Sign in with Microsoft
Sign in or create an account.
Select a different account.
You have multiple accounts
Choose the account you want to sign in with.

This is a general memory allocation error. The usual problem is that Revolution R is trying to read too many rows at once from your data file to process the data in memory for a single chunk of data.

First try the following, to resolve the issue:

Set a small value for the argument 'rowsPerRead' in your rxImport() statement. Try a value of '10000'  or less. You may need to try different settings for

this to find a value that works well and imports the data as quickly as possible.


If this doesn't help and your csv file has a lot of columns, it can help to import the data 'x' columns at a time. For example, if your dataset as 5000 columns, you may want to import the data for 50 columns at a time and write out the data for 50 columns to a new XDF file and append to that existing XDF file.

Here is some sample R code to do that:

varNames <- readLines("mycsv.txt", n=1) 
colsPerRead <- 50   ## Set how many columns to read from the csv file at a time. You may want to initially set this to a larger value, say 100. 
numReadsFromFile <- length(varNames/colsPerRead)

for (i in 1:numReadsFromFile) 

 tempdf <- rxImport(inData = "C:/MyRData/data.csv", varsToKeep = paste(varNames[((i-1)*colsPerRead)+1:(((i-1)*colsPerRead)+1)+colsPerRead], sep = ","), 
 rowsPerRead = 10000) 
 rxDataFrameToXdf(data = tempdf, ouFile = "C:/MyRData/data.xdf", append = "cols") 

Need more help?

Want more options?

Explore subscription benefits, browse training courses, learn how to secure your device, and more.

Communities help you ask and answer questions, give feedback, and hear from experts with rich knowledge.

Was this information helpful?

What affected your experience?

Thank you for your feedback!