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I would like to know how i could handle the data export with R
My dataset is more than 10millions line.
I know that one export is limitted to 150k.
So I write the following program to split the data into chuncks of data frame to be exported.
I am getting only the first 150k and the second file is only 1 row.
Could you help me handle this?
numBreaks <- nrow(dataset)%/%150000 + 1
setwd("D:/test/")
for( i in seq(numBreaks)){
filename = paste("test",i, sep="_")
filename = paste(filename,"csv",sep=".")
smallDAT <- dataset[((i-1)*150000+1): (min(nrow(dataset), i*150000)), ]
write.table (smallDAT , file =filename, sep =",", row.names = FALSE)
}
Solved! Go to Solution.
Hi @Anonymous,
R visuals in Power BI Desktop has a few limitations:
Data size limitations – data used by the R visual for plotting is limited to 150,000 rows. If more than 150,000 rows are selected, only the top 150,000 rows are used and a message is displayed on the image.
Considering this limitation which is the limit on all R-scripts at the moment on Power BI Desktop(For example, in your program above, the nrow(dataset) will always return 150000 when the dataset is more than 150,000 rows.), I don't think it is possible to break this limitation currently. ![]()
Regards
Hi @Anonymous,
R visuals in Power BI Desktop has a few limitations:
Data size limitations – data used by the R visual for plotting is limited to 150,000 rows. If more than 150,000 rows are selected, only the top 150,000 rows are used and a message is displayed on the image.
Considering this limitation which is the limit on all R-scripts at the moment on Power BI Desktop(For example, in your program above, the nrow(dataset) will always return 150000 when the dataset is more than 150,000 rows.), I don't think it is possible to break this limitation currently. ![]()
Regards
Thank you very much.
It is a really big problem for us now....
I hope it will be solved soon. At least the export to csv should not have limit
it's worth saying that you don't have to use Power BI to be your R environment, you can just use R-studio and you'll probably be fine.
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