Hi, all.
I began to migrate my R codes from Windows to Linux and surprised me
with an old question. I simplified the problem and made a little test to
compare times at same
computer and the Linux time is worse (not so little) than Windows time:
28 vs 53 seconds.
I make an example (below) to facilitate all to see the difference.
I also build from source (it's my first time) a version of R to compare with
the distributed (compiled) R version. The times are similar to the other Linux
version.
I supposed R on Linux should be faster (32 and 64 bit) than windows version. Is
this difference because 64 bit R version is slower than 32 bits one? I started
the machine in both sittuations and checked free memory.
Tecnichal details:
Machine: Intel Core 2 Duo DDR2 4 Gb RAM
Windows version: XP Professional - 32 bits
R version: 2.9* binaries
Linux version: Ubuntu 8* (Hardy) - 64 bits
R version: 2.9* binaries and 2.9* compiled from source
Thanks to all,
Cezar Freitas
#code
N = 50000
n = 15000
#makes data
dad = as.data.frame(cbind(sample(N,N,replace=FALSE), rpois(N,30)))
names(dad) = c("id","age")
aux = as.data.frame(cbind(sample(N,n,replace=FALSE), round(runif(n),4)))
names(aux) = c("id","score")
#calculates time
set.seed(790) #to be equal to everyone
system.time({
dad$score = 0
subdad = subset(dad, id%in%aux$id)
for(k in 1:(dim(subdad)[1])){
temp = aux$score[aux$id==subdad$id[k]]
if(length(temp)) subdad$score[k] = temp
}
})
#windows time
# user system elapsed
# 27.81 0.00 27.82
#linux usual compilation time
# user system elapsed
# 52.635 0.016 52.748
#linux (my compilation) time
# user system elapsed
# 52.567 0.016 52.588
#==============END OF CODE
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