Install SQL Server 2016 R Services
This article explains how to install and configure SQL Server 2016 R Services. If you have SQL Server 2016, install this feature to enable execution of R code in SQL Server.
In SQL Server 2017, R integration is offered in Machine Learning Services, reflecting the addition of Python. If you want R integration and have SQL Server 2017 installation media, see Install SQL Server 2017 Machine Learning Services to add the feature.
A database engine instance is required. You cannot install just R, although you can add it incrementally to an existing instance.
For business continuity, Always On Availabilty Groups are supported for R Services. You have to install R Services, and configure packages, on each node.
Do not install R Services on a failover cluster. The security mechanism used for isolating R processes is not compatible with a Windows Server failover cluster environment.
Do not install R Services on a domain controller. The R Services portion of setup will fail.
Do not install Shared Features > R Server (Standalone) on the same computer running an in-database instance.
Side-by-side installation with other versions of R and Python are possible because the SQL Server instance uses its own copies of the open-source R and Anaconda distributions. However, running code that uses R and Python on the SQL Server computer outside SQL Server can lead to various problems:
- You use a different library and different executable, and get different results, than you do when you are running in SQL Server.
- R and Python scripts running in external libraries cannot be managed by SQL Server, leading to resource contention.
If you used any earlier versions of the Revolution Analytics development environment or the RevoScaleR packages, or if you installed any pre-release versions of SQL Server 2016, you must uninstall them. Running older and newer versions of RevoScaleR and other proprietary packages is not supported. For help with removing previous versions, see Upgrade and Installation FAQ for SQL Server Machine Learning Services.
After setup is complete, be sure to complete the additional post-configuration steps described in this article. These steps include enabling SQL Server to use external scripts, and adding accounts required for SQL Server to run R jobs on your behalf. Configuration changes generally require a restart of the instance, or a restart of the Launchpad service.
Get the installation media
The download location for SQL Server depends on the edition:
SQL Server Enterprise, Standard, and Express Editions are licensed for production use. For Enterprise and Standard Editions, contact your software vendor for the installation media. You can find purchasing information and a directory of Microsoft partners on the Microsoft purchasing website.
Free editions are available at SQL Server Downloads.
Install patch requirement
Microsoft has identified a problem with the specific version of Microsoft VC++ 2013 Runtime binaries that are installed as a prerequisite by SQL Server. If this update to the VC runtime binaries is not installed, SQL Server may experience stability issues in certain scenarios. Before you install SQL Server follow the instructions at SQL Server Release Notes to see if your computer requires a patch for the VC runtime binaries.
For local installations, you must run Setup as an administrator. If you install SQL Server from a remote share, you must use a domain account that has read and execute permissions on the remote share.
Start the setup wizard for SQL Server 2016.
On the Installation tab, select New SQL Server stand-alone installation or add features to an existing installation.
On the Feature Selection page, select the following options:
Select Database Engine Services. The database engine is required in each instance that uses machine learning.
Select R Services (In-Database). Installs support for in-database use of R.
Do not install R Server and R Services at the same time. You would ordinarily install R Server (Standalone) to create an environment that a data scientist or developer uses to connect to SQL Server and deploy R solutions. Therefore, there is no need to install both on the same computer.
On the Consent to Install Microsoft R Open page, click Accept.
This license agreement is required to download Microsoft R Open, which includes a distribution of the open-source R base packages and tools, together with enhanced R packages and connectivity providers from the Microsoft R development team.
After you have accepted the license agreement, there is a brief pause while the installer is prepared. Click Next when the button becomes available.
On the Ready to Install page, verify that the following items are included, and then select Install.
- Database Engine Services
- R Services (In-Database)
Note of the location of the folder under the path
..\Setup Bootstrap\Logwhere the configuration files are stored. When setup is complete, you can review the installed components in the Summary file.
After setup is complete, if you are instructed to restart the computer, do so now. It is important to read the message from the Installation Wizard when you have finished with Setup. For more information, see View and Read SQL Server Setup Log Files.
Set environment variables
For R feature integration only, you should set the MKL_CBWR environment variable to ensure consistent output from Intel Math Kernel Library (MKL) calculations.
In Control Panel, click System and Security > System > Advanced System Settings > Environment Variables.
Create a new User or System variable.
- Set variable name to
- Set the variable value to
This step requires a server restart. If you are about to enable script execution, you can hold off on the restart until all of the configuration work is done.
Enable script execution
Open SQL Server Management Studio.
Connect to the instance where you installed Machine Learning Services, click New Query to open a query window, and run the following command:
The value for the property,
external scripts enabled, should be 0 at this point. That is because the feature is turned off by default. The feature must be explicitly enabled by an administrator before you can run R or Python scripts.
To enable the external scripting feature, run the following statement:
EXEC sp_configure 'external scripts enabled', 1 RECONFIGURE WITH OVERRIDE
Restart the service
When the installation is complete, restart the database engine before continuing to the next, enabling script execution.
Restarting the service also automatically restarts the related SQL Server Launchpad service.
You can restart the service using the right-click Restart command for the instance in SSMS, or by using the Services panel in Control Panel, or by using SQL Server Configuration Manager.
Check the installation status of the instance using custom reports.
Use the following steps to verify that all components used to launch external script are running.
In SQL Server Management Studio, open a new query window, and run the following command:
EXEC sp_configure 'external scripts enabled'
The run_value should now be set to 1.
Open the Services panel or SQL Server Configuration Manager, and verify SQL Server Launchpad service is running. You should have one service for every database engine instance that has R or Python installed. For more information about the service, see Extensibility framework.
If Launchpad is running, you should be able to run simple R to verify that external scripting runtimes can communicate with SQL Server.
Open a new Query window in SQL Server Management Studio, and then run a script such as the following:
EXEC sp_execute_external_script @language =N'R', @script=N' OutputDataSet <- InputDataSet; ', @input_data_1 =N'SELECT 1 AS hello' WITH RESULT SETS (([hello] int not null)); GO
The script can take a little while to run, the first time the external script runtime is loaded. The results should be something like this:
We recommend that you apply the latest cumulative update to both the database engine and machine learning components.
On internet-connected devices, cumulative updates are typically applied through Windows Update, but you can also use the steps below for controlled updates. When you apply the update for the database engine, Setup pulls in the cumulative updates for R libraries you installed on the same instance.
On disconnected servers, extra steps are required. For more information, see Install on computers with no internet access > Apply cumulative updates.
Start with a baseline instance already installed: SQL Server 2016 initial release, SQL Server 2016 SP 1, or SQL Server 2016 SP 2.
Go to the cumulative update list: SQL Server 2016 updates
Select the latest cumulative update. An executable is downloaded and extracted automatically.
Run Setup. Accept the licensing terms, and on the Feature selection page, review the features for which cumulative updates are applied. You should see every feature installed for the current instance, including R Services. Setup downloads the CAB files necessary to update all features.
Continue through the wizard, accepting the licensing terms for the R distribution.
If the external script verification step was successful, you can run Python commands from SQL Server Management Studio, Visual Studio Code, or any other client that can send T-SQL statements to the server.
If you got an error when running the command, review the additional configuration steps in this section. You might need to make additional appropriate configurations to the service or database.
At the instance level, additional configuration might include:
- Firewall configuration for SQL Server Machine Learning Services
- Enable additional network protocols
- Enable remote connections
On the database, you might need the following configuration updates:
Not all the listed changes are required, and none might be required. Requirements depend on your security schema, where you installed SQL Server, and how you expect users to connect to the database and run external scripts. Additional troubleshooting tips can be found here: Upgrade and installation FAQ
Now that you have everything working, you might also want to optimize the server to support machine learning, or install pretrained models.
Add more worker accounts
If you think you might use R heavily, or if you expect many users to be running scripts concurrently, you can increase the number of worker accounts that are assigned to the Launchpad service. For more information, see Modify the user account pool for SQL Server Machine Learning Services.
Optimize the server for external script execution
The default settings for SQL Server setup are intended to optimize the balance of the server for a variety of services that are supported by the database engine, which might include extract, transform, and load (ETL) processes, reporting, auditing, and applications that use SQL Server data. Therefore, under the default settings, you might find that resources for machine learning are sometimes restricted or throttled, particularly in memory-intensive operations.
To ensure that machine learning jobs are prioritized and resourced appropriately, we recommend that you use SQL Server Resource Governor to configure an external resource pool. You might also want to change the amount of memory that's allocated to the SQL Server database engine, or increase the number of accounts that run under the SQL Server Launchpad service.
To configure a resource pool for managing external resources, see Create an external resource pool.
To change the amount of memory reserved for the database, see Server memory configuration options.
To change the number of R accounts that can be started by SQL Server Launchpad, see Modify the user account pool for machine learning.
If you are using Standard Edition and do not have Resource Governor, you can use Dynamic Management Views (DMVs) and Extended Events, as well as Windows event monitoring, to help manage the server resources that are used by R. For more information, see Monitoring and managing R Services.
Install additional R packages
The R solutions you create for SQL Server can call basic R functions, functions from the proprietary packages installed with SQL Server, and third-party R packages compatible with the version of open-source R installed by SQL Server.
Packages that you want to use from SQL Server must be installed in the default library that is used by the instance. If you have a separate installation of R on the computer, or if you installed packages to user libraries, you won't be able to use those packages from T-SQL.
The process for installing and managing R packages is different in SQL Server 2016 and SQL Server 2017. In SQL Server 2016, a database administrator must install R packages that users need. In SQL Server 2017, you can set up user groups to share packages on a per-database level, or configure database roles to enable users to install their own packages. For more information, see Install new R packages.
R developers can get started with some simple examples, and learn the basics of how R works with SQL Server. For your next step, see the following links:
To view examples of machine learning that are based on real-world scenarios, see Machine learning tutorials.