A Blast implementation in Hadoop MapReduce using low cost commodity hardware
Khawla Tadist, Fatiha Mrabti, Zahi Azeddine, Saïd Najah · Procedia Computer Science · 2018
It is a known fact that health in all its kinds is the key to a successful society. The medical field is nowadays generating huge flows of data that need urgent, fast analyzing, and processing. A complete analysis of a patient’s personal file is now a must in order to understand the different diseases and thus be able to find cures. Due to the amount of generated medical Data that is going out of hand, a desperate need to new Big Data technologies has manifested itself. In this paper, we offer an implementation of the Blast (Basic local alignment tool) algorithm in Hadoop MapReduce using low commodity hardware to prove the ability of Big Data technologies to work on the medical field even with low budgets.