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Ttito, J., (2022). Query co-planning for shared execution in key-value stores [Tesis, Universidad Católica San Pablo]. https://hdl.handle.net/20.500.12590/17104
Ttito, J., Query co-planning for shared execution in key-value stores [Tesis]. PE: Universidad Católica San Pablo; 2022. https://hdl.handle.net/20.500.12590/17104
@misc{renati/76942,
title = "Query co-planning for shared execution in key-value stores",
author = "Ttito Amezquita, Josue Joel",
publisher = "Universidad Católica San Pablo",
year = "2022"
}
Title: Query co-planning for shared execution in key-value stores
Authors(s): Ttito Amezquita, Josue Joel
Advisor(s): Marroquin Mogrovejo, Renato Javier
Keywords: Key-value stores; Range queries; Bases de Datos; Optimización de cargas de trabajo compartido
OCDE field: http://purl.org/pe-repo/ocde/ford#1.02.01
Issue Date: 2022
Institution: Universidad Católica San Pablo
Abstract: Large amounts of data are being stored and queried using different data
models. For each of these models, there are specialized data stores which
are then accessed concurrently by many different applications. For instance,
key-value stores provide a simple data model of key and value pairs. Thus,
the simplicity of their read and write interface. Additionally, they provide
other operations such as full and range scans. However, along with its
simplicity, key-value stores impose some limitations when trying to optimize
data access. In this work, we study how to minimize the data movement
when executing a large number of range queries on key-value stores. This
is based on the observation that when accessing a common dataset, there
is usually a (possibly large) overlap among queries accessing it. Thus, to
accomplish this, we use shared-workload optimization techniques to execute
a group of queries together. We analyze different data structures suitable
for co-planning multiple range queries together in order to reduce the total
amount of data transferred. Our results show that by co-planning a group
of range queries we reduce the total execution time of a query workload
Link to repository: https://hdl.handle.net/20.500.12590/17104
Discipline: Ciencia de la Computación
Grade or title grantor: Universidad Católica San Pablo. Departamento de Ciencia de la Computación
Grade or title: Maestro en Ciencia de la Computación
Juror: José Eduardo Ochoa Luna; José Eduardo Talavera; Sergio Lifschitz; Lewis John McGibbney
Register date: 25-Mar-2022
This item is licensed under a Creative Commons License