| title | Install SQL Server Machine Learning Services (R, Python, Java) on Linux | Microsoft Docs |
|---|---|
| description | This article describes how to install SQL Server Machine Learning Services (R, Python, Java) on Red Hat and Ubuntu. |
| author | HeidiSteen |
| ms.author | heidist |
| manager | cgronlun |
| ms.date | 10/09/2018 |
| ms.topic | conceptual |
| ms.prod | sql |
| ms.custom | sql-linux |
| ms.technology | machine-learning |
| monikerRange | >=sql-server-ver15||>=sql-server-linux-ver15||=sqlallproducts-allversions |
SQL Server Machine Learning Services runs on Linux operating systems starting in this preview release of SQL Server 2019. Follow the steps in this article to install the Java programming extension, or the machine learning extensions for R and Python.
Machine learning and programming extensions are an add-on to the database engine. Although you can install the database engine and Machine Learning Services concurrently, it's a best practice to install and configure the SQL Server database engine first so that you can resolve any issues before adding more components.
Package location of the R, Python, and Java extensions are in the SQL Server Linux source repositories. If you already configured source repositories for the database engine install, you can run the mssql-mlservices package install commands using the same repo registration.
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Linux operating system must be supported by SQL Server, running on premises or in a Docker container.
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You must have a SQL Server 2019 Database Engine instance on:
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For R only, Microsoft R Open for mssql-mlsservices R packages.
Microsoft's base distribution of R is a prerequisite for using RevoScaleR, MicrosoftML, and other R packages installed with Machine Learning Services.
The required version is MRO 3.4.4.
Choose from the following two approaches to install MRO:
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Download the MRO tarball from MRAN, unpack it, and run its install.sh script. You can follow the installation instructions on MRAN if you want this approach.
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Alternatively, register the packages.microsoft.com repo as described below to install the three packages comprising the MRO distribution: microsoft-r-open-mro, microsoft-r-open-mkl, and microsoft-r-open-foreachiterators.
The following commands register the repository providing MRO. Post-registration, the commands for installing other R packages, such as mssql-mlservices-mml-r, will automatically include MRO as a package dependency.
# Install as root
sudo su
# Optionally, if your system does not have the https apt transport option
apt-get install apt-transport-https
# Add the **azure-cli** repo to your apt sources list
AZ_REPO=$(lsb_release -cs)
echo "deb [arch=amd64] https://packages.microsoft.com/repos/azure-cli/ $AZ_REPO main" | sudo tee /etc/apt/sources.list.d/azure-cli.list
# Set the location of the package repo the "prod" directory containing the distribution.
# This example specifies 16.04. Replace with 14.04 if you want that version
wget https://packages.microsoft.com/config/ubuntu/16.04/packages-microsoft-prod.deb
# Register the repo
dpkg -i packages-microsoft-prod.deb# Import the Microsoft repository key
sudo rpm --import https://packages.microsoft.com/keys/microsoft.asc
# Create local `azure-cli` repository
sudo sh -c 'echo -e "[azure-cli]\nname=Azure CLI\nbaseurl=https://packages.microsoft.com/yumrepos/azure-cli\nenabled=1\ngpgcheck=1\ngpgkey=https://packages.microsoft.com/keys/microsoft.asc" > /etc/yum.repos.d/azure-cli.repo'
# Set the location of the package repo at the "prod" directory
# The following command is for version 7.x
# For 6.x, replace 7 with 6 to get that version
rpm -Uvh https://packages.microsoft.com/config/rhel/7/packages-microsoft-prod.rpm# Install as root
sudo su
# Set the location of the package repo at the "prod" directory containing the distribution
# This example is for SLES12, the only supported version of SUSE in Machine Learning Server
zypper ar -f https://packages.microsoft.com/sles/12/prod packages-microsoft-com
# Update packages on your system:
zypper updateOn an internet-connected device, packages are downloaded and installed independently of the database engine using the package installer for each operating system. The following table describes all available packages, but for internet-connected installs, you only need one R or Python package to get a specific combination of features.
| Package name | Applies-to | Description |
|---|---|---|
| mssql-server-extensibility | All | Extensibility framework used to run R, Python, or Java code. |
| mssql-server-extensibility-java | Java | Java extension for loading a Java execution environment. There are no additional libraries or packages for Java. |
| microsoft-openmpi | Python, R | Message passing interface used by the Revo* libraries for parallelization on Linux. |
| microsoft-r-open* | R | Open-source distribution of R, composed of three packages. |
| mssql-mlservices-python | Python | Open-source distribution of Anaconda and Python. |
| mssql-mlservices-mlm-py | Python | Full install. Provides revoscalepy, microsoftml, pre-trained models for image featurization and text sentiment analysis. |
| mssql-mlservices-mml-py | Python | Partial install. Provides revoscalepy, microsoftml. Excludes pre-trained models. |
| mssql-mlservices-packages-py | Python | Partial install. Provides revoscalepy. Excludes pre-trained models and microsoftml. |
| mssql-mlservices-mlm-r | R | Full install. Provides RevoScaleR, MicrosoftML, sqlRUtils, olapR, pre-trained models for image featurization and text sentiment analysis. |
| mssql-mlservices-mml-r | R | Partial install. Provides RevoScaleR, MicrosoftML, sqlRUtils, olapR. Excludes pre-trained models. |
| mssql-mlservices-packages-r | R | Partial install. Provides RevoScaleR, sqlRUtils, olapR. Excludes pre-trained models and MicrosoftML. |
Install any one R package, plus any one Python package, and Java if you want that capability. Each R and Python package includes a bundle of features. Choose the package that provides the feature set you need. Dependent packages are included automatically.
Tip
If possible, run yum clean all to refresh packages on the system prior to installation.
Includes open-source R and Python, extensibility framework, microsoft-openmpi, extensions (R, Python, Java), with machine learning libraries and pre-trained models for R and Python. For R and Python, if you want something in between full and minimum install - such as machine learning libraries but without the pre-trained models - substitute mssql-mlservices-mml-r-9.4.5* and mssql-mlservices-mml-py-9.4.5* instead.
# Install as root or sudo
# Add everything (all R, Python, Java)
# Be sure to include -9.4.5* in mlsservices package names
sudo yum install mssql-mlservices-mlm-py-9.4.5*
sudo yum install mssql-mlservices-mlm-r-9.4.5*
sudo yum install mssql-server-extensibility-javaIncludes open-source R and Python, extensibility framework, microsoft-openmpi, core Revo* libraries for R and Python, Java extension. Excludes pre-trained models and machine learning libraries for R and Python.
# Install as root or sudo
# Minimum install of R, Python, Java extensions
# Be sure to include -9.4.5* in mlsservices package names
sudo yum install mssql-mlservices-packages-py-9.4.5*
sudo yum install mssql-mlservices-packages-r-9.4.5*
sudo yum install mssql-server-extensibility-javaInstall any one R package, plus any one Python package, and Java if you want that capability. Each R and Python package includes a bundle of features. Choose the package that provides the feature set you need. Dependent packages are included automatically.
Tip
If possible, run apt-get update to refresh packages on the system prior to installation. Additionally, some docker images of Ubuntu might not have the https apt transport option. To install it, use apt-get install apt-transport-https.
Includes open-source R and Python, extensibility framework, microsoft-openmpi, extensions (R, Python, Java), with machine learning libraries and pre-trained models for R and Python. For R and Python, if you want something in between full and minimum install - such as machine learning libraries but without the pre-trained models - substitute mssql-mlservices-mml-r and mssql-mlservices-mml-py instead.
# Install as root or sudo
# Add everything (all R, Python, Java)
# There is no asterisk in this full install
sudo apt-get install mssql-mlservices-mlm-py
sudo apt-get install mssql-mlservices-mlm-r
sudo apt-get install mssql-server-extensibility-javaIncludes open-source R and Python, extensibility framework, microsoft-openmpi, core Revo* libraries for R and Python, Java extension. Excludes pre-trained models and machine learning libraries for R and Python.
# Install as root or sudo
# Minimum install of R, Python, Java
# No aasterisk
sudo apt-get install mssql-mlservices-packages-py
sudo apt-get install mssql-mlservices-packages-r
sudo apt-get install mssql-server-extensibility-javaInstall any one R package, plus any one Python package, and Java if you want that capability. Each R and Python package includes a bundle of features. Choose the package that provides the feature set you need. Dependent packages are included automatically.
Includes open-source R and Python, extensibility framework, microsoft-openmpi, extensions (R, Python, Java), with machine learning libraries and pre-trained models for R and Python. For R and Python, if you want something in between full and minimum install - such as machine learning libraries but without the pre-trained models - substitute mssql-mlservices-mml-r-9.4.5* and mssql-mlservices-mml-py-9.4.5* instead.
# Install as root or sudo
# Add everything (all R, Python, Java)
# Be sure to include -9.4.5* in mlsservices package names
sudo zypper install mssql-mlservices-mlm-py-9.4.5*
sudo zypper install mssql-mlservices-mlm-r-9.4.5*
sudo zypper install mssql-server-extensibility-javaIncludes open-source R and Python, extensibility framework, microsoft-openmpi, core Revo* libraries for R and Python, Java extension. Excludes pre-trained models and machine learning libraries for R and Python.
# Install as root or sudo
# Minimum install of R, Python, Java extensions
# Be sure to include -9.4.5* in mlsservices package names
sudo zypper install mssql-mlservices-packages-py-9.4.5*
sudo zypper install mssql-mlservices-packages-r-9.4.5*
sudo zypper install mssql-server-extensibility-javaAdditional configuration is primarily through the mssql-conf tool.
- Add the mssql user account used to run the SQL Server Launchpad service.
sudo /opt/mssql/bin/mssql-conf setup- Accept the licensing agreements for open-source R and Python. There are several ways to do this. If you previously accepted SQL Server licensing and are now adding the R or Python extensions, the following command is your consent to their terms:
# Run as SUDO or root
# Use set + EULA
sudo /opt/mssql/bin/mssql-conf set EULA accepteulaml YAn alternative workflow is that if you have not yet accepted the SQL Server database engine licensing agreement, setup detects the mssql-mlservices packages and prompts for EULA acceptance when mssql-conf setup is run. For more information about EULA parameters, see Configure SQL Server with the mssql-conf tool.
- Restart the SQL Server Launchpad service and the database engine instance.
systemctl restart mssql-launchpadd
systemctl restart mssql-server.service- Enable external script execution in SQL Server Management Studio or another tool that runs Transact-SQL.
EXEC sp_configure 'external scripts enabled', 1
RECONFIGURE WITH OVERRIDE R libraries (MicrosoftML, RevoScaleR, and others) can be found at /opt/mssql/mlservices/libraries/RServer.
Python libraries (microsoftml and revoscalepy) can be found at /opt/mssql/mlservices/libraries/PythonServer.
Using a SQL Server query tool, execute the following SQL command to test R execution in SQL Server. If the script does not run, try a service restart, sudo systemctl restart mssql-server.
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 Execute the following SQL command to test Python execution in SQL Server.
EXEC sp_execute_external_script
@language =N'Python',
@script=N'
OutputDataSet = InputDataSet;
',
@input_data_1 =N'SELECT 1 AS hello'
WITH RESULT SETS (([hello] int not null));
GO You can install and configure the database engine and Machine Learning Services in one procedure by appending R, Python, or Java packages and parameters on a command that installs the database engine.
The following example is a "template" illustration of what a combined package installation looks like using the Yum package manager. It installs the database engine and adds the Java language extension, which pulls in the extensibility framework package as a dependency.
sudo yum install -y mssql-server mssql-server-extensibility-java An expanded example with all extensions (Java, R, Python) looks like this:
sudo yum install -y mssql-server mssql-server-extensibility-java mssql-mlservices-packages-r-9.4.5* mssql-mlservices-packages-py-9.4.5*Except for the R prerequisites, all of the packages used in this example are found at the same path. Adding R requires that you register the microsoft-r-open package repository as an extra step to get MRO. MRO is a prerequisite for R extensibility. On a computer connected to the internet, MRO is retrieved and installed automatically as part of the R extension, assuming you configured both repositories.
Post-installation, remember to use the mssql-conf tool to configure the entire installation and accept licensing agreements. Unaccepted EULAs for open-source R and Python components are detected automatically, and you are prompted to accept them, along with the EULA for SQL Server.
sudo /opt/mssql/bin/mssql-conf setup MSSQL_PID=Developer Using the unattended install for the Database Engine, add the packages for mssql-mlservices and EULAs.
Recall that Setup or the mssql-conf tool prompts for license agreement acceptance. If you already configured SQL Server database engine and accepted its EULA, use one of the mlservices-specific EULA parameters for the open-source R and Python distributions:
sudo /opt/mssql/bin/mssql-conf setup accept-eula-mlAll possible permutations of EULA acceptance are documented in Configure SQL Server on Linux with the mssql-conf tool.
Follow the Offline installation instructions for steps on installing the packages. Find your download site, and then download specific packages using the package list below.
Tip
Several of the package management tools provide commands that can help you determine package dependencies. For yum, use sudo yum deplist [package]. For Ubuntu, use sudo apt-get install --reinstall --download-only [package name] followed by dpkg -I [package name].deb.
You can download packages from https://packages.microsoft.com/. All of the mlservices packages for R, Python, and Java are co-located with database engine package. Base version for the mlservices packages is 9.4.5. The micrososoft-r-open packages are in a different folder.
| mssql/mlservices packages | https://packages.microsoft.com/rhel/7/mssql-server-preview/ |
| microsoft-r-open packages | https://packages.microsoft.com/rhel/7/prod/ |
| mssql/mlservices packages | https://packages.microsoft.com/ubuntu/16.04/mssql-server-preview/pool/main/m/ |
| microsoft-r-open packages | https://packages.microsoft.com/ubuntu/16.04/prod/pool/main/m/ |
| mssql/mlservices packages | https://packages.microsoft.com/sles/12/mssql-server-preview/ |
| microsoft-r-open packages | https://packages.microsoft.com/sles/12/prod/ |
Depending on which extensions you want to use, download the packages necessary for a specific language. Exact filenames include platform information, but the file names below should be close enough for you to determine which files to get.
# Core packages
mssql-server-15.0.1000
mssql-server-extensibility-15.0.1000
# Java
mssql-server-extensibility-java-15.0.1000
# R
microsoft-openmpi-3.0.0
microsoft-r-open-foreachiterators-3.4.4
microsoft-r-open-mkl-3.4.4
microsoft-r-open-mro-3.4.4
mssql-mlservices-packages-r-9.4.5
mssql-mlservices-mlm-r-9.4.5
mssql-mlservices-mml-r-9.4.5
# Python
microsoft-openmpi-3.0.0
mssql-mlservices-python-9.4.5
mssql-mlservices-packages-py-9.4.5
mssql-mlservices-mlm-py-9.4.5
mssql-mlservices-mml-py-9.4.5
You can install other R and Python packages and use them in script that executes on SQL Server 2019.
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Start an R session.
# sudo /opt/mssql/mlservices/bin/R/R -
Install an R package called glue to test package installation.
# install.packages("glue",lib="/opt/mssql/mlservices/libraries/RServer")Alternatively, you can install an R package from the command line
# sudo /opt/mssql/mlservices/bin/R/R CMD INSTALL -l /opt/mssql/mlservices/libraries/RServer glue_1.1.1.tar.gz -
Import the R package in sp_execute_external_script.
EXEC sp_execute_external_script @language = N'R', @script = N'library(glue)'
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Install a Python package called httpie using pip.
# sudo /opt/mssql/mlservices/bin/python/python -m pip install httpie -
Import the Python package in sp_execute_external_script.
EXEC sp_execute_external_script @language = N'Python', @script = N'import httpie'
The following limitations exist in this CTP release.
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Implied authentication is currently not available in Machine Learning Services on Linux at this time, which means you cannot connect back to the server from an in-progress R or Python script to access data or other resources.
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CREATE EXTERNAL LIBRARY (for storing R packages in the database) is currently not available on Linux and does not support Python.
There is parity between Linux and Windows for Resource governance for external resource pools, but the statistics for sys.dm_resource_governor_external_resource_pools currently have different units on Linux. Units will align in an upcoming CTP.
| Column name | Description | Value on Linux |
|---|---|---|
| peak_memory_kb | The maximum amount of memory used for the resource pool. | On Linux, this statistic is sourced from the CGroups memory subsystem, where the value is memory.max_usage_in_bytes |
| write_io_count | The total write IOs issued since the Resource Governor statistics were reset. | On Linux, this statistic is sourced from the CGroups blkio subsystem, where the value on the write row is blkio.throttle.io_serviced |
| read_io_count | The total read IOs issued since the Resource Governor statistics were reset. | On Linux, this statistic is sourced from the CGroups blkio subsystem, where value on the read row is blkio.throttle.io_serviced |
| total_cpu_kernel_ms | The cumulative CPU user kernel time in milliseconds since the Resource Governor statistics were reset. | On Linux, this statistic is sourced from the CGroups cpuacct subsystem, where the value on the user row is cpuacct.stat |
| total_cpu_user_ms | The cumulative CPU user time in milliseconds since the Resource Governor statistics were reset. | On Linux, this statistic is sourced from the CGroups cpuacct subsystem, where the value on the system row value is cpuacct.stat |
| active_processes_count | The number of external processes running at the moment of the request. | On Linux, this statistic is sourced from the GGroups pids subsystem, where the value is pids.current |
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:
Python developers can learn how to use Python with SQL Server by following these tutorials:
To view examples of machine learning that are based on real-world scenarios, see Machine learning tutorials.