Memory not mapped #18
Description
This package has been quite useful for my research and thank the author for writing it. However, sometimes I experienced the following problem:
In short words, I have a function which calls biglasso, and I was trying to use mclapply function in the package parallel to have multiple cores to run lasso with same X (created by setupX) and different y.
Here is my function, I think procedures other than biglasso are unimportant:
if (k > 1) {
y <-sample(realy)
} else {
y <-realy
}
tryCatch( {
time <- system.time(
fit <- biglasso(X, y, family='gaussian', penalty.factor = penalty,
lambda.min = 0.0001, nlambda = 250)
)
print(time)
# do the "maxfrac" operation
coef = as.matrix(fit$beta)
coef[coef < 0] <- 0.0
coef = round(coef, digits = 6)
colnames(coef) = fit$lambda
if (k == 1) {
write.table(coef, file=paste(outfname, ".coef", sep=""), sep="\t")
}
norm_beta = scale(coef, center=FALSE, scale=colSums(coef))
beta_max = apply(norm_beta, 1, max)
}, error = function(e) {
return(rep(-1, dim(X)[2]+1)) }
)
return(beta_max)
}
Then I use beta_max_all <- mclapply(1:(batch_size+1), bottleneck, mc.cores=n_cores, mc.cleanup=TRUE) for multi-core jobs.
I'd be appreciate if the author can help me figure out what causes the problem. I cannot see any rules about when such issue happens; it seem to occur randomly and sometimes the script just runs smoothly. I run my computing on an Sun Grid Engine Cluster.
Here is all the error message.
*** caught segfault ***
address 0x30, cause 'memory not mapped'
Traceback:
1: biglasso(X, y, family = "gaussian", penalty.factor = penalty, lambda.min = 1e-04, nlambda = 250)
2: system.time(fit <- biglasso(X, y, family = "gaussian", penalty.factor = penalty, lambda.min = 1e-04, nlambda = 250))
3: doTryCatch(return(expr), name, parentenv, handler)
4: tryCatchOne(expr, names, parentenv, handlers[[1L]])
5: tryCatchList(expr, classes, parentenv, handlers)
6: tryCatch({ time <- system.time(fit <- biglasso(X, y, family = "gaussian", penalty.factor = penalty, lambda.min = 1e-04, nlambda = 250)) print(time) coef = as.matrix(fit$beta) coef[coef < 0] <- 0 coef = round(coef, digits = 6) colnames(coef) = fit$lambda if (k == 1) { write.table(coef, file = paste(outfname, ".coef", sep = ""), sep = "\t") } norm_beta = scale(coef, center = FALSE, scale = colSums(coef)) beta_max = apply(norm_beta, 1, max)}, error = function(e) { return(rep(-1, dim(X)[2] + 1))})
7: FUN(X[[i]], ...)
8: lapply(X = S, FUN = FUN, ...)
9: doTryCatch(return(expr), name, parentenv, handler)
10: tryCatchOne(expr, names, parentenv, handlers[[1L]])
11: tryCatchList(expr, classes, parentenv, handlers)
12: tryCatch(expr, error = function(e) { call <- conditionCall(e) if (!is.null(call)) { if (identical(call[[1L]], quote(doTryCatch))) call <- sys.call(-4L) dcall <- deparse(call)[1L] prefix <- paste("Error in", dcall, ": ") LONG <- 75L msg <- conditionMessage(e) sm <- strsplit(msg, "\n")[[1L]] w <- 14L + nchar(dcall, type = "w") + nchar(sm[1L], type = "w") if (is.na(w)) w <- 14L + nchar(dcall, type = "b") + nchar(sm[1L], type = "b") if (w > LONG) prefix <- paste0(prefix, "\n ") } else prefix <- "Error : " msg <- paste0(prefix, conditionMessage(e), "\n") .Internal(seterrmessage(msg[1L])) if (!silent && identical(getOption("show.error.messages"), TRUE)) { cat(msg, file = outFile) .Internal(printDeferredWarnings()) } invisible(structure(msg, class = "try-error", condition = e))})
13: try(lapply(X = S, FUN = FUN, ...), silent = TRUE)
14: sendMaster(try(lapply(X = S, FUN = FUN, ...), silent = TRUE))
15: FUN(X[[i]], ...)
16: lapply(seq_len(cores), inner.do)
17: mclapply(1:(batch_size + 1), bottleneck, mc.cores = n_cores, mc.cleanup = TRUE)
18: system.time(beta_max_all <- mclapply(1:(batch_size + 1), bottleneck, mc.cores = n_cores, mc.cleanup = TRUE))
An irrecoverable exception occurred. R is aborting now ...