Re: [R] scan() vs readChar() speed
Thanks; I did not notice an appreciable difference between scan() and
scan(what=double()) in this example.
Adding to my confusion, I noted a strange and apparently systematic
discrepency between the timing results when the code is run within
R.app, within emacs, or from a terminal. Any idea what might be
causing this?
Thanks,
baptiste
On 2 April 2012 11:04, Duncan Murdoch wrote:
> On 12-04-01 2:58 AM, baptiste auguie wrote:
>>
>> Dear list,
>>
>> I am trying to find a fast solution to read moderately large (1 -- 10
>> million entries) text files containing only tab-delimited numeric
>> values. My test file is the following,
>>
>> nr<- 1000
>> nc<- 5000
>>
>> m<- matrix(round(rnorm(nr*nc),3),nr=nr)
>> write.table(m, file = "a.txt", append=FALSE,
>> row.names = FALSE, col.names = FALSE)
>>
>>
>> scan() is faster than read.table(), as expected, but still quite slow
>> compared to Matlab for example. Based on archived discussions on this
>> list and Stack Overflow, I tried readChar(); it's really fast.
>> However, it returns a long character string, where I really want
>> numeric values. I can use as.numeric(strsplit()), but to my complete
>> surprise it is faster to run scan() on this text string. Consider the
>> following comparison (I use the command line wc to optimize the memory
>> allocation),
>
>
> Tell it the types of the columns, and it will go a bit faster.
>
> Duncan Murdoch
>
>>
>> load_file1<- function(f){
>> ## ask wc the number of words
>> n<- scan(textConnection(system(paste("wc -w ", f), intern=TRUE)),
>> what=list(integer(), character()), quiet=TRUE)[[1]]
>> all<- scan(f, nmax=n, quiet=TRUE)
>> invisible(all)
>> }
>>
>> load_file2<- function(f){
>> ## ask wc the number of characters
>> n<- scan(textConnection(system(paste("wc -m ", f), intern=TRUE)),
>> what=list(integer(), character()), quiet=TRUE)[[1]]
>> tc<- textConnection(readChar(f, n))
>> all<- scan(tc, quiet=TRUE, multi.line = FALSE)
>> close(tc)
>> invisible(all)
>> }
>>
>>
>> system.time(a<- load_file1("a.txt"))
>> ## user system elapsed
>> ## 7.805 0.138 8.026
>> system.time(b<- load_file2("a.txt"))
>> ## user system elapsed
>> ## 2.182 0.301 2.538
>> all.equal(a, b)
>> ##> [1] TRUE
>>
>>
>> Could someone explain to me why it is faster to scan a textConnection
>> than the original file? Have I missed a better solution?
>>
>> Thanks,
>>
>> baptiste
>>
>> sessionInfo()
>> R version 2.15.0 RC (2012-03-29 r58868)
>> Platform: i386-apple-darwin9.8.0/i386 (32-bit)
>>
>> locale:
>> [1] C
>>
>> attached base packages:
>> [1] stats graphics grDevices utils datasets methods base
>>
>> __
>> 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.
>
>
__
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.
Re: [R] scan() vs readChar() speed
On 12-04-01 2:58 AM, baptiste auguie wrote:
Dear list,
I am trying to find a fast solution to read moderately large (1 -- 10
million entries) text files containing only tab-delimited numeric
values. My test file is the following,
nr<- 1000
nc<- 5000
m<- matrix(round(rnorm(nr*nc),3),nr=nr)
write.table(m, file = "a.txt", append=FALSE,
row.names = FALSE, col.names = FALSE)
scan() is faster than read.table(), as expected, but still quite slow
compared to Matlab for example. Based on archived discussions on this
list and Stack Overflow, I tried readChar(); it's really fast.
However, it returns a long character string, where I really want
numeric values. I can use as.numeric(strsplit()), but to my complete
surprise it is faster to run scan() on this text string. Consider the
following comparison (I use the command line wc to optimize the memory
allocation),
Tell it the types of the columns, and it will go a bit faster.
Duncan Murdoch
load_file1<- function(f){
## ask wc the number of words
n<- scan(textConnection(system(paste("wc -w ", f), intern=TRUE)),
what=list(integer(), character()), quiet=TRUE)[[1]]
all<- scan(f, nmax=n, quiet=TRUE)
invisible(all)
}
load_file2<- function(f){
## ask wc the number of characters
n<- scan(textConnection(system(paste("wc -m ", f), intern=TRUE)),
what=list(integer(), character()), quiet=TRUE)[[1]]
tc<- textConnection(readChar(f, n))
all<- scan(tc, quiet=TRUE, multi.line = FALSE)
close(tc)
invisible(all)
}
system.time(a<- load_file1("a.txt"))
## user system elapsed
## 7.805 0.138 8.026
system.time(b<- load_file2("a.txt"))
## user system elapsed
## 2.182 0.301 2.538
all.equal(a, b)
##> [1] TRUE
Could someone explain to me why it is faster to scan a textConnection
than the original file? Have I missed a better solution?
Thanks,
baptiste
sessionInfo()
R version 2.15.0 RC (2012-03-29 r58868)
Platform: i386-apple-darwin9.8.0/i386 (32-bit)
locale:
[1] C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
__
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.
__
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.
[R] scan() vs readChar() speed
Dear list,
I am trying to find a fast solution to read moderately large (1 -- 10
million entries) text files containing only tab-delimited numeric
values. My test file is the following,
nr <- 1000
nc <- 5000
m <- matrix(round(rnorm(nr*nc),3),nr=nr)
write.table(m, file = "a.txt", append=FALSE,
row.names = FALSE, col.names = FALSE)
scan() is faster than read.table(), as expected, but still quite slow
compared to Matlab for example. Based on archived discussions on this
list and Stack Overflow, I tried readChar(); it's really fast.
However, it returns a long character string, where I really want
numeric values. I can use as.numeric(strsplit()), but to my complete
surprise it is faster to run scan() on this text string. Consider the
following comparison (I use the command line wc to optimize the memory
allocation),
load_file1 <- function(f){
## ask wc the number of words
n <- scan(textConnection(system(paste("wc -w ", f), intern=TRUE)),
what=list(integer(), character()), quiet=TRUE)[[1]]
all <- scan(f, nmax=n, quiet=TRUE)
invisible(all)
}
load_file2 <- function(f){
## ask wc the number of characters
n <- scan(textConnection(system(paste("wc -m ", f), intern=TRUE)),
what=list(integer(), character()), quiet=TRUE)[[1]]
tc <- textConnection(readChar(f, n))
all <- scan(tc, quiet=TRUE, multi.line = FALSE)
close(tc)
invisible(all)
}
system.time(a <- load_file1("a.txt"))
## user system elapsed
## 7.805 0.138 8.026
system.time(b <- load_file2("a.txt"))
## user system elapsed
## 2.182 0.301 2.538
all.equal(a, b)
## > [1] TRUE
Could someone explain to me why it is faster to scan a textConnection
than the original file? Have I missed a better solution?
Thanks,
baptiste
sessionInfo()
R version 2.15.0 RC (2012-03-29 r58868)
Platform: i386-apple-darwin9.8.0/i386 (32-bit)
locale:
[1] C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
__
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.
