Semnan University International Journal of Nonlinear Analysis and Applications 2008-6822 12 Special Issue 2021 12 01 DNA barcoding using particle swarm optimization on apache spark SQL case study: DNA of covid-19 1561 1572 5812 10.22075/ijnaa.2021.5812 EN Lala Septem Riza Department of Computer Science Education, Universitas Pendidikan Indonesia, Indonesia Muhammad Ilham Nurfathiya Department of Computer Science Education, Universitas Pendidikan Indonesia, Indonesia Jajang Kusnendar Department of Computer Science Education, Universitas Pendidikan Indonesia, Indonesia Khyrina Airin Fariza Abu Samah Faculty of Computer and Mathematical Sciences, University Teknologi MARA Cawangan Melaka Kampus Jasin, Melaka, Malaysia Journal Article 2021 08 16 The objective of this research is to design and implement a computational model to determine DNA barcodes by utilizing the Particle Swarm Optimization (PSO) algorithms implemented on Big Data Platforms, namely Apache Hadoop and Apache Spark. The steps are as follows: (i) inputting DNA sequences to Hadoop Distributed File System (HDFS) in Apache Hadoop, (ii) pre-processing data, (iii) implementing PSO by utilizing the User Defined Function (UDF) in Apache Spark, (iv) collecting results and saving to HDFS. After obtaining the computational model, two following simulations have been done: the first scenario is using 4 cores and several worker nodes, meanwhile, the second one consists of a cluster with 2 worker nodes and several cores. In terms of computational time, the results show a significant acceleration between standalone and big data platforms with both experimental scenarios. This study proves that the computational model built on the big data platform shows the development of features and acceleration of previous research. https://ijnaa.semnan.ac.ir/article_5812_4bcaa895a499d080c10a0fb495eadacd.pdf