Hi All,
I have a txt file to read into R. The size of it is about 500MB.
This txt file is produced by calling write.table(M, file "xxx.txt"),
where M is a large matrix
After running MM = read.table("xxx.txt"), the R gui keeps a cpu
core/thread fully occupied forever.
64 bit R with 16GB RAM on Win7 64, i5 cpu should be capable. So if
anyone knows the reason, that will be appreciated.
Thank you for any advice.
Best wishes,
Jie
Jie <jimmycloud <at> gmail.com> writes: [snip]> I have a txt file to read into R. The size of it is about 500MB. > This txt file is produced by calling write.table(M, file > "xxx.txt"), where M is a large matrix > After running MM = read.table("xxx.txt"), the R gui keeps a cpu > core/thread fully occupied forever. > 64 bit R with 16GB RAM on Win7 64, i5 cpu should be capable.[snip] Take a look at http://stackoverflow.com/questions/1727772/ quickly-reading-very-large-tables-as-dataframes-in-r/ (URL broken to make gmane happy)
> -----Original Message----- > I have a txt file to read into R. The size of it is about 500MB. > This txt file is produced by calling write.table(M, file = > "xxx.txt"), where M is a large matrix After running MM = > read.table("xxx.txt"), the R gui keeps a cpu core/thread > fully occupied forever. > 64 bit R with 16GB RAM on Win7 64, i5 cpu should be capable. > So if anyone knows the reason, that will be appreciated. > Thank you for any advice. >A look at the ?read.table section on 'memory usage' may help. In particular, specifying colClasses as numeric is recommended. S Ellison ******************************************************************* This email and any attachments are confidential. Any use...{{dropped:8}}