SQL Server 2016 added support for running R scripts from T-SQL. SQL Server 2017 added support for running Python scripts from T-SQL. SQL Server 2019 adds support for running Java code from T-SQL.
Applies to: SQL Server 2016+, SQL Server 2019, SQL Server 2019 big data cluster
In this example, we are building a machine learning model using R and a logistic regression algorithm for a recommendation engine on an online store. Based on existing users' click pattern online and their interest in other categories and demographics, we are training a machine learning model. This model will then be used to predict if the visitor is interested in a given item category using the T-SQL PREDICT function.
book-click-prediction-partitioned-r.sql
Applies to: SQL Server 2019, SQL Server 2019 big data cluster
In this example, we are leveraging the new partitioning support (SQL Server 2019) in sp_execute_external_script to partition the input data and run the R script per partition. So we will modify the training script to train model per group of users based on credit rating. The R script will produce N models for the same input data set.
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Connect to SQL Server or SQL Server Master instance.
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Execute the SQL script.