By combining enterprise-scale R analytics software with the power of Apache Hadoop and Apache Spark, Microsoft R Server for HDInsight gives you the scale and performance you need. Multi-threaded math libraries and transparent parallelization in R Server handle up to 1000x more data and up to 50x faster speeds than open-source R, which helps you to train more accurate models for better predictions. R Server works with the open-source R language, so all of your R scripts run without changes.
Gives users the familiarity of the R language for machine learning while leveraging the scalability and reliability built into Hadoop and Spark. 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.
What do you dislike?
Beyond the inclusion of Microsoft ML, MRS 9 allows R models to be exposed as Web services, which is the same way Azure Machine Learning works. Microsoft points out that with the help of open source API framework Swagger, the Web service deployment means that models built in R can be used from virtually any programming language and platform.
Furthermore, with MRS 9, Microsoft says models that are trained in one environment can even be moved to, and scored in, other environments, and that new active-active high availability features in MRS 9 mean these models can be scaled for high-demand production use.
What business problems are you solving with the product? What benefits have you realized?
R has traditionally been a tool used by individual statisticians and data scientists, from individual desktop computers, on an ad hoc basis, a server version of R, all by itself, is important. A server version of R allows code written in it to be run centrally
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