updated getting started samples

Author: negust-microsoft

samples/features/r-services/gettingstarted/customerclustering/CustomerClustering.R renamed to samples/features/r-services/Getting-Started/Customer-Clustering/Customer Clustering.R

@@ -1,4 +1,9 @@
 
+
+
+# Define the connection string
+connStr <- paste("Driver=SQL Server;Server=", "MyServer", ";Database=", "tpcx1b", ";Trusted_Connection=true;", sep = "");
+
 # Input Query
 input_query <- "
 	SELECT
@@ -35,10 +40,6 @@ FROM
     GROUP BY sr_customer_sk
   ) returned ON ss_customer_sk=sr_customer_sk 
 "
-
-# Define the connection string
-connStr <- paste("Driver=SQL Server;Server=", "NELLIELAPTOP", ";Database=", "tpcx1b", ";Trusted_Connection=true;", sep = "");
-
 # Input customer data that needs to be classified
 customer_returns <- RxSqlServerData(sqlQuery = input_query,
                                         colClasses = c(customer = "numeric", orderRatio = "numeric", itemsRatio = "numeric", monetaryRatio = "numeric", frequency = "numeric"),
@@ -56,7 +57,6 @@ head(customer_data, n = 5);
 wss <- (nrow(customer_data) - 1) * sum(apply(customer_data, 2, var))
 for (i in 2:20) { 
 xt = kmeans(customer_data, centers = i)
-    print(xt$ifault)
 wss[i] <- sum(kms = kmeans(customer_data, centers = i)$withinss)
     }
 plot(1:20, wss, type = "b", xlab = "Number of Clusters", ylab = "Within groups sum of squares")

samples/features/r-services/gettingstarted/customerclustering/CustomerClustering.sql renamed to samples/features/r-services/Getting-Started/Customer-Clustering/Customer Clustering.sql

@@ -0,0 +1,70 @@
+# Build a predictive model with SQL Server R Services
+
+This sample provides custom reports for SQL Server R Services that can be viewed from SQL Server Management Studio. The reports can be used to view configuration information, resource usage, execution statistics, active sessions and other information about R Services.
+
+### Contents
+
+[About this sample](#about-this-sample)<br/>
+[Before you begin](#before-you-begin)<br/>
+[Sample details](#sample-details)<br/>
+[Related links](#related-links)<br/>
+
+
+<a name=about-this-sample></a>
+
+## About this sample
+
+Predictive modeling is a powerful way to add intelligence to your application. It enables applications to predict outcomes against new data.
+The act of incorporating predictive analytics into your applications involves two major phases: 
+model training and model operationalization.
+
+In this sample, you will learn how to create a predictive model in R and operationalize it with SQL Server 2016.
+
+Follow the step by step tutorial [here](http://aka.ms/sqldev/R) to walk through this sample.
+
+<!-- Delete the ones that don't apply -->
+- **Applies to:** SQL Server 2016 (or higher)
+- **Key features:**
+- **Workload:** SQL Server R Services
+- **Programming Language:** T-SQL, R
+- **Authors:** Nellie Gustafsson
+- **Update history:** Getting started tutorial for R Services
+
+<a name=before-you-begin></a>
+
+## Before you begin
+
+To run this sample, you need the following prerequisites.
+Section 1 in the [tutorial](http://aka.ms/sqldev/R) covers all prerequisites.
+
+**Software prerequisites:**
+
+<!-- Examples -->
+1. SQL Server 2016 (or higher) with R Services installed
+2. SQL Server Management Studio
+3. R IDE Tool like Visual Studio
+
+
+<a name=sample-details></a>
+## Sample Details
+
+### PredictiveModel.R
+
+The R script that generates a predictive model and uses it to predict rental counts
+
+### PredictiveModel.SQL
+
+Takes the R code in PredictiveModel.R and uses it inside SQL Server. Creating stored procedures for training and prediction.
+
+
+
+<a name=related-links></a>
+
+## Related Links
+<!-- Links to more articles. Remember to delete "en-us" from the link path. -->
+
+For additional content, see these articles:
+
+[SQL Server R Services - Upgrade and Installation FAQ](https://msdn.microsoft.com/en-us/library/mt653951.aspx)
+
+[Other SQL Server R Services Tutorials](https://msdn.microsoft.com/en-us/library/mt591993.aspx)

samples/features/r-services/Getting-Started/Customer-Clustering/README.md

@@ -0,0 +1,70 @@
+# Build a predictive model with SQL Server R Services
+
+This sample provides custom reports for SQL Server R Services that can be viewed from SQL Server Management Studio. The reports can be used to view configuration information, resource usage, execution statistics, active sessions and other information about R Services.
+
+### Contents
+
+[About this sample](#about-this-sample)<br/>
+[Before you begin](#before-you-begin)<br/>
+[Sample details](#sample-details)<br/>
+[Related links](#related-links)<br/>
+
+
+<a name=about-this-sample></a>
+
+## About this sample
+
+Predictive modeling is a powerful way to add intelligence to your application. It enables applications to predict outcomes against new data.
+The act of incorporating predictive analytics into your applications involves two major phases: 
+model training and model operationalization.
+
+In this sample, you will learn how to create a predictive model in R and operationalize it with SQL Server 2016.
+
+Follow the step by step tutorial [here](http://aka.ms/sqldev/R) to walk through this sample.
+
+<!-- Delete the ones that don't apply -->
+- **Applies to:** SQL Server 2016 (or higher)
+- **Key features:**
+- **Workload:** SQL Server R Services
+- **Programming Language:** T-SQL, R
+- **Authors:** Nellie Gustafsson
+- **Update history:** Getting started tutorial for R Services
+
+<a name=before-you-begin></a>
+
+## Before you begin
+
+To run this sample, you need the following prerequisites.
+Section 1 in the [tutorial](http://aka.ms/sqldev/R) covers all prerequisites.
+
+**Software prerequisites:**
+
+<!-- Examples -->
+1. SQL Server 2016 (or higher) with R Services installed
+2. SQL Server Management Studio
+3. R IDE Tool like Visual Studio
+
+
+<a name=sample-details></a>
+## Sample Details
+
+### PredictiveModel.R
+
+The R script that generates a predictive model and uses it to predict rental counts
+
+### PredictiveModel.SQL
+
+Takes the R code in PredictiveModel.R and uses it inside SQL Server. Creating stored procedures for training and prediction.
+
+
+
+<a name=related-links></a>
+
+## Related Links
+<!-- Links to more articles. Remember to delete "en-us" from the link path. -->
+
+For additional content, see these articles:
+
+[SQL Server R Services - Upgrade and Installation FAQ](https://msdn.microsoft.com/en-us/library/mt653951.aspx)
+
+[Other SQL Server R Services Tutorials](https://msdn.microsoft.com/en-us/library/mt591993.aspx)