There are five ways of using integrate hadoop and R
Rhadoop – Integrate hadoop and R programming language called Rhadoop. It provided by Revolution analytics used for directly insert the data from HDFS systems and Hbase systems. Rhadoop is a collection of five packages for manages the data using R programming language that packages are rhbse, rhdfs, plyrmr, ravro and rmr2
Hadoop Streaming – Hadoop streaming used to runs the MapReduce jobs that give standard output data as mapper or reducer. In this method no need any client side integration because its access data through command line
RHIPE – RHIPE means R and Hadoop Integrated Programming Environment. It allows runs MapReduce jobs within R. In this method programmers write R Maps and R Reduce functions only and RHIPE transfer data to Hadoop MapReduce tasks.
RHIVE(Install R on Workstations and Connect to Data in Hadoop) – Rhive is a statistical libraries which available in R programming. It is used to extending the HiveQl and query language.
ORCH (Oracle Connector for Hadoop) – It can be used to non-oracle hadoop clusters. Mappers and Reducer jobs written in R programming and MapReduce job executed from R. This connector also used to tests the MapReduce jobs.
Conclusion:
Hadoop and R working together is a best tool for big data professionals with high performance and scalability. Hadoop integration with R built for overcome limitations of R programming but if we just ignore it, then R and Hadoop together can make big data analytics an ecstasy!