Refactored ML samples

Author: uc-msft

samples/features/sql-big-data-cluster/machine-learning/README.md

@@ -1,7 +1,9 @@
-# Machine learning in SQL Server 2019 big data cluster
+# Machine Learning in SQL Server 2019 big data cluster
 
 ## SQL Server Machine Learning Services
 
+SQL Server 2016 added capability to run R script 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. You can now run R, Python or Java code from T-SQL in SQL Server 2019 on Windows or Linux or SQL Server 2019 big data cluster.
+
 [sql](sql)
 
 SQL Server machine learning services samples showing R, Python & Java support.

samples/features/sql-big-data-cluster/machine-learning/sql/README.md

@@ -1,23 +1,17 @@
-# SQL Server Machine Learning Services on SQL Master instance
+# SQL Server Machine Learning Services
 
-[book-click-prediction-r.sql](book-click-prediction-r.sql/)
+SQL Server 2016 added capability to run R script 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.
 
-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.
+**Applies to: SQL Server 2016+, SQL Server 2019, SQL Server 2019 big data cluster**
 
-[book-click-prediction-py.sql](book-click-prediction-py.sql/)
+[r](r)
 
-In this example, we are building a machine learning model using Python 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.
+This folder contains the R samples.
 
-[book-click-prediction-partitioned-r.sql](book-click-prediction-partitioned-r.sql/)
+[python](python)
 
-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.
+This folder contains the R samples.
 
-[book-click-prediction-partitioned-py.sql](book-click-prediction-partitioned-py.sql/)
+[java](java)
 
-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 Python script per partition. So we will modify the training script to train model per group of users based on credit rating. The Python script will produce N models for the same input data set.
-
-### Instructions
-
-1. Connect to SQL Server Master instance.
-
-1. Execute the SQL script.
+This folder contains the Java samples.

samples/features/sql-big-data-cluster/machine-learning/sql/python/README.md

@@ -0,0 +1,21 @@
+# SQL Server Machine Learning Services
+
+SQL Server 2016 added capability to run R script 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.
+
+[book-click-prediction-py.sql](book-click-prediction-py.sql/)
+
+**Applies to: SQL Server 2017+, SQL Server 2019, SQL Server 2019 big data cluster**
+
+In this example, we are building a machine learning model using Python 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-py.sql](book-click-prediction-partitioned-py.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 Python script per partition. So we will modify the training script to train model per group of users based on credit rating. The Python script will produce N models for the same input data set.
+
+## Instructions
+
+1. Connect to SQL Server or SQL Server Master instance.
+
+1. Execute the SQL script.

…book-click-prediction-partitioned-py.sql …book-click-prediction-partitioned-py.sqlsamples/features/sql-big-data-cluster/machine-learning/sql/book-click-prediction-partitioned-py.sql renamed to samples/features/sql-big-data-cluster/machine-learning/sql/python/book-click-prediction-partitioned-py.sql samples/features/sql-big-data-cluster/machine-learning/sql/book-click-prediction-partitioned-py.sql renamed to samples/features/sql-big-data-cluster/machine-learning/sql/python/book-click-prediction-partitioned-py.sql

@@ -0,0 +1,21 @@
+# SQL Server Machine Learning Services
+
+SQL Server 2016 added capability to run R script 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.
+
+[book-click-prediction-r.sql](book-click-prediction-r.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](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.
+
+## Instructions
+
+1. Connect to SQL Server or SQL Server Master instance.
+
+1. Execute the SQL script.