Towards Analyzing Computational Costs of Spark for SARS-CoV-2 Sequences Comparisons on a Commercial Cloud

  • Alan L. Nunes UFF
  • Alba Cristina Magalhaes Alves de Melo UnB
  • Cristina Boeres UFF
  • Daniel de Oliveira UFF
  • Lúcia Maria de Assumpção Drummond UFF


In this paper, we developed a Spark application, named Diff Sequences Spark, which compares 540 SARS-CoV-2 sequences from South America in Amazon EC2 Cloud, generating as output the positions where the differences occur. We analyzed the performance of the proposed application on selected memory and storage optimized virtual machines (VMs) at on-demand and spot markets. The execution times and financial costs of the memory optimized VMs outperformed the storage optimized ones. Regarding the markets, Diff Sequences Spark reduced the average execution times and monetary costs when using spot VMs compared to their respective on-demand VMs, even in scenarios with several spot revocations, benefiting from the low overhead fault tolerance Spark framework.


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NUNES, Alan L.; MELO, Alba Cristina Magalhaes Alves de; BOERES, Cristina; OLIVEIRA, Daniel de; DRUMMOND, Lúcia Maria de Assumpção. Towards Analyzing Computational Costs of Spark for SARS-CoV-2 Sequences Comparisons on a Commercial Cloud. In: SIMPÓSIO EM SISTEMAS COMPUTACIONAIS DE ALTO DESEMPENHO (SSCAD), 22. , 2021, Belo Horizonte. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 192-203. DOI: