Thanks, very helpful. Is there some way to adjust those GC triggers in advance? -----Original Message----- From: Prof Brian Ripley [mailto:ripley at stats.ox.ac.uk] Sent: Thu 8/4/2005 4:15 PM To: Stone, Glenn (CMIS, North Ryde) Cc: r-help at stat.math.ethz.ch Subject: Re: [R] Odd timing behaviour in reading a file Please see the gcFirst argument to system.time, which you should set to TRUE for such timings. Your second run is paying to GC the results of the first, most likely. Beyond that, R adjusts its GC triggers based on usage, and when you first start using large objects the trigger levels will grow and generally things will speed up. Set gcinfo(TRUE) to watch what is happening.
On Thu, 4 Aug 2005, Glenn Stone wrote:
Hi all, please don't ask me why I tried this but....... I have observed some odd behaviour in the time taken to read a file. I tried searching the archives without much success, but that could be me. The first time I read a (60Mb) CSV file, takes a certain amount of time. The second time takes appreciably longer and the third and subsequent times very much shorter times. See below, $ R2.1.1 R : Copyright 2005, The R Foundation for Statistical Computing Version 2.1.1 (2005-06-20), ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. Natural language support but running in an English locale R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for a HTML browser interface to help. Type 'q()' to quit R.
system.time(temp <-
read.csv("Mapping50K_Xba240_annot.csv",header=TRUE, as.is=TRUE))
[1] 32.55 0.30 33.46 0.00 0.00
system.time(temp <-
read.csv("Mapping50K_Xba240_annot.csv",header=TRUE, as.is=TRUE))
[1] 45.32 0.24 45.72 0.00 0.00
system.time(temp <-
read.csv("Mapping50K_Xba240_annot.csv",header=TRUE, as.is=TRUE))
[1] 11.73 0.17 11.94 0.00 0.00
system.time(temp <-
read.csv("Mapping50K_Xba240_annot.csv",header=TRUE, as.is=TRUE))
[1] 8.58 0.28 8.96 0.00 0.00
system.time(temp <-
read.csv("Mapping50K_Xba240_annot.csv",header=TRUE, as.is=TRUE))
[1] 8.80 0.16 9.02 0.00 0.00
This is a relatively quiet opteron running redhat linux and using R2.1.1
The same pattern is repeatable, and occurs in R2.0.1 and on a Dell
laptop running Windows XP.
I guess it is probably something to do with the garbage collector? Can
anyone explain further? Particularly the first increase.
Thanks....
--
Glenn Stone
CSIRO Bioinformatics
http://www.bioinformatics.csiro.au
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Brian D. Ripley, ripley at 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