Improving query performance on dynamic graphs

• Autores: Gala Barquero Moreno, Javier Troya Castilla, Antonio Vallecido
• Localización: Actas de las XXV Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2021): [Málaga, 22 al 24 de septiembre de 2021] / coord. por Rafael Capilla Sevilla, Maider Azanza Sese, Miguel Rodríguez Luaces, M. M. Roldán García, Dolores Burgueño Caballero, José Raúl Romero Salguero, José Antonio Parejo Maestre, José Francisco Chicano García, Marcela Genero, Óscar Díaz García, José González Enríquez, María Carmen Penades Gramage; Silvia Mara Abrahao Gonzales (col.), 2021
• Idioma: inglés
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• Resumen

  • Querying large models efficiently often imposes high demands on system resources such as memory, processing time, disk access or network latency. The situation becomes more complicated when data are highly interconnected, e.g. in the form of graph structures, and when data sources are heterogeneous, partly coming from dynamic systems and partly stored in databases. These situations are now common in many existing social networking applications and geo-location systems, which require specialized and efficient query algorithms in order to make informed decisions on time. In this paper, we propose an algorithm to improve the memory consumption and time performance of this type of queries by reducing the amount of elements to be processed, focusing only on the information that is relevant to the query but without compromising the accuracy of its results. To this end, the reduced subset of data is selected depending on the type of query and its constituent filters. Three case studies are used to evaluate the performance of our proposal, obtaining significant speedups in all cases.