performance - R: Why is the [[ ]] approach for subsetting a list faster than using $?

Question

I've been working on a few projects that have required me to do a lot of list subsetting and while profiling code I realised that the object[["nameHere"]] approach to subsetting lists was usually faster than the object$nameHere approach.

As an example if we create a list with named components:

a.long.list <- as.list(rep(1:1000))
names(a.long.list) <- paste0("something",1:1000)

Why is this:

system.time (
for (i in 1:10000) {
    a.long.list[["something997"]]
}
)


user  system elapsed 
0.15    0.00    0.16 

faster than this:

system.time (
    for (i in 1:10000) {
        a.long.list$something997
    }
)

user  system elapsed 
0.23    0.00    0.23 

My question is simply whether this behaviour is true universally and I should avoid the $ subset wherever possible or does the most efficient choice depend on some other factors?

Answer 1

Function [[ first goes through all elements trying for exact match, then tries to do partial match. The $ function tries both exact and partial match on each element in turn. If you execute:

system.time (
    for (i in 1:10000) {
     a.long.list[["something9973", exact=FALSE]]
     }
)

i.e., you are running a partial match where there is no exact match, you will find that $ is in fact ever so slightly faster.