Install Machine Learning Server (Standalone) or R Server (Standalone)

SQL Server setup includes the option to install a machine learning server that runs outside of SQL Server. This option might be useful if you need to develop high-performance machine learning solutions that can use remote compute contexts, or that can be deployed to multiple platforms, including:

  • An instance of SQL Server 2016 or SQL Server 2017 where machine learning is enabled
  • An instance of R Server or Machine Learning Server in a Hadoop or Spark cluster
  • R Server or Machine Learning Server in Linux

This article describes how to use SQL Server setup to install the standalone version of Machine Learning Server or Microsoft R Server. If you have an Enterprise Edition or Software Assurance, installing the standalone machine learning server is free.

Install Machine Learning Server (Standalone)

This feature requires an Enterprise license or equivalent for SQL Server 2017.

If you have installed a previous version of Microsoft R Server, we recommend that you uninstall it first.

If the computer does not have Internet access, you should download the component installers in advance. For more information, see Installing machine learning components without internet access.

  1. Run SQL Server 2017 setup.

  2. Click the Installation tab, and select New Machine Learning Server (Standalone) installation.

    Install Machine Learning Server Standalone

  3. After the rules check is complete, accept SQL Server licensing terms, and select a new installation.

  4. On the Feature Selection page, the following options should already be selected:

    • Microsoft Machine Learning Server (Standalone)

    • R and Python are both selected by default. You can deselect either language, but we recommend that you install at least one of the supported languages.

      Install Machine Learning Server Standalone

      All other options should be ignored.

      Note

      Avoid installing the Shared Features if the computer already has Machine Learning Services installed for SQL Server in-database analytics. This creates duplicate libraries.

      Also, whereas R or Python scripts running in SQL Server are managed by SQL Server so as not to conflict with memory used by other database engine services, the standalone machine learning server has no such constraints, and can interfere with other database operations. Finally, remote access via RDP session, which is often used for operationalization, is typically blocked by database administrators.

      For these reasons, we generally recommend that you install Machine Learning Server (Standalone) on a separate computer from SQL Server Machine Learning Services.

  5. Accept the license terms for downloading and installing the machine learning components. If you install both languages, a separate licensing agreement is required for Microsoft R and for Python.

    Python license agreement

    Installation of these components, and any prerequisites they might require, might take a while. When the Accept button becomes unavailable, you can click Next.

  6. On the Ready to Install page, verify your selections, and click Install.

For more information about automated or off-line installation, see Install Microsoft R Server from the command line.

Install Microsoft R Server (Standalone)

This feature requires an Enterprise license or equivalent for SQL Server 2016.

If you have installed any previous version of the Revolution Analytics tools or packages, you must uninstall them first. See Upgrading from an older version of Microsoft R Server.

  1. Run SQL Server 2016 setup. We recommend that you install Service Pack 1 or later.

  2. On the Installation tab, click New R Server (Standalone) installation.

    Start setup of R Server Standalone

  3. On the Feature Selection page, the following option should be already selected:

    R Server (Standalone)

    Feature selections for R Server Standalone

    All other options can be ignored.

    Note

    Avoid installing the Shared Features if you are running setup on a computer where R Services has already been installed for SQL Server in-database analytics. This creates duplicate libraries.

    Whereas R scripts running in SQL Server are managed by SQL Server so as not to conflict with memory used by other database engine services, the standalone R Server has no such constraints, and can interfere with other database operations.

    We generally recommend that you install Machine Learning Server (Standalone) on a separate computer from SQL Server Machine Learning Services.

  4. Accept the license terms for downloading and installing Microsoft R Open. When the Accept button becomes unavailable, you can click Next.

    Installation of these components, and any prerequisites they might require, might take a while.

  5. On the Ready to Install page, verify your selections, and click Install.

Upgrade an existing instance of R Server

If you installed an earlier version of Microsoft R Server (Standalone), you can upgrade the instance to use newer versions of the R components. The upgrade also changes the support policy to use the Modern Software Lifecycle Support policy. This allows the instance to be updated more frequently, on a different schedule than the SQL Server releases.

  1. Download the separate Windows-based installer from the locations listed here:

  2. Run the installer and follow the instructions. On the page where you select the features to install, select each instance of R Server that you want to upgrade.

Installation tips and follow-up

This section provides additional information related to setup.

Which version should I install?

  • Microsoft R Server was first offered as a part of SQL Server 2016 and supports the R language. The last version of Microsoft R Server was 9.0.1.

  • Microsoft Machine Learning Server is the latest version, which was released with SQL Server 2017 and features many updates, including support for Python. Cumulative Update 1 for SQL Server 2017 has been released, which includes version 9.2.1.24 of Machine Learning Server. We recommend this update if you want the latest Python APIs.

  • Upgrading in place: Setup requires a SQL Server license and upgrades are typically aligned with the SQL Server release cadence. This ensures that your development tools are in synch with the version running in the SQL Server compute context. However, you can use the separate Windows-based installer to get more frequent updates, under the Modern Software Lifecycle support policy. You can also use this installer to upgrade an instance of SQL Server 2016 or SQL Server 2017.

Default installation folders

When you install R Server or Machine Learning Server using SQL Server setup, the R libraries are installed in a folder associated with the SQL Server version that you used for setup. In this folder, you will also find sample data, documentation for the R base packages, and documentation of the R tools and runtime.

However, if you install using the separate Windows installer, or if you upgrade using the separate Windows installer, the R libraries are installed in a different folder.

Just for reference, if you have installed an instance of SQL Server with R Services (In-Database) or Machine Learning Services (In-Database), and that instance is on the same computer, the R libraries and tools are installed by default in a different folder.

The following table lists the paths for each installation.

Version Installation method Default folder
R Server (Standalone) SQL Server 2016 setup wizard C:\Program Files\Microsoft SQL Server\130\R_SERVER
R Server (Standalone) Windows standalone installer C:\Program Files\Microsoft\R Server\R_SERVER
Machine Learning Server (Standalone) SQL Server 2017 setup wizard C:\Program Files\Microsoft SQL Server\140\R_SERVER
Machine Learning Server (Standalone) Windows standalone installer C:\Program Files\Microsoft\R Server\R_SERVER
R Services (In-Database) SQL Server 2016 setup wizard C:\Program Files\Microsoft SQL Server\MSSQL13.<instance_name>\R_SERVICES
Machine Learning Services (In-Database) SQL Server 2017 setup wizard C:\Program Files\Microsoft SQL Server\MSSQL14.<instance_name>\R_SERVICES or C:\Program Files\Microsoft SQL Server\MSSQL14.<instance_name>\PYTHON_SERVICES

Development tools

A development IDE is not installed as part of setup. Additional tools are not required, as all the standard tools are included that would be provided with a distribution of R or Python.

We recommend that you try the new release of R Tools for Visual Studio. Visual Studio supports both R and Python, as well as database development tools, connectivity with SQL Server, and BI tools. However, you can use any preferred development environment, including RStudio.

Troubleshooting

This section lists some common issues to be aware of when installing Machine Learning Server or R Server.

Incompatible version of R Client and R Server

If you install Microsoft R Client and use it to run R in a remote SQL Server compute context, you might get an error like this:

You are running version 9.0.0 of Microsoft R client on your computer, which is incompatible with the Microsoft R Server version 8.0.3. Download and install a compatible version.

In SQL Server 2016, it was required that the version of R that was running in SQL Server R Services be exactly the same as the libraries in Microsoft R Client. That requirement has been removed in later versions. However, we recommend that you always get the latest versions of the machine learning components, and install all service packs.

If you have an earlier version of Microsoft R Server and need to ensure compatibility with Microsoft R Client 9.0.0, install the updates that are described in this support article.

Installing Microsoft R Server on an instance of SQL Server installed on Windows Core

In the RTM version of SQL Server 2016, there was a known issue when adding Microsoft R Server to an instance on Windows Server Core edition. This has been fixed.

If you encounter this issue, you can apply the fix described in KB3164398 to add the R feature to the existing instance on Windows Server Core. For more information, see Can't install Microsoft R Server Standalone on a Windows Server Core operating system.

Upgrading from an older version of Microsoft R Server

If you installed a pre-release version of Microsoft R Server, you must uninstall it before you can upgrade to a newer version.

To uninstall R Server (Standalone)

  1. In Control Panel, click Add/Remove Programs, and select Microsoft SQL Server 2016 <version number>.

  2. In the dialog box with options to Add, Repair, or Remove components, select Remove.

  3. On the Select Features page, under Shared Features, select R Server (Standalone). Click Next, and then click Finish to uninstall just the selected components.

Installation fails with error "Only one Revolution Enterprise product can be installed at a time."

You might encounter this error if you have an older installation of the Revolution Analytics products, or a pre-release version of SQL Server R Services. You must uninstall any previous versions before you can install a newer version of Microsoft R Server. Side-by-side installation with other versions of the Revolution Enterprise tools is not supported.

However, side-by-side installs are supported when using R Server Standalone with SQL Server 2017 or SQL Server 2016.

Unable to uninstall older components

If you have problems removing an older version, you might need to edit the registry to remove related keys.

Important

This issue applies only if you installed a pre-release version of Microsoft R Server or a CTP version of SQL Server 2016 R Services.

  1. Open the Windows Registry, and locate this key: HKLM\Software\Microsoft\Windows\CurrentVersion\Uninstall.
  2. Delete any of the following entries if present, and if the key contains only the value sEstimatedSize2:

    • E0B2C29E-B8FC-490B-A043-2CAE75634972 (for 8.0.2)

    • 46695879-954E-4072-9D32-1CC84D4158F4 (for 8.0.1)

    • 2DF16DF8-A2DB-4EC6-808B-CB5A302DA91B (for 8.0.0)

    • 5A2A1571-B8CD-4AAF-9303-8DF463DABE5A (for 7.5.0)

See also

Machine Learning Server (Standalone)