GADIS: A genetic algorithm for database index selection

Priscilla Neuhaus, Julia Couto, Jonatas Wehrmann, Duncan D. Ruiz, Felipe Meneguzzi

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

5 Citations (Scopus)

Abstract

Creating an optimal amount of indexes, taking into account query performance and database size remains a challenge. In theory, one can speed up query response by creating indexes on the most used columns, although causing slower data insertion and deletion, and requiring a much larger amount of memory for storing the indexing data, but in practice, it is very important to balance such a trade-off. This is not a trivial task that often requires action from the Database Administrator. We address this problem by introducing GADIS, A Genetic Algorithm for Database Index Selection, designed to automatically select the best configuration of indexes adaptable for any database schema. This method aims to find the fittest individuals for optimizing both query response time, and disk required for the indexed data. We evaluate the effectiveness of GADISthrough several experiments we developed based on a standard database benchmark, compare it to three baseline indexing strategies, and show that our approach consistently leads to a better resulting index configuration.

Original languageEnglish
Title of host publicationProceedings - SEKE 2019
Subtitle of host publication31st International Conference on Software Engineering and Knowledge Engineering
PublisherKnowledge Systems Institute Graduate School
Pages39-42
Number of pages4
ISBN (Electronic)1891706489
DOIs
Publication statusPublished - 2019
Event31st International Conference on Software Engineering and Knowledge Engineering, SEKE 2019 - Lisbon, Portugal
Duration: 10 Jul 201912 Jul 2019

Publication series

NameProceedings of the International Conference on Software Engineering and Knowledge Engineering, SEKE
Volume2019-July
ISSN (Print)2325-9000
ISSN (Electronic)2325-9086

Conference

Conference31st International Conference on Software Engineering and Knowledge Engineering, SEKE 2019
Country/TerritoryPortugal
CityLisbon
Period10/07/1912/07/19

Keywords

  • Artificial intelligence
  • Database
  • Genetic algorithms
  • Indexing
  • Learning system

Fingerprint

Dive into the research topics of 'GADIS: A genetic algorithm for database index selection'. Together they form a unique fingerprint.

Cite this