MIRI Infotech presents Predictive analytics framework environment in R, Java, and Hadoop with specially optimized R version 3.3.3 (2017-03-06) with Ubuntu 16.04 OS. This framework includes RStudio Version 0.98.1091 & RServer 1.0.36 and Hadoop 2.7.3 with HDFS, HBase Version 1.3.0.

Miri Infotech has launched a product that will configure and publish Predictive Analytics Framework with R & Java and Hadoop, to a wide variety of statistical (linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering) and graphical techniques which is embedded pre-configured tool with Ubuntu 16.04 and ready-to-launch AMI on Alibaba Cloud that contains Hadoop, R, RStudio, HDFS, Hbase and Shiny server.

R is a language and environment for graphics and statistical computing and a popular tool for statistics and data analysis. It provides a wide variation of statistical (classical statistical tests, classification, linear and nonlinear modeling, clustering, time-series analysis) and graphical techniques, along with being is highly extensible. R has rich visualization capabilities and a large collection of libraries that have been developed and maintained by the R developer community. The skills of R are extended to user-created packages that allows for specialized statistical techniques, graphical devices to be used. All this makes it simple to write and execute R programs that operate on the data stored in a Hadoop cluster.

A core set of package is included with the installation of R, with more than 10,331 additional packages.

The following is a list of other open source components (full copies of the license agreements used by these components are included below):

• Qt (LGPL v2.1)
• QtSingleApplication
• Ace (LGPL v2.1)
• Boost
• RapidXml
• JSON Spirit
• Google Web Toolkit
• Guice
• GIN
• AOP Alliance
• RSA-JS
• tree.hh
• Hunspell (MPL)
• Chromium Hunspell Dictionaries (MPL)
• pdf.js
• SyncTeX
• ZLib
• Sundown
• highlight.js
• MathJax
• reveal.js
• node-webkit
• JSCustomBadge

RStudio Server allows you to provide a browser-based interface (the RStudio IDE) to a version of R running on a remote Linux server. Deploying R and RStudio on a server has numerous benefits, including:

• The ability to access R workspace from any computer in any location
• It provides centralized configuration and installation of R, R packages, TeX, and other supporting libraries
• Allows for sharing of code, data, and other files with colleagues
• Enabling multiple users to share access to the more powerful computer resources (memory, processors, etc.) available on the server

Simply put, R Server is scalable data analytics server, which can be deployed as a single-user workstation, a local network of connected servers, or on a Hadoop cluster in the cloud. On Hadoop, R Server requires MapReduce, Hadoop Distributed File System (HDFS), and YARN.

For more info- https://www.cloud.miritech.com/Alibaba%20Cloud/predictive-analytics-framework-r-hadoop.aspx