RHadoop

Combination of R and Hadoop

R Packages for Hadoop -RHadoop, RHIPE

R Packages for Spark -SparkR

R Packages forH2O -h2o

R Packages forMongoDB -rmongodb,Rmongo

Major advantage of using R with Hadoop is "Elastic data analytics platform"

Big Data Platform (Hadoop) + Data Analytics (R) = Big data Analytics (RHadoop)

rhdfs - R and HDFS connector

rmr -R interface for calling Hadoop MapReduce API

rhbase - R and HBase connector

Available on github

Steps to install RHadoop in your PC:

installing R

Installing Hadoop

Installing R packages

configuring environment

installing RhHadoop (rmr,rhdfs,rhbase)

library('rhdfs')

library('rmr2')

initialization

Hdfs operations

hdfs.init()

hdfs.defaults()

file manipulation

hdfs.put()

hdfs.copy()

hdfs.write()

hdfs.read()

hdfs.rm()

hdfs.ls()

RMR opretaions

to.dfs()

from.dfs()

mapreduce(input,output,map,reduce,combine,input.format,output.format,verbose)

keyval(key,val)

Example: Word Count script in R (Wordcount.R)

wordcount=function(input,output = NULL,pattern = " ") #pattern represents delimiter

{

wcmap=function(k,lines) { #Mapper function

keyval(unlist(strsplit(x = lines,split = pattern)),1)}

wcreduce=function(word,counts) { #Reducer function

keyval(word,sum(counts))}

mapreduce(input=input,output=output,input.format="text",map=wcmap,reduce=wcreduce)

}

wordcount('<inputfilelpath>')

from.dfs("<tmp_file_location>") #Checking the wordcount output

source("./Wordcount.R")

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