Hi,
We've encountered a difference in running time between a straight function
call and the same call using do.call when the called function generated an
error. We've isolated the problem to the following small reproducible
example:
Consider the following function:
foo <- function(nr = 2e6, nc=3, use.do.call = FALSE) {
nn <- paste("V", 1:nc, sep="")
z <- data.frame(matrix(rnorm(nr*nc), nrow=nr, ncol = nc, dimnames =
list(NULL, nn)))
foo2 <- function(x) x[,"V1"] + x[,"V0"]
if (use.do.call)
do.call(foo2, list(z))
else
foo2(z)
}
foo2, when called, generates an error because it accesses the V0 column
which does not exist. When use.do.call==FALSE, foo2 is called directly.
When use.do.call==TRUE, foo2 is called with the same arguments but using
do.call. Calling foo() takes about 1 second. Calling
foo(use.do.call=TRUE)takes about 20 seconds. Does anybody know what
could explain the difference
in running time? The difference seems to be related to error handling,
since try(foo(use.do.call=TRUE)) takes just 1 second.
We used the latest R version (2.15.0) for the test.
Any insight will be appreciated,
Thanks,
Alon
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