Cargando…
CloudDOE: A User-Friendly Tool for Deploying Hadoop Clouds and Analyzing High-Throughput Sequencing Data with MapReduce
BACKGROUND: Explosive growth of next-generation sequencing data has resulted in ultra-large-scale data sets and ensuing computational problems. Cloud computing provides an on-demand and scalable environment for large-scale data analysis. Using a MapReduce framework, data and workload can be distribu...
Autores principales: | Chung, Wei-Chun, Chen, Chien-Chih, Ho, Jan-Ming, Lin, Chung-Yen, Hsu, Wen-Lian, Wang, Yu-Chun, Lee, D. T., Lai, Feipei, Huang, Chih-Wei, Chang, Yu-Jung |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4045712/ https://www.ncbi.nlm.nih.gov/pubmed/24897343 http://dx.doi.org/10.1371/journal.pone.0098146 |
Ejemplares similares
-
Moving Hadoop to the cloud: harnessing cloud features and flexibility for Hadoop Clusters
por: Havanki, Bill
Publicado: (2017) -
Optimizing Hadoop for MapReduce: learn how to configure your Hadoop cluster to run optimal MapReduce jobs
por: Tannir, Khaled
Publicado: (2014) -
Hadoop MapReduce v2 cookbook
por: Gunarathne, Thilina
Publicado: (2015) -
cl-dash: rapid configuration and deployment of Hadoop clusters for bioinformatics research in the cloud
por: Hodor, Paul, et al.
Publicado: (2016) -
Apache Hadoop YARN: moving beyond MapReduce and batch processing with Apache Hadoop 2
por: Murthy, Arun
Publicado: (2014)