EventsMOL2NET'17, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 3rd ed.
Event submissions
Published
with-doi10.3390/mol2net-03-05049
This submission belongs to the session 03. USEDAT-03: USA-EU Data Analysis Training Prog. Work., Cambridge, UK-Bilbao, Spain-Duluth, USA, 2017 of the event MOL2NET'17, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 3rd ed.
Published date
01 Dec, 2017
Citation
Alex Camargo, Diego Rodrigues Mengarda, Vinicius Rosa Seus, Optimizing queries via search server ElasticSearch: a study applied to large volumes of genomic data, in Proceedings of MOL2NET'17, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 3rd ed., 15 January–15 December 2017, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-03-05049
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Optimizing queries via search server ElasticSearch: a study applied to large volumes of genomic data

Alex Camargo 1
Diego Rodrigues Mengarda 2
Vinicius Rosa Seus 3
1. UFPEL
2. UNIPAMPA
3. FURG
Abstract

When it is necessary to analyze large volumes of data, Bioinformatics acts as a multidisciplinary field that integrates knowledge from different areas. Its applicability goes from the analysis of biological data to the construction of tools and methodologies that allow the use of the computer for tasks usually laboratory. This work aims to use the ElasticSearch server to optimize searches on genomic data made publicly available by the UCI Machine Learning Repository. As a case study, the results obtained were compared with the MySQL and PostgreSQL relational databases. With the proposal presented, a gain of more than 90% was achieved through the use of ElasticSearch technology.

Keywords
ElasticSearch
genomic data
databases
Poster
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