R script error on Azure machine learning (Error 1000)

Question

When I try to connect my data source to the "Execute R script" then I run the experiment, the experiment does not run and I get this error message "Execute R Script Error
RPackage library exception: Attempting to obtain R output before invoking execution process . ( Error 1000 )"

Please advice me how to solve this error and In general how to connect my datasets on Azure machine learning for D365 demand forecasting.

Answer 1

You use the import data module to import data from local files or online sources. The Azure AI gallery is also a great resource to view sample experiments. Here's a forecasting model for Dynamics 365 example. Regarding the error message, can you please share the module that generated this error as well as more details about the error by viewing the output log (detailed error message is displayed in the last two lines of the window)?

Answer 2

Hi there, if you are uploading a local file:

• I recommend that you import a .csv file instead of excel
• You can connect from csv to Execute R Script module directly.
• In some cases, you may need to Edit Metadata and then Convert to Dataset
• Check the data output by right clicking the module and select Dataset > Visualize to ensure the data is in expected format
• Connect your .csv file to the Execute R Script module and run the experiment (start with simple R commands and see if it runs)
• Ensure no errors before deploying the web service
• As for web service input/output, you specify those when you want to deploy your model

You may find this sample experiment helpful (click open in studio) and view import data and Execute R script modules respectively. . Hope this helps.

Answer 3

It was just a simple CSV file.

I need the Azure ML to analyze the data in the Excel file or the CSV I attach to the experiment and generate the forecast based on it not based on the historical transactions in D365, I will tell you the steps I know as I still a beginner and kindly provide me the correct steps:
1- I will upload the sheet to my Azure studio library(it should be CSV format not normal Excel,right?)
2- Then I will choose the sheet from "my saved data sets" and drag it into the experiment.
3- Then I will drag "convert to dataset" into the experiment and I will connect the sheet to it then connect the "convert to dataset" to the "Execute R script" (Sheet>>Connected to "convert to dataset">>connected to "Execute R script").
4- Then I will run the experiment then deploy the service.

Are those correct steps? and should I remove "Web service input" to only analyze and generate based on the data in the sheet not the data in the D365?

Kindly advice @GiftA-MSFT