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Loan Classification using SQL Server 2016 R Services#

Joseph Sirosh, Data Group Corporate Vice President, had shown during his keynote session how customers are able to achieve a scale up of 1 million predictions/sec using SQL Server 2016 R Services. This sample contains all the scripts required to emulate a similar setup using Lending Club data with SQL Server 2016 R Services and an Azure Data Science VM.


  • 1 - Create Database.sql - Creates the database, tables, stored procedures and other associated database objects required to get this sample going
  • 2 - ImportCSVData.ps1 - Imports the data from the CSV files, performs the transformations and transfers the data to the LoanStats table
  • 3 - Create Columnstore Index.sql - This script creates the non-clustered columnstore index which will be used during the loan scoring process
  • 4 - Create Model.sql - Creates the model which will be used to score the loans
  • 5 - Resource Governor Config.sql - Sample resource governor configuration used for creating the external resource pools
  • 6 - Score Loans.ps1 - PowerShell script to start parallel processes to score the loans
  • 7 - WhatIf.ps1 - PowerShell script to take an input for the increased interest rate and perform the WhatIf scenario scoring