Programming with Big Data in R: Difference between revisions

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| website = {{URL|www.r-pbd.org}}

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'''Programming with Big Data in R''' (pbdR)<ref>{{cite web|author=Ostrouchov, G., Chen, W.-C., Schmidt, D., Patel, P.|title=Programming with Big Data in R|year=2012|url=http://r-pbd.org}}</ref> is a series of [[R (programming language)|R]] packages and an environment for [[statistical computing]] with [[Big Data]] by using high-performance statistical computation.<ref>{{cite web|authorauthor1=Chen, W.-C. and |author2=Ostrouchov, G. |lastauthoramp=yes |url=http://thirteen-01.stat.iastate.edu/snoweye/hpsc/|year=2011|title=HPSC -- High Performance Statistical Computing for Data Intensive Research}}</ref> The pbdR uses the same programming language as R with [[S (programming language)|S3/S4]] classes and methods which is used among [[statistician]]s and [[Data mining|data miners]] for developing [[statistical software]]. The significant difference between pbdR and R code is that pbdR mainly focuses on [[distributed memory]] systems, where data are distributed across several processors and analyzed in a [[Batch processing|batch mode]], while communications between processors are based on [[Message Passing Interface|MPI]] that is easily used in large [[High-performance computing|high-performance computing (HPC)]] systems. R system mainly focuses{{Citation needed|date=July 2013}} on single [[Multi-core processor|multi-core]] machines for data analysis via an interactive mode such as [[Graphical user interface|GUI interface]].

Two main implementations in [[R (programming language)|R]] using [[Message Passing Interface|MPI]] are Rmpi<ref name=rmpi>{{cite journal|author=Yu, H.|title=Rmpi: Parallel Statistical Computing in R|year=2002|url=http://cran.r-project.org/package=Rmpi|journal=R News}}</ref> and pbdMPI of pbdR.