Users forget how much is an OS service. This is OS X not R being slow.
On a recent Linux box it takes about 90s.
But at least you can easily parallelize it: see ?pvec in package
parallel for one way to do this (and one way not to).
If the file contain a high proportion of duplicates, making a factor and
converting the levels will help.
On 27/09/2012 18:24, Fisher Dennis wrote:
R 2.15.1
OS X.7.4
Colleagues,
I have a large dataset (27773536 records, the file is several GB) that contains
a column of date / time entries in the format:
"2/1/2011 13:25:01"
I need to convert these to numeric values (ideally in seconds; the origin
[e.g., 1970-01-01] is not important).
I am using:
as.numeric(strptime(DATA$DATADTM, "%m/%d/%Y %H:%M:%S"))
It takes 21 minutes to execute this step on a dual quad-core Mac with 12 GB RAM
(it is appreciably slower on other Mac's including a new i5 iMac).
Are there other time formatting functions or strategies that would be faster?
Sample data:
TIMECOL <- rep("2/1/2011 13:25:01", 100)
Any tips would be appreciated.
Dennis
Dennis Fisher MD
P < (The "P Less Than" Company)
Phone: 1-866-PLessThan (1-866-753-7784)
Fax: 1-866-PLessThan (1-866-753-7784)
www.PLessThan.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.
--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
______________________________________________
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.
