Thanks. I will try break into pieces to analysis.
Kevin On Fri, Apr 26, 2013 at 4:38 PM, Ye Lin <ye...@lbl.gov> wrote: > I can not think of sth better. Maybe try read part of the data that you > want to analyze, basically break the large data set into pieces. > > > On Fri, Apr 26, 2013 at 10:58 AM, Ye Lin <ye...@lbl.gov> wrote: > >> Have you think of build a database then then let R read it thru that db >> instead of your desktop? >> >> >> On Fri, Apr 26, 2013 at 8:09 AM, Kevin Hao <rfans4ch...@gmail.com> wrote: >> >>> Hi all scientists, >>> >>> Recently, I am dealing with big data ( >3G txt or csv format ) in my >>> desktop (windows 7 - 64 bit version), but I can not read them faster, >>> thought I search from internet. [define colClasses for read.table, >>> cobycol >>> and limma packages I have use them, but it is not so fast]. >>> >>> Could you share your methods to read big data to R faster? >>> >>> Though this is an odd question, but we need it really. >>> >>> Any suggest appreciates. >>> >>> Thank you very much. >>> >>> >>> kevin >>> >>> [[alternative HTML version deleted]] >>> >>> ______________________________________________ >>> 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. >>> >> >> > [[alternative HTML version deleted]] ______________________________________________ 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.
