Utilising R in SSRS

With the release of SQL Server 2016 CTP3 the inclusion of R has been a powerful and welcome addition. As R can now be directly queried from inside SQL Server Management Studio (SSMS) one can now use the data outputs from R in SQL Server Reporting Services (SSRS) thereby utilising the power of R in the convenience of SSRS.

This blog will guide you through the process of creating a simple report in SSRS using data from R.

As demonstrated in a previous blog, it is very easy to begin using R within SQL Server and this is no different.

First of you will need your SQL R Script, for which I’m producing a simple K Means cluster of employees in the Adventure Work Data Warehouse. Then you will want to wrap that query inside a stored procedure.

CREATE PROCEDURE dbo.spKMeansEmployee



      EXECUTE sp_execute_external_script

                   @language = N’R’,

                   @script = N’ClusterCount <- 4;

                                      df <- data.frame(InputDataSet);

                                      ClusterFeatures <- data.frame(df$BaseRate, df$VacationHours, df$SickLeaveHours, df$SalaryFlag);

                                      ClusterResult <- kmeans(ClusterFeatures, centers = ClusterCount, iter.max = 10)$cluster;

                                      OutputDataSet <- data.frame(df, ClusterResult);’,

                   @input_data_1 = N’SELECT





                                                   CAST(SalariedFlag AS VARCHAR(1)) AS SalaryFlag

                                            FROM dbo.DimEmployee;’


                                      BaseRate MONEY NOT NULL,

                                      VacationHours INT NOT NULL,

                                      SickLeaveHours INT NOT NULL,

                                      SalaryFlag VARCHAR(1) NOT NULL,

                                      ClusterResult INT NOT NULL




The next step is to create a new report in Visual Studio and add a new Data Source.

Then create a dataset.

And link that dataset to a new report.

Then build the report how you want, using that dataset. This is the quick output I’ve opted for as you can quickly analyse employees based on the cluster they are in.

As you can see, and hopefully reproduce, it’s a very quick and relatively easy process that allows you to make business decisions by utilising the combined powerful capabilities of R and SQL.