问题
I am a newbie to R, but I am aware that it chokes on "big" files. I am trying to read a 200MB data file. I have tried it in csv format and also converting it to tab delimited txt but in both cases I use up my 4GB of RAM before the file loads.
Is it normal that R would use 4GB or memory to load a 200MB file, or could there be something wrong with the file and it is causing R to keep reading a bunch of nothingness in addition to the data?
回答1:
From ?read.table
Less memory will be used if colClasses is specified as one of the six atomic vector classes.
...
Using nrows, even as a mild over-estimate, will help memory usage.
Use both of these arguments.
Ensure that you properly specify numeric for your numeric data. See here: Specifying colClasses in the read.csv
And do not under-estimate nrows.
If you're running 64-bit R, you might try the 32-bit version. It will use less memory to hold the same data.
See here also: Extend memory size limit in R
来源：https://stackoverflow.com/questions/14294217/reading-large-files-into-r