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.
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Optimizing queries via search server ElasticSearch: a study applied to large volumes of genomic data
Published: 01 December 2017 by MDPI in MOL2NET'17, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 3rd ed. congress USEDAT-03: USA-EU Data Analysis Training Prog. Work., Cambridge, UK-Bilbao, Spain-Duluth, USA, 2017
Keywords: ElasticSearch, genomic data, databases