github/sql-server-samples
1
0
Fork 0
mirror of https://github.com/Microsoft/sql-server-samples.git synced 2025-12-08 14:58:54 +00:00
Code Issues Releases Wiki Activity

Update README.md

Browse Source
This commit is contained in:
Amit Banerjee
2016-12-30 20:13:33 -08:00
committed by GitHub
parent e35c705823
commit ac38a44dd9
1 changed files with 10 additions and 1 deletions
Download Patch File Download Diff File Expand all files Collapse all files

11
samples/features/r-services/Loan Classification/README.md
View File

@ -1,2 +1,11 @@
## Loan Classification using SQL Server 2016
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.
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.
**Scripts**
* 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