An Improved Smith-Waterman Algorithm Based on Spark Parallelization

Abstract

This paper proposes the design and the implementation of a Spark parallelization plan for improving the Smith-Waterman (SW) algorithm, named the Spark-OSW algorithm. Then, the Spark-OSW was verified through accuracy, performance and acceleration tests. The results show that the proposed algorithm achieved 100% accuracy, ran much faster than the SW, and performed well in cluster environment. The research findings shed important new light on the database search for gene sequences.