Hadoop cluster deployment: A methodological approach
MetadataShow full item record
For a long time, data has been treated as a general problem because it just represents fractions of an event without any relevant purpose. However, the last decade has been just about information and how to get it. Seeking meaning in data and trying to solve scalability problems, many frameworks have been developed to improve data storage and its analysis. As a framework, Hadoop was presented as a powerful tool to deal with large amounts of data. However, it still causes doubts about how to deal with its deployment and if there is any reliable method to compare the performance of distinct Hadoop clusters. This paper presents a methodology based on benchmark analysis to guide the Hadoop cluster deployment. The experiments employed The Apache Hadoop and the Hadoop distributions of Cloudera, Hortonworks, and MapR, analyzing the architectures on local and on clouding-using centralized and geographically distributed servers. The results show the methodology can be dynamically applied on a reliable comparison among different architectures. Additionally, the study suggests that the knowledge acquired can be used to improve the data analysis process by understanding the Hadoop architecture.
How to cite this document
Showing items related by title, author, creator and subject.
Pinho, Sheila Zambello de ; Oliveira, José Brás Barreto de ; Gazola, Rodrigo José Cristiano ; Mazotti, Adriano César ; Molero, Camila Schimite ; Mendes, Carolina Borghi ; Mello, Denise Fernandes de ; Marques, Emilia de Mendonça Rosa ; Talamoni, Jandira Liria Biscalquini ; Silva, José Humberto Dias da et al. (Coleção PROGRAD (UNESP), 2011) [Livro]
Pinho, Sheila Zambello de ; Oliveira, José Brás Barreto de ; Pontes, Sueli Rodrigues ; Almeida, Djanira Soares de Oliveira e ; Godoy, Kathya Maria Ayres de ; Rosa, Claudia de Souza ; Nunes, Julianus Araújo ; Salvador, Sérgio Azevedo ; David, Célia Maria ; Vilche Peña, Angel Fidel et al. (Coleção PROGRAD (UNESP), 2011) [Livro]
Pinho, Sheila Zambello de ; Spazziani, Maria de Lourdes ; Mendonça, Sueli Guadelupe de Lima ; Rubo, Elisabete Aparecida Andrello ; Villarreal, Dalva Maria de Oliveira ; Duarte, Camila ; Okamoto, Mary Yoko ; Souza, Thais R. ; Garms, Gilza Maria Zauhy ; Marin, Fátima Aparecida Dias Gomes et al. (Coleção PROGRAD (UNESP), 2012) [Livro]