Machine Learning in SQL Server 2019

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Machine Learning
Services
in SQL Server 2019

1988 2000 Founderv 6.0 60 +2010
Antonios Chatzipavlis
Data Solutions Consultant & Trainer
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Machine Learning Services
in
SQL Server 2019

Microsoft Learn Student Ambassadors | Greece
Data Analysis Scientific Process
• Create, Read, Update, Delete
• Programming Control
• Reporting
• Business Intelligence
• Statistics and Data Mining
• Story Telling
• Define the Question
• Create Hypothesis
• Create a Repeatable Test
• Publish Results
Data Science

Descriptive
- Reporting and Scorecards
- Grouping Similarity Scores
Prescriptive
- Optimization and Simulation
- What, Why, When
Predictive
- Predicting the future from the past
Types of Analysis
Machine
Learning

Machine Learning Algorithms
Which category?
How much/many?
Which Group?
Is it odd?
Which action?
Classification
Regression
Clustering
Anomaly
Reinforcement Learning

Team
Data
Science
Process
https://bit.ly/2DkeHvL

Collaboration and end-to-end efficiency
• Deploy training/scoring scripts in DB
• Make models accessible to any
applications
• Manage model version in DB
• Consume ML models from any apps
• Make simple stored proc calls
• Train models remotely on SQL Server
• Use R/Python code to embedded in T-SQL
stored procedure
• Explore and experiment with data
• Stay in your favorite IDE
• Use R, Python, T-SQL
Explore Train
Deploy
Share &
Consume
SQL Server
ML Services
App Developer
Data Scientist
Data Scientist
SQL Server DBA

Evolution of SQL Server ML Services

Machine Learning outside of database
Data
transformations
Model
training Model
Analytics Server
Scoring
Separate server or embedded logic
Application
Transactions
Data movement
Model
operationalization
New data
Predictions

In-Database Machine Learning
Application
Data
transformations
Model
training
Scoring
Transactions

How it works
Application
Server Box
Satellite
T-SQL
SQL Server
Launchpad Service
Direct
Communication
Performance

• A database engine instance is required.
• Always On Availability Groups are supported for Machine Learning
Services.
• Always On Failover Cluster Instance (FCI) is supported with SQL Server
2019 and later.
• Don't install Machine Learning Services on a domain controller
• Side-by-side installation with other versions of Python and R is supported
but isn't recommended.
Pre-install checklist

What we need to install?

Set environment variables
Enable script execution
Restart the service
Post Installation actions

Verify installation
R
Python

• Create a login for SQLRUserGroup.
• Make sure that SQLRUserGroup has "Allow Log on locally" permissions.
• Firewall configuration for SQL Server Machine Learning Services.
• Ensure that SQL Server TCP network protocol is enabled.
• Ensure that SQL Server Remote Access is enabled.
• Manage disk quotas to avoid external scripts running tasks that exhaust
disk space
Additional configuration

Get Python package information

Packages Version Description
revoscalepy 9.4.7
Used for remote compute contexts, streaming, parallel execution of rx
functions for data import and transformation, modeling, visualization,
and analysis.
microsoftml 9.4.7 Adds machine learning algorithms in Python.
Microsoft Python packages

Packages Version Description
RevoScaleR 9.4.7
Used for remote compute contexts, streaming, parallel execution of rx
functions for data import and transformation, modeling, visualization, and
analysis.
sqlrutils 1.0.0 Used for including R script in stored procedures.
MicrosoftML 9.4.7 Adds machine learning algorithms in R.
olapR 1.0.0 Used for writing MDX statements in R.
Microsoft R packages

Don't try to install Python packages directly in the SQL package library
using pip or similar methods.
Install Python / R packages with sqlmlutils
Python : https://bit.ly/3fn668o
R : https://bit.ly/2DE9IWb
Install new Python / R packages
For SQL Server 2019

Code Execution
R / Python / Java
sp_execute_external_script
@language
@script

Code Execution
Execute with Result Sets
EXECUTE sp_execute_external_script @language = N'Python'
, @script = N'OutputDataSet = InputDataSet;'
, @input_data_1 = N'SELECT * FROM T;'
WITH RESULT SETS(([ID] INT,[YOD] INT,[Name] nvarchar(200)));
GO

• Generates a predicted value or scores
based on a stored model.
• Uses the native C++ extension
capabilities in SQL machine learning.
• Offers the fastest possible processing
speed of forecasting and prediction
workloads
• Support models in Open Neural
Network Exchange (ONNX) format or
models trained using the RevoScaleR
and revoscalepy packages.
PREDICT
T-SQL function
PREDICT

Download them from GitHub https://bit.ly/2DyHLzc
In these reports, you can view details such as:
• Active Python or R sessions
• Configuration settings for the instance
• Execution statistics for machine learning jobs
• Extended events for R Services
• Python or R packages installed on the current instance
Monitor using SSMS Reports

sys.dm_external_script_requests
Returns a row for each active worker account that is running an external script.
sys.dm_external_script_execution_stats
Returns one row for each type of external script request.
Monitor using DMVs

Monitor using XE
event
SQLSatellite
predict%
https://bit.ly/33zlCf1

Thank you!
@antoniosch - @sqlschool
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Antonios Chatzipavlis
Data Solutions Consultant & Trainer

Machine Learning in SQL Server 2019

Machine Learning in SQL Server 2019

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