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Applies to: 
SQL Server 2017 (14.x) and later
Azure SQL Managed Instance
Machine Learning Services is a feature in SQL Server that gives the ability to run Python and R scripts with relational data. You can use open-source packages and frameworks, and the Microsoft Python and R packages, for predictive analytics and machine learning. The scripts are executed in-database without moving data outside SQL Server or over the network. This article explains the basics of SQL Server Machine Learning Services and how to get started.
Bilješka
Machine Learning Services is also available in Azure SQL Managed Instance. For machine learning on other SQL platforms, see the SQL machine learning documentation.
Bilješka
Machine Learning Services is also available in Azure SQL Managed Instance. For machine learning on other SQL platforms, see the SQL machine learning documentation.
For executing Java in SQL Server, see the Java Language Extension documentation.
For executing C# in SQL Server, see the C# Language Extension documentation.
SQL Server Machine Learning Services lets you execute Python and R scripts in-database. You can use it to prepare and clean data, do feature engineering, and train, evaluate, and deploy machine learning models within a database. The feature runs your scripts where the data resides and eliminates transfer of the data across the network to another server.
You can execute Python and R scripts on a SQL Server instance with the stored procedure sp_execute_external_script.
Base distributions of Python and R are included in Machine Learning Services. You can install and use open-source packages and frameworks, such as PyTorch, TensorFlow, and scikit-learn, in addition to the Microsoft packages.
Machine Learning Services uses an extensibility framework to run Python and R scripts in SQL Server. Learn more about how this works:
Install SQL Server Machine Learning Services on Windows or on Linux. You can also use Machine Learning Services on Big Data Clusters and Machine Learning Services in Azure SQL Managed Instance.
Configure your development tools. You can use run Python and R scripts in Azure Data Studio notebooks. You can also run T-SQL in Azure Data Studio.
Write your first Python or R script.
Configure your development tools. You can use run Python and R scripts in Azure Data Studio notebooks. You can also use T-SQL in Azure Data Studio.
Write your first Python or R script.
The following lists the versions of Python and R that are included in Machine Learning Services.
| SQL Server version | Cumulative Update | Python runtime version | R runtime versions |
|---|---|---|---|
| SQL Server 2022* | RTM and later | 3.10.2 | 4.2.0 |
| SQL Server 2019 | RTM and later | 3.7.1 | 3.5.2 |
| SQL Server 2017 | CU22 and later | 3.5.2 and 3.7.2 | 3.3.3 and 3.5.2 |
| SQL Server 2017 | RTM - CU21 | 3.5.2 | 3.3.3 |
| SQL Server 2016 | See the R version |
* For supported versions of R and Python and the RevoScaleR and revoscalepy packages, see Install SQL Server 2022 Machine Learning Services (Python and R) on Windows or Install SQL Server Machine Learning Services (Python and R) on Linux.
You can use open-source packages and frameworks, in addition to Microsoft's enterprise packages. Most common open-source Python and R packages are pre-installed in Machine Learning Services.
Bilješka
Beginning with SQL Server 2022 (16.x), runtimes for R, Python, and Java, are no longer installed with SQL Setup. Instead, install your desired R and/or Python custom runtime(s) and packages. For more information, see Install SQL Server 2022 Machine Learning Services on Windows or Install SQL Server Machine Learning Services (Python and R) on Linux.
The following Python and R packages from Microsoft are also included at installation:
| Language | Package | Description |
|---|---|---|
| Python | revoscalepy | The primary package for scalable Python. Data transformations and manipulation, statistical summarization, visualization, and many forms of modeling. Additionally, functions in this package automatically distribute workloads across available cores for parallel processing. |
| Python | microsoftml | Applies only to SQL Server 2016, SQL Server 2017, and SQL Server 2019. Adds machine learning algorithms to create custom models for text analysis, image analysis, and sentiment analysis. |
| R | RevoScaleR | The primary package for scalable R. Data transformations and manipulation, statistical summarization, visualization, and many forms of modeling. Additionally, functions in this package automatically distribute workloads across available cores for parallel processing. |
| R | MicrosoftML (R) | Applies only to SQL Server 2016, SQL Server 2017, and SQL Server 2019. Adds machine learning algorithms to create custom models for text analysis, image analysis, and sentiment analysis. |
| R | olapR | Applies only to SQL Server 2016, SQL Server 2017, and SQL Server 2019. R functions used for MDX queries against a SQL Server Analysis Services OLAP cube. |
| R | sqlrutils | Applies only to SQL Server 2016, SQL Server 2017, and SQL Server 2019. A mechanism to use R scripts in a T-SQL stored procedure, register that stored procedure with a database, and run the stored procedure from an R development environment. |
| R | Microsoft R Open (retired) | Applies to: SQL Server 2016, SQL Server 2017, and SQL Server 2019. Microsoft R Open (MRO) was the enhanced distribution of R from Microsoft. |
For more information on which packages are installed with Machine Learning Services and how to install other packages, see:
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Dokumentacija
-
What's new in SQL Server Machine Learning Services? - SQL Server Machine Learning Services
New feature announcements for each release of SQL Server Machine Learning Services and SQL Server 2016 R Services.
-
Python language extension - SQL Server Machine Learning Services
Learn about the Python extension for running external Python scripts with SQL Server Machine Learning Services.
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Extensibility architecture - SQL Server Machine Learning Services
This article describes the architecture of the extensibility framework for running an external Python or R script on SQL Server Machine Learning Services. The script executes in a language runtime environment as an extension to the core database engine.