Hello, I have R as a socket server that computes R code sent by some
scripts (the clients). These scrips send R code to generate models
(SVM). The problem is that first models are generated in less than one
second and one hour later, the same models are generated in more than
ten seconds (even training with same data). If I restart the server ,
then it works well (fast). I don't know if I have to free the memory
or something.
Here you have the code:
R server:
FSsocket <- function(){
continue = TRUE;
while(continue){
conn <- try(socketConnection(server = TRUE, port = 7890, blocking TRUE, open
= "ab"), silent = FALSE);
isOpened = !inherits(conn, "try-error");
isOpened = isOpened && isOpen(conn);
while(!isOpened){
Sys.sleep(1);
conn <- try(socketConnection(server = TRUE, port = 7890, blocking
= TRUE, open = "ab"), silent = FALSE);
isOpened = !inherits(conn, "try-error");
isOpened = isOpened && isOpen(conn);
}
print("Waitting for source");
srcFile = readLines(conn, n = 1)
print(srcFile)
continue = srcFile != "--close"
if(continue){
print("Executing source");
error <- try(source(srcFile), silent = FALSE);
if(inherits(error, "try-error")){
writeLines("ERROR", conn)
}
print("Sending confirmation")
writeLines("DONE", conn)
print("Closing connection")
}
close(conn)
}
}
FSsocket();
Model generator example:
library("class");
library("e1071");
dd = read.table("sampling/adapteddataSet");
attach(dd);
ddv = read.table("sampling/adaptedvalidationDataSet");
attach(ddv);
dd[,1] = factor(dd[,1]);
ddv[,1] = factor(ddv[,1]);
attach(dd);
tr_in = as.matrix(dd[,2:(1 + 1)]);
tr_out = dd[,1];
val_in = as.matrix(ddv[,2:(1 + 1)]);
val_out = ddv[,1];
t = tune(svm, kernel = "radial", train.x = tr_in, train.y = tr_out,
validation.x = val_in, validation.y = val_out,
range = list( gamma = 2^(-1:1), cost = 2^(2:4) ), tunecontrol
tune.control(sampling = "fix") )
z = t$best.model
save(z, file = "./models/1/20", compress=FALSE);
Thanks
Pau.
Hello, I am still having the same problem, even removing the objects (with rm()). I checked the memory allocated by R and it is constant (about 4.5%), so I have no idea of what is happening... Moreover in few minutes (15) the models are generated 5 times slower... restarting the server is the only (but not acceptable) solution I have. (I do not generate any graph and/or extra object) Pau 2006/3/25, pau carre <pau.carre at gmail.com>:> Hello, I have R as a socket server that computes R code sent by some > scripts (the clients). These scrips send R code to generate models > (SVM). The problem is that first models are generated in less than one > second and one hour later, the same models are generated in more than > ten seconds (even training with same data). If I restart the server , > then it works well (fast). I don't know if I have to free the memory > or something. > > Here you have the code: > R server: > FSsocket <- function(){ > continue = TRUE; > while(continue){ > conn <- try(socketConnection(server = TRUE, port = 7890, blocking > TRUE, open = "ab"), silent = FALSE); > isOpened = !inherits(conn, "try-error"); > isOpened = isOpened && isOpen(conn); > while(!isOpened){ > Sys.sleep(1); > conn <- try(socketConnection(server = TRUE, port = 7890, blocking > = TRUE, open = "ab"), silent = FALSE); > isOpened = !inherits(conn, "try-error"); > isOpened = isOpened && isOpen(conn); > } > print("Waitting for source"); > srcFile = readLines(conn, n = 1) > print(srcFile) > continue = srcFile != "--close" > if(continue){ > print("Executing source"); > error <- try(source(srcFile), silent = FALSE); > if(inherits(error, "try-error")){ > writeLines("ERROR", conn) > } > print("Sending confirmation") > writeLines("DONE", conn) > print("Closing connection") > } > close(conn) > } > } > FSsocket(); > > Model generator example: > library("class"); > library("e1071"); > dd = read.table("sampling/adapteddataSet"); > attach(dd); > ddv = read.table("sampling/adaptedvalidationDataSet"); > attach(ddv); > dd[,1] = factor(dd[,1]); > ddv[,1] = factor(ddv[,1]); > attach(dd); > tr_in = as.matrix(dd[,2:(1 + 1)]); > tr_out = dd[,1]; > val_in = as.matrix(ddv[,2:(1 + 1)]); > val_out = ddv[,1]; > t = tune(svm, kernel = "radial", train.x = tr_in, train.y = tr_out, > validation.x = val_in, validation.y = val_out, > range = list( gamma = 2^(-1:1), cost = 2^(2:4) ), tunecontrol > tune.control(sampling = "fix") ) > z = t$best.model > save(z, file = "./models/1/20", compress=FALSE); > > Thanks > Pau. >
I'm just taking wild guesses here, and I have no clue what could be the problem. - The timing you mentioned, I assume, is `wall clock' time? Have you checked whether the CPU time also increase, or just the wall clock time? - Perhaps you can use Rprof() to check which part of the computation is increasing from run to run? Andy From: pau carre> > Hello, I am still having the same problem, even removing the > objects (with rm()). I checked the memory allocated by R and > it is constant (about 4.5%), so I have no idea of what is > happening... Moreover in few minutes (15) the models are > generated 5 times slower... restarting the server is the only > (but not acceptable) solution I have. (I do not generate any > graph and/or extra object) Pau > > > 2006/3/25, pau carre <pau.carre at gmail.com>: > > Hello, I have R as a socket server that computes R code > sent by some > > scripts (the clients). These scrips send R code to generate models > > (SVM). The problem is that first models are generated in > less than one > > second and one hour later, the same models are generated in > more than > > ten seconds (even training with same data). If I restart > the server , > > then it works well (fast). I don't know if I have to free > the memory > > or something. > > > > Here you have the code: > > R server: > > FSsocket <- function(){ > > continue = TRUE; > > while(continue){ > > conn <- try(socketConnection(server = TRUE, port = 7890, > > blocking = TRUE, open = "ab"), silent = FALSE); > > isOpened = !inherits(conn, "try-error"); > > isOpened = isOpened && isOpen(conn); > > while(!isOpened){ > > Sys.sleep(1); > > conn <- try(socketConnection(server = TRUE, > port = 7890, > > blocking = TRUE, open = "ab"), silent = FALSE); > > isOpened = !inherits(conn, "try-error"); > > isOpened = isOpened && isOpen(conn); > > } > > print("Waitting for source"); > > srcFile = readLines(conn, n = 1) > > print(srcFile) > > continue = srcFile != "--close" > > if(continue){ > > print("Executing source"); > > error <- try(source(srcFile), silent = FALSE); > > if(inherits(error, "try-error")){ > > writeLines("ERROR", conn) > > } > > print("Sending confirmation") > > writeLines("DONE", conn) > > print("Closing connection") > > } > > close(conn) > > } > > } > > FSsocket(); > > > > Model generator example: > > library("class"); > > library("e1071"); > > dd = read.table("sampling/adapteddataSet"); > > attach(dd); > > ddv = read.table("sampling/adaptedvalidationDataSet"); > > attach(ddv); > > dd[,1] = factor(dd[,1]); > > ddv[,1] = factor(ddv[,1]); > > attach(dd); > > tr_in = as.matrix(dd[,2:(1 + 1)]); > > tr_out = dd[,1]; > > val_in = as.matrix(ddv[,2:(1 + 1)]); > > val_out = ddv[,1]; > > t = tune(svm, kernel = "radial", train.x = tr_in, train.y = tr_out, > > validation.x = val_in, validation.y = val_out, > > range = list( gamma = 2^(-1:1), cost = 2^(2:4) ), > > tunecontrol = tune.control(sampling = "fix") ) z = t$best.model > > save(z, file = "./models/1/20", compress=FALSE); > > > > Thanks > > Pau. > > > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > >