Hadoop Performance Analysis on Raspberry Pi for DNA Sequence Alignment
Abstract: The rapid
development of electronic data has brought two major challenges, namely, how to
store big data and how to process it. Two main problems in processing big data
are the high cost and the computational power. Hadoop, one of the open source
frameworks for processing big data, uses distributed computational model
designed to be able to run on commodity hardware. The aim of this research is
to analyze Hadoop cluster on Raspberry Pi as a commodity hardware for DNA
sequence alignment. Six B Model Raspberry Pi and a Biodoop library were used in
this research for DNA sequence alignment. The length of the DNA used in this
research is between 5,639 bp and 13,271 bp. The results showed that the Hadoop
cluster was running on the Raspberry Pi with the average usage of processor 73.08%,
334.69 MB of memory and 19.89 minutes of job time completion. The distribution
of Hadoop data file blocks was found to reduce processor usage as much as
24.14% and memory usage as much as 8.49%. However, this increased job
processing time as much as 31.53%.
Author: Jaya Sena Turana, Heru
Sukoco, Wisnu Ananta Kusuma
Jurnal Code: jptkomputergg160169
