Understanding SQL Server’s External Language Runtime for Executing External Scripts
SQL Server has come a long way since its inception, evolving significantly over the years to meet the growing needs of database administrators, data analysts, and application developers. Amongst its feature set is the powerful External Language Runtime (ELR) that enables the execution of external scripts directly from SQL Server. This capability allows for a much broader range of analyses and operations, leveraging the strengths of various programming languages within SQL Server’s database environment.
In this comprehensive analysis, we will delve into SQL Server’s External Language Runtime, exploring its functionality, use cases, benefits, and considerations to help you harness its power effectively and securely in your data-related tasks.
What is SQL Server’s External Language Runtime?
External Language Runtime (ELR) in SQL Server is a framework that allows for the integration and execution of external scripts and code written in supported programming languages such as R, Python, Java, and others. ELR was first introduced in SQL Server 2016 with support for R Services, and later expanded to include Python support with the release of SQL Server 2017. This feature, also known as ‘External Scripts Execution,’ enables SQL Server to execute R and Python scripts in the context of a T-SQL query.
External Language Runtime utilizes a separate service called ‘SQL Server Launchpad’ to manage communications between SQL Server and the external runtimes. This dedicated service helps ensure that the code execution does not adversely impact the performance and stability of the SQL Server itself.
Key Components
SQL Server Launchpad Service
The SQL Server Launchpad service facilitates the interoperability between SQL Server and the external engines. It is responsible for starting the external runtime processes required for script execution, passing data between SQL Server and the external runtime, and returning results to the client.
Supported Languages
As of the time of writing, SQL Server’s ELR supports several languages, most notably:
- R – A language and environment for statistical computing and graphics.
- Python – A versatile programming language with strong support for data manipulation, machine learning, and analytics.
- Java – Known for its robustness, Java can be used to build complex applications and processes within SQL Server.
Support for additional languages can be anticipated as ELR continues to evolve with further releases of SQL Server.
Setting Up External Language Runtime
Before you can execute external scripts, the SQL Server instance must be configured to support the External Language Runtime, and the necessary external language extensions must be installed.
Installing External Languages
To get started with R or Python support, the external language runtime components must be downloaded and installed. This typically involves running the SQL Server setup and selecting the ‘Advanced Analytics (R and Python) Services’ feature.
Configuring the SQL Server Instance
Once the languages are installed, you’ll need to enable external script execution on the SQL Server instance using the sp_configure system stored procedure. Additionally, ensure that the SQL Server Launchpad service is running to manage the execution of the external scripts.
EXEC sp_configure 'external scripts enabled', 1;
RECONFIGURE;
This command enables the feature and applies the new configuration to the server.
Using ELR in SQL Server
Executing external scripts involves the use of the sp_execute_external_script system stored procedure, which is central to the operation of ELR. This procedure has various parameters allowing you to specify the language of the script, the script itself, input data from a SQL query, and how to process the output data.
EXEC sp_execute_external_script
@language = N'Python',
@script = N'Your Python script here',
@input_data_1 = N'SELECT * FROM YourTable';
The above example shows how to invoke a Python script in the context of a SQL query on a table called ‘YourTable’.
Understanding External Runtime with R Language
R is a popular language for statistical analysis and visualization. SQL Server 2016 initially added support for R, which allows running R scripts directly from within SQL Server.
Integrating R with SQL Server’s ELR provides powerful data analytics and machine learning capabilities directly on the data stored in the SQL database, without the need to move it to a separate analytics platform. This integration also optimizes performance since the data can be processed natively, close to where it resides.
Understanding External Runtime with Python Language
Similar to R, Python is a highly regarded language in the areas of data science and analytics. SQL Server’s support for Python through the ELR allows for complex data processing, analytics, and machine learning tasks to be executed directly alongside SQL queries.
SQL Server’s Python integration means you can leverage libraries such as pandas for data manipulation, NumPy for numerical processing, and scikit-learn for machine learning directly on data within the database.
Benefits of Using External Language Runtime
The integration of
