CODEWITHSUNDEEP
rweb-servicesazure-machine-learning-service
Fernando Doreto
Fernando Doreto

Reputation: 13

LibraryExecutionError - testing a web service published via Rstudio RRS feed

I built a model in Rstudio, published in Azure ML Studio a web service using "AzureML" R package. When testing the web service on Azure ML Studio, I encountered an error:

Error: AzureML returns error code:
HTTP status code : 400
AzureML error code : LibraryExecutionError
Module execution encountered an internal library error.
The following error occurred during evaluation of R script: R_tryEval: return error: Error: bad restore file magic number (file may be corrupted) -- no data loaded

Do you have any insights on how to solve such issue? Am I missing some important code in the R script?

The model I used was a RandomForest to predicted Species on Iris dataset

# Iris dataset
df = iris
set.seed(100);

index = createDataPartition(df$Species, p = 0.7, list = FALSE)
ML.train = df[index,]; 
ML.test = df[-index,];  rm(index)

library(randomForest)
model = randomForest::randomForest(Species ~., data = ML.train)

mypredict = function(newdata) {
      require(randomForest)
      predict(model, newdata, type = "response")
}

# Create workspace
wsObj = AzureML::workspace(id = "my Id", auth = "my token")  # I omitted on purpose my Id and my token values

# Publishing
library(devtools)
library(AzureML)
api = AzureML::publishWebService(ws = wsObj,
                                 fun = mypredict,
                                 name = "IrisWebService",
                                 inputSchema = ML.test %>% select(-Species) )

Upvotes: 1

Views: 61

Answers (1)

Ram
Ram

Reputation: 2754

AzureML for RStudio is now not supported as the package is removed from CRAN repository from 2019-07-29. Azure ML studio with this package will not work as the package(AzureML) is removed.

Azure Machine Learning SDK for R can be Downloaded from CRAN at https://cloud.r-project.org/web/packages/azuremlsdk/index.html

Upvotes: 0

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