Microsoft today announced that they have integrated support for Apache Spark into Microsoft R Server for Hadoop, bringing Spark's speed advantages within the reach of R users with on-premises installations.
- Power of Microsoft R on Apache Spark: Combining R Server with Spark gives users the ability to run R functions over thousands of Spark nodes letting you train models on data 1000 times larger. Furthermore, when comparing R Server on a five node Spark cluster to open source R with CRAN algorithms which can only run on a single server, R Server ran GLM 125 times faster on five times the hardware, showing the combined speed of R Server's parallelized algorithms and Spark's in-memory architecture.
- Free R Client for data scientists: To further empower data scientists, we also recently announced Microsoft R Client, a new freely available tool for data scientists to build high performance analytics using R. R Client not only allows you to use any of the open source R functions to analyze the data present on your local workstation, it also enables you to analyze remote big data and scale out the analytics by pushing the computation to a production instance of Microsoft R Server such as SQL Server R Services, R Server for Hadoop and HD Insight with Spark.
Microsoft today also announced that DeployR, a component of Microsoft R Server, has undergone major architecture improvements making it easier to use, with more choices of supported repository databases and more secure than ever with improved Web security features for better protection against malicious attacks, improved installation security, and improved Security Policy Management.
Download Microsoft R Client today. Read more about it from the source link below.
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