Hi, Yes dplyr syntax is quite equivalent to SQL, although it is faster. Another alternative you could consider is to use *data.table* which has a syntax very similar to the way you select subset within a data.frame and in terms of performance is faster (a bit) than sqldf.
You can get some idea of how to work with it here: http://stackoverflow.com/questions/1727772/quickly-reading-very-large-tables-as-dataframes-in-r Regards, Carlos Ortega www.qualityexcellence.es 2014-05-06 11:12 GMT+02:00 Dr Eberhard Lisse <e...@lisse.na>: > Jeff > > It's in MySQL, at the moment roughly 1.8 GB, if I pull it into a > dataframe it saves to 180MB. I work from the dataframe. > > But, it's not only a size issue it's also a speed issue and hence I > don't care what I am going to use, as long as it is fast. > > sqldf is easy to understand for me but it takes ages. If > alternatives were roughly similar in speed I would remain with > sqldf. > > dplyr sounds faster, and promising, but the intrinsic stuff is > way beyond me (elderly Gynaecologist) on the learning curve... > > el > > on 2014-05-06, 09:41 Jeff Newmiller said the following: > > In what format is this "growing" data stored? CSV? SQL? Log > > textfile? You say you don't want to use sqldf, but you haven't > > said what you do want to use. > > ______________________________________________ > 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. > -- Saludos, Carlos Ortega www.qualityexcellence.es [[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.
