I'm looking to use parLapply()
on windows within an R6
object and noticed (that in at least some cases) that I do not need to export the R6 functions or data to the nodes.
Here is an example where I can access private methods within parLapply()
:
require(R6);require(parallel)
square <-
R6Class("square",
public = list(
numbers = NA,
squares = NA,
initialize = function(numbers,integer) {
self$numbers <- numbers
squares <- private$square.numbers()
}
),
private = list(
square = function(x) {
return(x^2)
},
square.numbers = function() {
cl <- makeCluster(detectCores())
self$squares <- parLapply(cl,
self$numbers,
function (x) private$square(x)
)
stopCluster(cl)
}
))
##Test
test <- square$new(list(1,2,3))
print(test$squares)
# [[1]]
# [1] 1
#
# [[2]]
# [1] 4
#
# [[3]]
# [1] 9
And a second example where I can also access public members:
square2 <-
R6Class("square2",
public = list(
numbers = NA,
squares = NA,
integer = NA,
initialize = function(numbers,integer) {
self$numbers <- numbers
self$integer <- integer
squares <- private$square.numbers()
}
),
private = list(
square = function(x) {
return(x^2)
},
square.numbers = function() {
cl <- makeCluster(detectCores())
self$squares <- parLapply(cl,
self$numbers,
function (x) private$square(x)+self$integer
)
stopCluster(cl)
}
))
##Test
test2 <- square2$new(list(1,2,3),2)
print(test2$squares)
#[[1]]
#[1] 3
#
#[[2]]
#[1] 6
#
#[[3]]
#[1] 11
My question is twofold: (1) What about R6 makes this possible so that I don't need to export data objects and functions; and (2) can I rely on this behavior or is this an artifact of these specific examples?
UPDATE:
This behavior also appears to work using public methods and members after the object has been instantiated:
square3 <- R6Class(
classname = "square3",
public = list(
numbers = NA,
squares = NA,
integer = NA,
square = function(x) {
return(x^2)
},
square.numbers = function() {
cl <- makeCluster(detectCores())
self$squares <- parLapply(cl,
self$numbers,
function (x) self$square(x)+self$integer
)
stopCluster(cl)
},
initialize = function(numbers,integer) {
self$numbers <- numbers
self$integer <- integer
}
)
)
test3.obj <- square3$new(list(1,2,3),2)
test3.obj$square.numbers()
test3.obj$squares
# [[1]]
# [1] 3
#
# [[2]]
# [1] 6
#
# [[3]]
# [1] 11