ExtGraph: A Fast Extraction Method of User-intended Graphs from a Relational Database

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autores principales: Park, Jeongho, Lee, Geonho, Kim, Min-Soo
Formato: Preprint
Publicado: 2025
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866908554733027328
author Park, Jeongho
Lee, Geonho
Kim, Min-Soo
author_facet Park, Jeongho
Lee, Geonho
Kim, Min-Soo
contents Graph analytics is widely used in many fields to analyze various complex patterns. However, in most cases, important data in companies is stored in RDBMS's, and so, it is necessary to extract graphs from relational databases to perform graph analysis. Most of the existing methods do not extract a user-intended graph since it typically requires complex join query processing. We propose an efficient graph extraction method, \textit{ExtGraph}, which can extract user-intended graphs efficiently by hybrid query processing of outer join and materialized view. Through experiments using the TPC-DS, DBLP, and IMDB datasets, we have shown that \textit{ExtGraph} outperforms the state-of-the-art methods up to by 2.78x in terms of graph extraction time.
format Preprint
id arxiv_https___arxiv_org_abs_2509_18534
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle ExtGraph: A Fast Extraction Method of User-intended Graphs from a Relational Database
Park, Jeongho
Lee, Geonho
Kim, Min-Soo
Databases
Graph analytics is widely used in many fields to analyze various complex patterns. However, in most cases, important data in companies is stored in RDBMS's, and so, it is necessary to extract graphs from relational databases to perform graph analysis. Most of the existing methods do not extract a user-intended graph since it typically requires complex join query processing. We propose an efficient graph extraction method, \textit{ExtGraph}, which can extract user-intended graphs efficiently by hybrid query processing of outer join and materialized view. Through experiments using the TPC-DS, DBLP, and IMDB datasets, we have shown that \textit{ExtGraph} outperforms the state-of-the-art methods up to by 2.78x in terms of graph extraction time.
title ExtGraph: A Fast Extraction Method of User-intended Graphs from a Relational Database
topic Databases
url https://arxiv.org/abs/2509.18534