[R] Size of a refClass instance

David Kulp dkulp at fiksu.com
Fri May 3 12:56:12 CEST 2013


Good tip.  Thanks Morgan.
I agree that a different structure might (necessarily) be in order.  I wanted to create a tree where nodes in a tree were of different derived sub-classes -- possibly holding more data and behaving polymorphically.  OO programming seemed ideal for this: lots of small things with specialized behavior -- but this isn't R's strength.

On May 2, 2013, at 4:57 PM, Martin Morgan wrote:

> On 05/01/2013 11:20 AM, David Kulp wrote:
>> I'm using refClass for a complex multi-directional tree structure with
>> possibly 100,000s of nodes.  The refClass design is very impressive and I'd
>> love to use it, but I've found that the size of refClass instances are very
>> large and creation time is slow.  For example, below is a RefClass and normal
>> S4 class.  The RefClass requires about 4KB per instance vs 500B for the S4
>> class -- based on adding the Ncells and Vcells of used memory reported by
>> gc().  And instantiation is more than twice as slow for a RefClass.  (R
>> 2.14.2)
>> 
>> Anyone have thoughts on this and whether there's any hope for improving
>> resources on either front?
> 
> Hi David -- not necessarily helpful but creating a few large objects is always better than creating many small in R, so perhaps re-conceptualize your data structure? As a rough analogy, instead of constructing a graph as a large number of 'Node' instances each pointing to one another, a graph could be represented as a data.frame containing columns of 'from' and 'to' indexes (neighbour-edge list, a few large objects) or as an adjacency matrix. One would also implement creation and update of the few large objects in an R-friendly (vectorized) way.
> 
> Perhaps there are existing packages that already model the data you're interested in? If your multi-directional tree can be represented as a graph, then perhaps
> 
>  http://bioconductor.org/packages/release/bioc/html/graph.html
> 
> including facilities in the Boost graph library (RBGL, on the Bioconductor web site, too) or the igraph package can be put to use.
> 
> Martin
> 
>> 
>> I wonder what others are doing.  I've been thinking about lightweight
>> alternative implementations, but nothing particularly elegant has come to
>> mind, yet!
>> 
>> Thanks!
>> 
>> 
>> simple <- setRefClass('simple', fields = list(a = "character", b="numeric")
>> ) gc() system.time(simple.list <- lapply(1:100000, function(i) {
>> simple$new(a='foo',b=i) })) gc()
>> 
>> setClass('simple2', representation(a="character",b="numeric"))
>> setMethod("initialize", "simple2", function(.Object, a, b) { .Object at a <- a
>> .Object at b <- b .Object })
>> 
>> gc() system.time(simple2.list <- lapply(1:100000, function(i) {
>> new('simple2',a='foo',b=i) })) gc()
>> 
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> 
> 
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