Towards Selecting the Informative Alternative Relational Query Plans for Database Education

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autores principales: Wang, Hu, Li, Hui, Bhowmick, Sourav S, Ma, Zihao
Formato: Preprint
Publicado: 2022
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866915847366246400
author Wang, Hu
Li, Hui
Bhowmick, Sourav S
Ma, Zihao
author_facet Wang, Hu
Li, Hui
Bhowmick, Sourav S
Ma, Zihao
contents Off-the-shelf RDBMS typically expose only the query execution plan (QEP) of an SQL query, without presenting information about representative alternative query plans (AQPs) considered during plan selection in a user-friendly manner. Providing easy access to representative AQPs is valuable in database education, as it helps learners understand the plan choices made by a query optimizer, one of the several important components related to relational query processing. In this paper, we present a novel problem called the informative plan selection problem (TIPS), which aims to discover a set of k informative AQPs from the underlying plan space so that the plan informativeness of the set is maximized. Specifically, we explore two variants of the problem, batch TIPS and incremental TIPS, to cater to diverse learners. Due to the computational hardness of the problem, we present an approximation algorithm to address it efficiently while providing theoretical guarantees for the results. An extensive experimental study, including feedback from real-world learners and a three-year in-class evaluation of academic outcomes, demonstrates the effectiveness of our solutions for database education.
format Preprint
id arxiv_https___arxiv_org_abs_2210_13722
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Towards Selecting the Informative Alternative Relational Query Plans for Database Education
Wang, Hu
Li, Hui
Bhowmick, Sourav S
Ma, Zihao
Databases
H.2.4
Off-the-shelf RDBMS typically expose only the query execution plan (QEP) of an SQL query, without presenting information about representative alternative query plans (AQPs) considered during plan selection in a user-friendly manner. Providing easy access to representative AQPs is valuable in database education, as it helps learners understand the plan choices made by a query optimizer, one of the several important components related to relational query processing. In this paper, we present a novel problem called the informative plan selection problem (TIPS), which aims to discover a set of k informative AQPs from the underlying plan space so that the plan informativeness of the set is maximized. Specifically, we explore two variants of the problem, batch TIPS and incremental TIPS, to cater to diverse learners. Due to the computational hardness of the problem, we present an approximation algorithm to address it efficiently while providing theoretical guarantees for the results. An extensive experimental study, including feedback from real-world learners and a three-year in-class evaluation of academic outcomes, demonstrates the effectiveness of our solutions for database education.
title Towards Selecting the Informative Alternative Relational Query Plans for Database Education
topic Databases
H.2.4
url https://arxiv.org/abs/2210.13722