using parallel's parLapply: unable to access variables within parallel code

Question

I recently got a computer with several cores and am learning to use parallel computing. I\'m fairly proficient with lapply and was told parLapply

Answer 1

out1<-lapply(seq_len(ntv), function(i) {x <- pos(text.var[i]);if (i%%gc.rate==0) gc();return(x)})
out2<-parLapply(cl, seq_len(ntv), function(i) {x <- pos(text.var[i]);if (i%%gc.rate==0) gc();return(x)})

>     identical(out1,out2)
# [1] TRUE
require(rbenchmark)
benchmark(lapply(seq_len(ntv), function(i) {x <- pos(text.var[i]);if (i%%gc.rate==0) gc();return(x)}),parLapply(cl, seq_len(ntv), function(i) {x <- pos(text.var[i]);if (i%%gc.rate==0) gc();return(x)}))


                                                                                       test
#1        lapply(seq_len(ntv), function(i) {\n    x <- pos(text.var[i])\n    if (i%%gc.rate == 0) \n        gc()\n    return(x)\n})
#2 parLapply(cl, seq_len(ntv), function(i) {\n    x <- pos(text.var[i])\n    if (i%%gc.rate == 0) \n        gc()\n    return(x)\n})
#  replications elapsed relative user.self sys.self user.child sys.child
#1          100   20.03 3.453448     20.31     0.05         NA        NA
#2          100    5.80 1.000000      0.22     0.03         NA        NA

> cl
socket cluster with 2 nodes on host ‘localhost’