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Introducing Microsoft SQL Server 2019

You're reading from   Introducing Microsoft SQL Server 2019 Reliability, scalability, and security both on premises and in the cloud

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781838826215
Length 488 pages
Edition 1st Edition
Languages
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Authors (8):
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Allan Hirt Allan Hirt
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Allan Hirt
Dustin Ryan Dustin Ryan
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Dustin Ryan
Mitchell Pearson Mitchell Pearson
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Mitchell Pearson
Kellyn Gorman Kellyn Gorman
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Kellyn Gorman
Dave Noderer Dave Noderer
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Dave Noderer
Buck Woody Buck Woody
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Buck Woody
Arun Sirpal Arun Sirpal
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Arun Sirpal
James Rowland-Jones James Rowland-Jones
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James Rowland-Jones
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Table of Contents (15) Chapters Close

Preface 1. Optimizing for performance, scalability and real‑time insights 2. Enterprise Security FREE CHAPTER 3. High Availability and Disaster Recovery 4. Hybrid Features – SQL Server and Microsoft Azure 5. SQL Server 2019 on Linux 6. SQL Server 2019 in Containers and Kubernetes 7. Data Virtualization 8. Machine Learning Services Extensibility Framework 9. SQL Server 2019 Big Data Clusters 10. Enhancing the Developer Experience 11. Data Warehousing 12. Analysis Services 13. Power BI Report Server 14. Modernization to the Azure Cloud

Machine learning using the sp_rxPredict stored procedure

Another method you can use for scoring predictions in the database is to use the sp_rxPredict stored procedure. As you can see in the name, this process involves using the RevoScaleR or the MicrosoftML functions (a full list of the algorithms in those functions can be found in the following link).

Note

To use sp_rxPredict, you'll need to enable the common language runtime (CLR) in SQL Server, but you don't need to install R or Python. You'll also need to enable real-time scoring by following the instructions here: https://docs.microsoft.com/en-us/sql/advanced-analytics/real-time-scoring?view=sql-server-ver15#bkmk_enableRtScoring.

With the prerequisites completed, you then have to follow this process to score the predictions in T-SQL:

  1. Load a trained model into a binary variable.
  2. Select the data you want to score.
  3. Call the sp_rxPredict function.
  4. Receive the results.

Here's...

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