DocumentCode
3184698
Title
Enhancing performance of Hadoop and MapReduce for scientific data using NoSQL database
Author
Alshammari, Hamoud ; Bajwa, Hassan ; Jeongkyu Lee
Author_Institution
Dept. of Comput. Sci., Univ. of Bridgeport, Bridgeport, CT, USA
fYear
2015
fDate
1-1 May 2015
Firstpage
1
Lastpage
5
Abstract
Scientific data sets usually have similar jobs that are frequently applied to them by different users. In addition, many of these data sets are unstructured and complex, and required fast and simple processing. In order to increase the performance of the existing Hadoop and MapReduce algorithm, it is necessary to develop an algorithm based on the type of data sets and requirements of the jobs. Genomic and biological data is an example of unstructured data because it only has a huge sequence of unreadable and non-relational letters. In this paper, we present an overview of a developed MapReduce algorithm and its simulation using HBase as a NoSQL database.
Keywords
parallel algorithms; relational databases; HBase; Hadoop algorithm; MapReduce algorithm; NoSQL database; biological data; genomic data; Bioinformatics; Biological cells; Computer architecture; Computer science; DNA; Databases; Genomics; BigData; HBase; Hadoop; MapReduce; NoSQL Database;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Applications and Technology Conference (LISAT), 2015 IEEE Long Island
Conference_Location
Farmingdale, NY
Type
conf
DOI
10.1109/LISAT.2015.7160180
Filename
7160180
Link To Document