on/am 31.10.2013 09:12, Prof Brian Ripley wrote/hat geschrieben:
On 30/10/2013 21:15, William Dunlap wrote:I have to defer to others for policy declarations like how long the current format used by load and save should be readable.You could also ask how long R will last .... R can still read (but not write) save() formats used in the 1990's. We would expect R to be able to read saves since R 1.0.0 for as long as R exists. And as R is Open Source, you would be able to compile it and dump the objects you want for as long as suitable compilers and OSes exist .... And of course R is not the only application which will read the format. There is no guarantee that source() will be able to parse dumps from earlier versions of R, and that has not always been true. People commenting on parse() speed should note the NEWS for R-devel: • The parser has been modified to use less memory.
Thank you for the hint.It appears to me that source() in R-devel performs at about the same speed as in R 2.15.2.
Bill Dunlap Spotfire, TIBCO Software wdunlap tibco.com-----Original Message----- From: Heinz Tuechler [mailto:tuech...@gmx.at] Sent: Wednesday, October 30, 2013 1:43 PM To: William Dunlap Cc: Carl Witthoft; r-help@r-project.org Subject: Re: [R] big speed difference in source btw. R 2.15.2 and R 3.0.2 ? Best thanks for confirming my impression. I use dump for storing large data.frames with a number of attributes for each variable. save/load is much faster, but I am unsure, if such files will be readable by R versions years later. What format/functions would you suggest for data storage/transfer between different (future) R versions? best regards, Heinz on/am 30.10.2013 20:11, William Dunlap wrote/hat geschrieben:I see a big 2.15.2/3.0.2 speed difference in parse() (which is used by source()) when it is parsing long vectors of numeric data. dump/source has never been anefficientway of transferring data between different R session, but it is much worse now for long vectors. In 2.15.2 doubling the size of the vector (of lengths in the range 10^4 to 10^7) makes the time to parse go up by a factor of c. 2.1. In 3.0.2 that factor is more like 4.4. n elapsed-2.15.2 elapsed-3.0.2 2048 0.003 0.018 4096 0.006 0.065 8192 0.013 0.254 16384 0.025 1.067 32768 0.050 4.114 65536 0.100 16.236 131072 0.219 66.013 262144 0.808 291.883 524288 2.022 1285.265 1048576 4.918 NA 2097152 9.857 NA 4194304 22.916 NA 8388608 49.671 NA 16777216 101.042 NA 33554432 512.719 NA I tried this with 64-bit R on a Linux box. The NA's represent sizes that did not finish while I was at a 1 1/2 hour dentist's apppointment. The timing function was: test <- function(n = 2^(11:25)) { tf <- tempfile() on.exit(unlink(tf)) t(sapply(n, function(n){ dput(log(seq_len(n)), file=tf) print(c(n=n, system.time(parse(file=tf))[1:3])) })) } Bill Dunlap Spotfire, TIBCO Software wdunlap tibco.com-----Original Message----- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] OnBehalfOf Carl Witthoft Sent: Wednesday, October 30, 2013 5:29 AM To: r-help@r-project.org Subject: Re: [R] big speed difference in source btw. R 2.15.2 and R 3.0.2 ? Did you run the identical code on the identical machine, and did you verify there were no other tasks running which might have limited the RAM available to R? And equally important, did you run these tests in the reverse order (in case R was storing large objects from the first run, thus chewing up RAM)? Dear All, is it known that source works much faster in R 2.15.2 than in R 3.0.2 ? In the example below I observe e.g. for a data.frame with 10^7 rows the following timings: R version 2.15.2 Patched (2012-11-29 r61184) length: 1e+07 user system elapsed 62.04 0.22 62.26 R version 3.0.2 Patched (2013-10-27 r64116) length: 1e+07 user system elapsed 388.63 176.42 566.41 Is there a way to speed R version 3.0.2 up to the performance of R version 2.15.2? best regards, Heinz Tüchler example: sessionInfo() sample.vec <- c('source', 'causes', 'R', 'to', 'accept', 'its', 'input', 'from', 'the', 'named', 'file', 'or', 'URL', 'or', 'connection') dmp.size <- c(10^(1:7)) set.seed(37) for(i in dmp.size) { df0 <- data.frame(x=sample(sample.vec, i, replace=TRUE)) dump('df0', file='testdump') cat('length:', i, '\n') print(system.time(source('testdump', keep.source = FALSE, encoding=''))) } output for R version 2.15.2 Patched (2012-11-29 r61184):sessionInfo()R version 2.15.2 Patched (2012-11-29 r61184) Platform: x86_64-w64-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=German_Switzerland.1252 LC_CTYPE=German_Switzerland.1252 [3] LC_MONETARY=German_Switzerland.1252 LC_NUMERIC=C [5] LC_TIME=German_Switzerland.1252 attached base packages: [1] stats graphics grDevices utils datasets methods basesample.vec <-+ c('source', 'causes', 'R', 'to', 'accept', 'its', 'input', 'from', 'the', + 'named', 'file', 'or', 'URL', 'or', 'connection')dmp.size <- c(10^(1:7)) set.seed(37) for(i in dmp.size) {+ df0 <- data.frame(x=sample(sample.vec, i, replace=TRUE)) + dump('df0', file='testdump') + cat('length:', i, '\n') + print(system.time(source('testdump', keep.source = FALSE, + encoding=''))) + } length: 10 user system elapsed 0 0 0 length: 100 user system elapsed 0 0 0 length: 1000 user system elapsed 0 0 0 length: 10000 user system elapsed 0.02 0.00 0.01 length: 1e+05 user system elapsed 0.21 0.00 0.20 length: 1e+06 user system elapsed 4.47 0.04 4.51 length: 1e+07 user system elapsed 62.04 0.22 62.26output for R version 3.0.2 Patched (2013-10-27 r64116):sessionInfo()R version 3.0.2 Patched (2013-10-27 r64116) Platform: x86_64-w64-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=German_Switzerland.1252 LC_CTYPE=German_Switzerland.1252 [3] LC_MONETARY=German_Switzerland.1252 LC_NUMERIC=C [5] LC_TIME=German_Switzerland.1252 attached base packages: [1] stats graphics grDevices utils datasets methods basesample.vec <-+ c('source', 'causes', 'R', 'to', 'accept', 'its', 'input', 'from', 'the', + 'named', 'file', 'or', 'URL', 'or', 'connection')dmp.size <- c(10^(1:7)) set.seed(37) for(i in dmp.size) {+ df0 <- data.frame(x=sample(sample.vec, i, replace=TRUE)) + dump('df0', file='testdump') + cat('length:', i, '\n') + print(system.time(source('testdump', keep.source = FALSE, + encoding=''))) + } length: 10 user system elapsed 0 0 0 length: 100 user system elapsed 0 0 0 length: 1000 user system elapsed 0 0 0 length: 10000 user system elapsed 0.01 0.00 0.01 length: 1e+05 user system elapsed 0.36 0.06 0.42 length: 1e+06 user system elapsed 6.02 1.86 7.88 length: 1e+07 user system elapsed 388.63 176.42 566.41-- View this message in context: http://r.789695.n4.nabble.com/big-speed-difference-in-source-btw-R-2-15-2-and-R-3-0-2-tp4679314p4679346.html Sent from the R help mailing list archive at Nabble.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.______________________________________________ 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-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.
