Utility functions for easier usage of SQL Server Machine Learning Services
Перейти к файлу
aaronburtle 347bdad7a6
Add SQL Server 2022 workflow contained on runner VM with Python (#118)
* pthon installation

* configure python for MLS

* add python client install and tests

* add env variable passwords

* add some doc links use most recent python install version

* whitspace/format

* add logging for python installation

* add passive for python install

* try remove previous python installs

* using python-setup

* new strategy for Python installation

* use github native python path

* add explicit user and pw

* add explicit user and pw

* add explicit user and pw

* add explicit user and pw

* add explicit user and pw

* update some names continueOnError
2024-07-12 13:52:03 -07:00
.github/workflows Add SQL Server 2022 workflow contained on runner VM with Python (#118) 2024-07-12 13:52:03 -07:00
Python Migrate Pipeline to Self-Hosted Runners and Remediate Tests (#104) 2022-08-29 11:32:21 -07:00
R Update CRAN repo to latest, fix one test using removed CRAN packages, ignore another (#113) 2024-06-27 13:17:59 -07:00
.gitignore Add and modify files for PyPI release 2019-10-15 12:07:48 -07:00
AirlineTestDB.bak downgrade bak SQL version and add Airline test users (#15) 2019-01-31 11:52:19 -08:00
CODEOWNERS add codeowners (#116) 2024-06-27 14:39:41 -07:00
CONTRIBUTING.md Initial Commit 2018-09-24 11:59:34 -07:00
LICENSE rename back no extension license 2019-10-15 14:15:00 -07:00
README.md Update README.md formatting (#109) 2024-06-27 15:12:03 -07:00
SECURITY.md Microsoft mandatory file (#102) 2022-08-15 16:49:46 -07:00

README.md

sqlmlutils

BuildAndTest

sqlmlutils is a package designed to help users interact with SQL databases (SQL Server and Azure SQL Database) and execute R or Python code in SQL from an R/Python client. Currently, only the R version of sqlmlutils is supported in Azure SQL Database. Python support will be added later.

Check out the README in each language folder for language-specific details and code examples!

Installation

To install sqlmlutils, follow the instructions below for Python and R, respectively.

Python: To install from PyPI: Run

pip install sqlmlutils

To install from file, download the latest release from https://github.com/microsoft/sqlmlutils/releases:

pip install sqlmlutils-1.1.0.zip

R:

Download the latest release from https://github.com/microsoft/sqlmlutils/releases.

Windows:

To obtain the version of R your server is currently using, please use this query:

EXEC sp_execute_external_script
    @language = N'R',
    @script = N'
        v = R.version
        OutputDataSet = data.frame(rversion=paste0(v$major, ".", v$minor))',
    @input_data_1 = N'select 1'
WITH RESULT SETS ((rversion varchar(max)));

Get the version of R which the server is using and install it locally. Then, run the following commands with the same version of R.

From command prompt, run

R.exe -e "install.packages('odbc', type='binary')"
R.exe CMD INSTALL sqlmlutils_1.0.0.zip

OR To build a new package file and install, run

.\buildandinstall.cmd

Linux

R.exe -e "install.packages('odbc')"
R.exe CMD INSTALL sqlmlutils_1.0.0.tar.gz

Details

sqlmlutils contains 3 main parts:

  • Execution of Python/R in SQL databases using sp_execute_external_script
  • Creation and execution of stored procedures created from scripts and functions
  • Install and manage packages in SQL databases

For more specifics and examples of how to use each language's API, look at the README in the respective folder.

Execute in SQL

Execute in SQL provides a convenient way for the user to execute arbitrary Python/R code inside a SQL database using an sp_execute_external_script. The user does not have to know any t-sql to use this function. Function arguments are serialized into binary and passed into the t-sql script that is generated. Warnings and printed output will be printed at the end of execution, and any results returned by the function will be passed back to the client.

Stored Procedures (Sprocs)

The goal of this utility is to allow users to create and execute stored procedures on their database without needing to know the exact syntax of creating one. Functions and scripts are wrapped into a stored procedure and registered into a database, then can be executed from the Python/R client.

Package Management

R and Python package management with sqlmlutils is supported in SQL Server 2019 CTP 2.4 and later.

With package management users can install packages to a remote SQL database from a client machine. The packages are downloaded on the client and then sent over to SQL databases where they will be installed into library folders. The folders are per-database so packages will always be installed and made available for a specific database. The package management APIs provided a PUBLIC and PRIVATE folders. Packages in the PUBLIC folder are accessible to all database users. Packages in the PRIVATE folder are only accessible by the user who installed the package.