For the IT Administrator
This solution demonstrates the code with 1,000,000 borrowers for developing the model. Using HDInsight Spark clusters makes it simple to extend to very large data, both for training and scoring. As you increase the data size you may want to add more nodes but the code itself remains exactly the same.
This solution uses:
HDInsight Spark cluster billing starts once a cluster is created and stops when the cluster is deleted. See these instructions for important information about deleting a cluster and re-using your files on a new cluster.
Access RStudio on the cluster edge node by using the url of the form
http://CLUSTERNAME.azurehdinsight.net/rstudio Run the script development_main.R followed by deployment_main.R to perform all the steps of the solution.
The following data files are available in the Loans/Data directory in the storage account associated with the cluster:
|Loan.csv||Loan data with 100K rows of the simulated data used to build the end-to-end Loan Credit Risk Loan solution for SQL solution. (Larger data is generated via script for HDInsight solution.)|
|Borrower.csv||Borrower data with 100K rows of the simulated data used to build the end-to-end Loan Credit Risk for SQL solution. (Larger data is generated via script for HDInsight solution.)|
|Loan_Prod.csv||Loan data with 22 rows of the simulated data used in the Production pipeline|
|Borrower_Prod.csv||Borrower data with 22 rows of the simulated data used in the Production pipeline|
|LoanCreditRisk_Data_Dictionary.xlsx||Schema and description of the input tables and variables|