About Microsoft R Client

Microsoft R Client is a free, community-supported, data science tool for high performance analytics. R Client is built on top of Microsoft R Open so you can use any open source R package to build your analytics. Additionally, R Client introduces the powerful ScaleR technology and its proprietary functions to benefit from parallelization and remote computing.

R Client allows you to work with production data locally using the full set of ScaleR functions, but there are some constraints. On its own, the data to be processed must fit in local memory, and processing is limited up to two threads for RevoScaleR functions. To benefit from disk scalability, performance and speed, you can push the compute context to a production instance of Machine Learning Server (or R Server) such as SQL Server Machine Learning Services and Machine Learning Server for Hadoop. Learn more about its compatibility.

You can offload heavy processing to Machine Learning Server or test your analytics during their development. You by running your code remotely using remoteLogin() or remoteLoginAAD() from the mrsdeploy package.

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Machine Learning Server vs R Client

Machine Learning Server and Microsoft R Client offer virtually identical R packages, but each one targets different scenarios. R Client is intended for data scientists who create solutions that run locally. Machine Learning Server is commercial software that runs on a range of platforms, at much greater scale, with infrastructure for handling major workloads, on client-server topologies that support remote access over authenticated connections.

You can work with R Client standalone. You can also use it with Machine Learning Server, where you learn and develop on R Client, and then migrate your work to Machine Learning Server or execute it remotely on an Machine Learning Server whenever you need the scale, support, and infrastructure of an operationalized server.

Get started with R Client

Getting started with Microsoft R Client is as easy as 1-2-3. Click a step to get started:
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1. Install R Client

The first step is to download Microsoft R Client for your operating system and install it. To learn more about the supported platforms or installation steps, please see the following articles:


2. Configure Your IDE

While R is a command line driven program, you can also use your favorite R integrated development environment (IDE) to interact with Microsoft R Client. To do so, you must point that IDE to the R Client R executable. This way, whenever you execute your R code, you'll do so using R Client and benefit from the proprietary packages installed with R Client. R IDE options include R Tools for Visual Studio on Windows (Recommended), RStudio, or any other R development environment.

  • Set up RTVS for R Client on Windows: R Tools for Visual Studio (RTVS) is an integrated development environment available as a free add-in for any edition of Visual Studio. To make R Client the default R engine for RTVS, choose Change R to Microsoft R Client from the R Tools menu.

  • Set up RStudio for R Client on Windows or Linux: RStudio is another popular R IDE. To make R Client the default R engine for RStudio, update the path to R. For example, point to C:\Program Files\Microsoft\R Client\R_SERVER\bin\x64 on Windows.

After you configure the IDE, a message appears in the console signaling that the Microsoft R Client packages were loaded.

Important

You can connect remotely from your local IDE to an Machine Learning Server instance using functions from the mrsdeploy package. Then, the R code you enter at the remote command line executes on the remote server. This is very convenient when you need to offload heavy processing on server or to test your analytics during their development. Your Machine Learning Server administrator must configure Machine Learning Server for this functionality.


3. Try Out R Client

Now that you've installed R Client, you can start building and running some R code. Launch R on the command line or in your IDE and:

When ready, you can run that R code using R Client or even send those R commands to a remote Machine Learning Server for execution if Machine Learning Server is also installed in your organization.

What's new in Microsoft R Client

Microsoft R Client 3.4.1

This release of R Client, built on open source R 3.4.1. Download R Client from http://aka.ms/rclient (Windows) or http://aka.ms/rclientlinux (Linux).

Several of the packages installed have been updated. Learn more about here.

Microsoft R Client 3.3.3

This release of R Client, built on open source R 3.3.3. Key release features include:

  • Installations on Linux are now possible for R Client

  • Several of the packages installed have been updated. Learn more about here.

Microsoft R Client 3.3.2

The following release notes apply to Microsoft R Client, which can be downloaded from http://aka.ms/rclient/download.

  • New enhanced Microsoft R Client Getting Started guide
  • A new 'version check' and auto-update is now possible using CheckForUpdates() in your R Console
  • Offline installations are now possible for R Client
  • New packages now bundled with Microsoft R Client (and Microsoft R Open):

    • mrsdeploy - adds remote execution and web service deployment from R Client 3.3.2 to a remote R Server 9.0.1 instance
    • MicrosoftML - adds machine learning algorithms to R script that executes on either R Client or R Server
    • olapR- adds MDX query support through connections to OLAP cubes on a SQL Server 2016 Analysis Services instance
    • and the packages bundled with Microsoft R Open 3.3.2

    Learn more about the new and updated packages in this release.

  • Updated end-user license agreement
  • Telemetry collection is now enabled. Learn more about this feature and how to turn it off.

Learn More

You can learn more with these guides: