Multiplying elements of list with lapply is almost twice as fast with in-line function definition than with standard "*"

If we want to multiply of elements of a list by a constant, we can do so with lapply. However, I have observed that defining the function to be applied in-line is almost twice faster than specifying "*" as the function to be applied:

library(microbenchmark)
microbenchmark::microbenchmark(x=lapply(X=list(a=c(1,2,3)), FUN=function(x) x*1000), y=lapply(X=list(a=c(1,2,3)), "*", 1000), times = 10000)

This gives me a median of around 1100 nanoseconds for the first expression, and around 1900 nanoseconds for the second one.

Any ideas why this could be happening?

>Solution :

lapply calls match.fun, which must spend some time matching the string "*" to the primitive function `*`. Passing the function directly avoids the overhead.

l <- list(1, 2, 3)
microbenchmark::microbenchmark(lapply(l, function(x) x * 1000),
                               lapply(l, "*", 1000),
                               lapply(l, `*`, 1000),
                               times = 1e+06L)
## Unit: nanoseconds
##                             expr  min   lq     mean median   uq      max neval
##  lapply(l, function(x) x * 1000) 1271 1435 1614.497   1476 1517  1243981 1e+06
##             lapply(l, "*", 1000) 1640 1763 2026.791   1804 1886 16498605 1e+06
##             lapply(l, `*`, 1000)  861  984 1198.956   1025 1066 16636365 1e+06