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You're reading from  Learning Bayesian Models with R

Product typeBook
Published inOct 2015
Reading LevelBeginner
PublisherPackt
ISBN-139781783987603
Edition1st Edition
Languages
R
Concepts
Machine Learning
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Author (1)
Hari Manassery Koduvely
Hari Manassery Koduvely
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Hari Manassery Koduvely

Dr. Hari M. Koduvely is an experienced data scientist working at the Samsung R&D Institute in Bangalore, India. He has a PhD in statistical physics from the Tata Institute of Fundamental Research, Mumbai, India, and post-doctoral experience from the Weizmann Institute, Israel, and Georgia Tech, USA. Prior to joining Samsung, the author has worked for Amazon and Infosys Technologies, developing machine learning-based applications for their products and platforms. He also has several publications on Bayesian inference and its applications in areas such as recommendation systems and predictive health monitoring. His current interest is in developing large-scale machine learning methods, particularly for natural language understanding.
Read more about Hari Manassery Koduvely

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SparkR

Similar to RHadoop, SparkR is an R package that allows R users to use Spark APIs through the RDD class. For example, using SparkR, users can run jobs on Spark from RStudio. SparkR can be evoked from RStudio. To enable this, include the following lines in your .Rprofile file that R uses at startup to initialize the environments:

Sys.setenv(SPARK_HOME/.../spark-1.5.0-bin-hadoop2.6")
#provide the correct path where spark downloaded folder is kept for SPARK_HOME 
.libPaths(c(file.path(Sys.getenv("SPARK_HOME"),""R",""lib"),".libPaths()))

Once this is done, start RStudio and enter the following commands to start using SparkR:

>library(SparkR)
>sc <- sparkR.init(master="local")

As mentioned, as of the latest version 1.5 when this chapter is in writing, SparkR supports limited functionalities of R. This mainly includes data slicing and dicing and summary stat functions. The current version does not support the use of contributed R packages; however, it is planned for a future release...

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Learning Bayesian Models with R
Published in: Oct 2015Publisher: PacktISBN-13: 9781783987603
© 2015 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Hari Manassery Koduvely

Dr. Hari M. Koduvely is an experienced data scientist working at the Samsung R&D Institute in Bangalore, India. He has a PhD in statistical physics from the Tata Institute of Fundamental Research, Mumbai, India, and post-doctoral experience from the Weizmann Institute, Israel, and Georgia Tech, USA. Prior to joining Samsung, the author has worked for Amazon and Infosys Technologies, developing machine learning-based applications for their products and platforms. He also has several publications on Bayesian inference and its applications in areas such as recommendation systems and predictive health monitoring. His current interest is in developing large-scale machine learning methods, particularly for natural language understanding.
Read more about Hari Manassery Koduvely

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