R Server 9.1 Installation for Linux Systems

Artikel
04/28/2017

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Microsoft R Server is an enterprise class server for hosting and managing parallel and distributed workloads of R processes on servers and clusters. The server runs on a wide range of computing platforms, including Linux.

This article explains how to install Microsoft R Server 9.1.0 on a standalone Linux server that has an internet connection. If your server has restrictions on internet access, see the instructions for an offline installation.

If you previously installed version 9.0.1, it will be replaced with the 9.1.0 version. An 8.x version can run side-by-side 9.x, unaffected by the new installation.

System requirements

Operating system must be a supported version of Linux on a 64-bit with x86-compatible architecture (variously known as AMD64, Intel64, x86-64, IA-32e, EM64T, or x64 chips). Itanium chips (also known as IA-64) are not supported. Multiple-core chips are recommended.
Memory must be a minimum of 2 GB of RAM is required; 8 GB or more are recommended.
Disk space must be a minimum of 500 MB.
An internet connection. If you do not have an internet connection, for the instructions for an offline installation.
A package manager (yum for RHEL systems, apt for Ubuntu, zypper for SLES systems)
Root or super user permissions

The following additional components are included in Setup and required for R Server.

Microsoft R Open 3.3.3
Microsoft .NET Core 1.1 for Linux (required for mrsdeploy and MicrosoftML use cases)

How to install

This section walks you through an R Server 9.1.0 deployment using the install.sh script. Under these instructions, your installation will be serviced under the Modern Lifecycle policy and includes the ability to operationalize your analytics and use the MicrosoftML package.

Tip

Review recommendations and best practices for deployments in locked down environments.

Download R Server installer

You can get the gzipped installation file from one of the following download sites.

Site	Edition	Details
Visual Studio Dev Essentials	Developer (free)	This option provides a zipped file, free when you sign up for Visual Studio Dev Essentials. Developer edition has the same features as Enterprise, except it is licensed for development scenarios.
Volume Licensing Service Center (VLSC)	Enterprise	Sign in, search for R Server for Linux. A selection for R Server 9.1.0 for Linux is provided on this site.

For downloads from Visual Studio Dev Essentials:

Click Join or access now to sign up for download benefits.
Check the URL to verify it changed to https://my.visualstudio.com/.
Click Downloads to search for R Server.
Click Downloads for a specific version to select the platform.

Download page on Visual Studio benefits page

Unpack the distribution

Download the software to a writable directory, such as /tmp, unpack the distribution and then run the installation script.

The distribution includes one installer for Microsoft R Server. For a gzipped TAR file, you should unpack the file as follows (be sure you have downloaded the file to a writable directory, such as /tmp):

Log in as root or a user with super user privileges (sudo su).
Switch to the /tmp directory (assuming it's the download location).
Unpack the file:

[tmp] $ tar zxvf en_microsoft_r_server_910_for_linux_x64_10323878.tar.gz

The distribution is unpacked into an MRS91Linux folder at the download location. The distribution includes the following files:

File	Description
`install.sh`	Script for installing R Server.
`generate_mrs_parcel.sh`	Script for generating a parcel used for installing R Server on CDH.
`EULA.txt`	End user license agreements for each separately licensed component.
DEB folder	Contains Microsoft R packages for deployment on Ubuntu.
RPM folder	Contains Microsoft R packages for deployment on CentOS/RHEL and SUSE.
Parcel folder	Contains files used to generate a parcel for installation on CDH.

MRS packages include an admin utility, core engine and function libraries, compute node and web node configuration options, platform packages, and machine learning.

Important

Package names in the R Server distribution have changed in the 9.1 release. Instead of DeployrR-themed package names, the new names are aligned to base packages. If you have script or tooling for manual R Server package installation, be sure to note the name change.

Run the MRS install script

R Server for Linux is deployed by running the install script with no parameters.

Log in as root or as a user with super user privileges (sudo -s). The following instructions assume root install.
Clean cached data so that the installer can get updated packages.
- On RHEL use yum: [root@localhost tmp] $ yum expire-cache
- On Ubuntu use apt-get: [root@localhost tmp] $ apt-get autoclean
Change to the MRS91Linux directory containing the installation script:

[root@localhost tmp] $ cd /tmp/MRS91Linux
Run the script. To include the pre-trained machine learning models for MicrosoftML, append the -m switch.

[root@localhost MRS91Linux] $ bash install.sh -m
When prompted to accept the license terms for Microsoft R Open, click Enter to read the EULA, click q when you are finished reading, and then click y to accept the terms.
Repeat for the R Server license agreement: click Enter, click q when finished reading, click y to accept the terms.

Installation begins immediately. Installer output shows the packages and location of the log file.

Verify installation

List installed MRS packages:
- On RHEL: rpm -qa | grep microsoft
- On Ubuntu: apt list --installed | grep microsoft
Once you have a package name, you can obtain verbose version information. For example:
- On RHEL: $ rpm -qi microsoft-r-server-packages-9.1.x86_64
- On Ubuntu: $ dpkg --status microsoft-r-server-packages-9.1.x86_64

Partial output is as follows (note version 9.1.0):

	  Name        : microsoft-r-server-packages-9.1     Relocations: /usr/lib64
	  Version     : 9.1.0                               Vendor: Microsoft
	  . . .

Start Revo64

As another verification step, run the Revo64 program. By default, Revo64 is linked to the /usr/bin directory, available to any user who can log in to the machine:

From /Home or any other working directory:

[<path>] $ Revo64
Run a RevoScaleR function, such as rxSummary on a dataset. Many sample datasets, such as the iris dataset, are ready to use because they are installed with the software:

> rxSummary(~., iris)

Output from the iris dataset should look similar to the following:

        Rows Read: 150, Total Rows Processed: 150, Total Chunk Time: 0.001 seconds
        Computation time: 0.005 seconds.
        Call:
        rxSummary(formula = ~., data = iris)

        Summary Statistics Results for: ~.
        Data: iris
        Number of valid observations: 150

         Name         Mean     StdDev    Min Max ValidObs MissingObs
         Sepal.Length 5.843333 0.8280661 4.3 7.9 150      0
         Sepal.Width  3.057333 0.4358663 2.0 4.4 150      0
         Petal.Length 3.758000 1.7652982 1.0 6.9 150      0
         Petal.Width  1.199333 0.7622377 0.1 2.5 150      0

        Category Counts for Species
        Number of categories: 3
        Number of valid observations: 150
        Number of missing observations: 0

         Species    Counts
         setosa     50
         versicolor 50
         virginica  50

To quit the program, type q() at the command line with no arguments.

Enable Remote Connections and Analytic Deployment

The server can be used as-is if you install and use an R IDE on the same box, but to benefit from the deployment and consumption of web services with Microsoft R Server, then you must configure R Server after installation to act as a deployment server and host analytic web services. Possible configurations are a one-box setup or an enterprise setup. Doing so also enables remote execution, allowing you to connect to R Server from an R Client workstation and execute code on the server.

Unattended install options

You can perform a silent install to bypass prompts during setup. In /tmp/MRS91Linux, run the install script with the following parameters:

[root@localhost MRS91Linux] $ install.sh -a -s

Additional flags are available, as follows:

flag	Option	Description
-a	--accept-eula	Accept all end user license agreements.
-d	--download-mro	Download microsoft r open for distribution to an offline system.
-m	--models	Install Microsoft ML models.
-r	--no-dotnet-core	Opt out of installing .NET Core (required for mrsdeploy and MicrosoftML)
-s	--silent	Perform a silent, unattended install.
-u	--unattended	Perform an unattended install.
-h	--help	Print this help text.

What's Installed with R Server

The Microsoft R Server setup installs the R base packages and a set of enhanced and proprietary R packages that support parallel processing, improved performance, and connectivity to data sources including SQL Server and Hadoop. In contrast with R Client, R Server supports much larger data sets and distributed workloads.

Note

By default, telemetry data is collected during your usage of R Server. To turn this feature off, use the RevoScaleR package function rxPrivacyControl(FALSE). To turn it back on, change the setting to TRUE.

Next Steps

Review the best practices in Manage your R Server for Linux installation for instructions on how to set up a local package repository using MRAN or miniCRAN, change file ownership or permissions, set Revo64 as the de facto R script engine on your server.

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