia de Teruel (EUPT), Universidad de Zaragoza, Spain. Fundación Carolina (2017). Research Stays for University Academics and Scientists: TIB-Leibniz Information Centre for Science and Technology University Library, Hannover, Germany. DAAD (2018). Junior Researcher: Universidad Politécnica de Madrid. Spain (2019-2020). Her area of current research is Database and Software Engineering and has 35 articles in extenso in international conferences, 13 book chapters and 12 articles in national and international journals in the area of databases.

Citas

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Una Implementación para el Agrupamiento Difuso en SQL

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