SLOW split() function
I tried this:
library(data.table)
N <- 1000
T <- N*10
d <- data.table(gp= rep(1:T, rep(N,T)), val=rnorm(N*T), key = 'gp')
dim(d)
[1] 10000000 2
# On my humble 8Gb system,
system.time(l <- d[, split(val, gp)])
user system elapsed 4.15 0.09 4.27 I wouldn't be surprised if there were a much faster way to do this operation in data.table since split() is a data frame operation. This is about as fast as Jim Holtman's suggestion: system.time(s <- split(seq_len(nrow(d)), d$gp)) user system elapsed 4.15 0.09 4.29 HTH, Dennis
On Mon, Oct 10, 2011 at 6:01 PM, ivo welch <ivo.welch at gmail.com> wrote:
dear R experts: ?apologies for all my speed and memory questions. ?I
have a bet with my coauthors that I can make R reasonably efficient
through R-appropriate programming techniques. ?this is not just for
kicks, but for work. ?for benchmarking, my [3 year old] Mac Pro has
2.8GHz Xeons, 16GB of RAM, and R 2.13.1.
right now, it seems that 'split()' is why I am losing my bet. ?(split
is an integral component of *apply() and by(), so I need split() to be
fast. ?its resulting list can then be fed, e.g., to mclapply().) ?I
made up an example to illustrate my ills:
? ?library(data.table)
? ?N <- 1000
? ?T <- N*10
? ?d <- data.table(data.frame( key= rep(1:T, rep(N,T)), val=rnorm(N*T) ))
? ?setkey(d, "key"); gc() ## force a garbage collection
? ?cat("N=", N, ". ?Size of d=", object.size(d)/1024/1024, "MB\n")
? ?print(system.time( s<-split(d, d$key) ))
My ordered input data table (or data frame; doesn't make a difference)
is 114MB in size. ?it takes about a second to create. ?split() only
needs to reshape it. ?this simple operation takes almost 5 minutes on
my computer.
with a data set that is larger, this explodes further.
am I doing something wrong? ?is there an alternative to split()?
sincerely,
/iaw
----
Ivo Welch (ivo.welch at gmail.com)
______________________________________________ R-help at 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.