Microsoft Announces the Availability of R Server Inside Azure HDInsight

The availability of R server inside the Azure HDInsight will leverage Hadoop and Spark and provide the most comprehensive set of statistical functions and ML algorithms in the cloud.

MicrosoftGreatResponder.com  At Strata, and Hadoop World, the company made this announcement that is apparently hopeful to take advantage of on the increasing development of open source technologies. Microsoft R is now 100 percent friendly with Open Source R and any library that exists can be used in the R Server framework.

Microsoft attained Revolution Analytics in early in 2015 as a way of entering into the R-based analytics market, and has since that time distributed SQL Server R Services on SQL Server 2016 CTP3. R is one of the most accepted programming languages that assist millions of data scientists resolve the majority of difficult troubles in different fields like computational biology to quantitative marketing.

R Server for Azure HDInsight is a level out the execution of R integrated with Hadoop and Spark clusters created from HDInsight. It is the only 100 percent open source R implementation that runs in the cloud on Hadoop and Spark.

“By making R Server available as a workload inside HDInsight, we remove obstacles for users to unlock the power of R by eliminating memory and processing constraints and extending analytics from the laptop to large multi-node Hadoop and Spark clusters,” said Oliver Chiu, Product Marketing, Hadoop/Big Data and Data Warehousing at Microsoft.

The organization stated that by making the R Server accessible as a workload inside HDInsight, it will eliminate memory and processing limitation, permitting developers to improved employment of the power of Hadoop and Spark clusters. Organizations will be capable to run machine learning models on large data sets, escalating the correctness of business predication that is made by the copy.

“This gives you the familiarity of the R language for machine learning while leveraging the scalability and reliability built into Hadoop and Spark,” said Chiu. “It also eliminates memory and processing constraints and easily extends their code from their laptop to large multi-terabyte files producing models that are more powerful and accurate.”

Microsoft R is not only well-matched with Open Source R and any all the libraries used in the R Server context. In addition, R server can influence the power of Hadoop to parallel any on hand R function to numerous nodes, letting you employ your existing information and system investments.