My opinion is that you should be spending your effort on setting up a SQL
engine and importing it there. If you have 32GB of RAM your current direction
might work, but working with sampled data rather than population data seems
pretty typical for statistical analysis.
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Sent from my phone. Please excuse my brevity.
RHelpPlease <rrum...@trghcsolutions.com> wrote:
>Hi there,
>I wish to read a 9.6GB .DAT file into R (64-bit R on 64-bit Windows
>machine)
>- to then delete a substantial number of rows & then convert to a .csv
>file.
>Upon the first attempt the computer crashed (at some point last night).
>
>I'm rerunning this now & am closely monitoring Processor/CPU/Memory.
>
>Apart from this crash being a computer issue alone (possibly), is R
>equipped
>to handle this much data? I read up on the FAQs page that 64-bit R can
>handle larger data sets than 32-bit.
>
>I'm using the read.fwf function to read in the data. I don't have
>access to
>a database program (SQL, for instance).
>
>Advice is most appreciated!
>
>
>
>--
>View this message in context:
>http://r.789695.n4.nabble.com/Reading-in-9-6GB-DAT-File-OK-with-64-bit-R-tp4457220p4457220.html
>Sent from the R help mailing list archive at Nabble.com.
>
>______________________________________________
>R-help@r-project.org mailing list
>https://stat.ethz.ch/mailman/listinfo/r-help
>PLEASE do read the posting guide
>http://www.R-project.org/posting-guide.html
>and provide commented, minimal, self-contained, reproducible code.
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and provide commented, minimal, self-contained, reproducible code.
