On 06/19/2012 02:22 AM, Jan Mueller wrote:
Dear All,
It seems that reference classes consume a lot of memory which became a problem
for my rather extensive simulation.
I prepared a small example. An instance of this minimal class uses about 20K on
disk.
rm(list=ls(all=TRUE));
MySmallClass = setRefClass("MySmallClass",
fields = list(
myField = "numeric"
),
methods = list(
initialize = function(f) {
myField<<- f;
})
);
o = MySmallClass$new(10);
saveRDS(o, file="C:\\o.rds");
file.info("C:\\o.rds")$size;
Result:
[1] 21274
My questions:
Is saveRDS() is representative for memory usage?
If so, is there a way to shrink these objects to a smaller size?
Caution: my answer is little more than speculation.
usually one would use
object.size(o)
to see the (approximate) size of an object, but reference classes use
environments, and object.size does not help here. Poking around at the
structure of reference classes, the environment is in a slot .xData, and
the content of the slot can have their sizes determined, as
> unlist(eapply(o@.xData, object.size, all.names=TRUE))
.self show getClass .refClassDef
656 5576 2456 48424
.->myField initialize myField field
48 1952 5592 5144
and so we discover that the reference class instance carries with it
it's own definition .refClassDef (!). So I think the answer is no, there
is no way to shrink these instances. One could create a light-weight S3
class to represent agents, say, in some kind of simulation as
agent <- function(myField) {
env = new.env(parent=emptyenv())
env[["myField"]] = myField
lockBinding("myField", env) ## 'private' data?
class(env) = "agent"
env
}
agents = lapply(rnorm(1000), agent)
or re-organize your simulation to act on vectors rather than individuals
.agents = setRefClass("Agents", fields = list(myField="numeric"))
agents = .agents$new(myField=rnorm(n))
and win by (a) amortizing the size of the reference class over many
agents and (b) setting yourself up for efficient vector calculations.
Martin
I use R 2.15.0 on a 32 Bit Windows 7 system.
Best regards,
Jan
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