[Rd] [R] How to create a list that grows automatically

Prof Brian Ripley ripley at stats.ox.ac.uk
Sun Mar 25 12:50:41 CEST 2007


[Moved to R-devel for a technical comment.]

On Fri, 9 Mar 2007, hadley wickham wrote:

>> I would like to know if there is a way to create a list or an array (or
>> anything) which grows automatically as more elements are put into it. What I
>> want to find is something equivalent to an ArrayList object of Java
>> language. In Java, I can do the following thing:
>>
>> // Java code
>> ArrayList myArray = new ArrayList();
>> myArray.add("object1");
>> myArray.add("object2");
>> ....
>> // End of java code
>
> As others have mentioned, you can do this with lists in R.
>
> However, there is an important difference between ArrayLists in Java
> and Lists in R.  In Java, when an ArrayList grows past its bound, it
> doesn't allocate just enough space, it allocates a lot more, so the
> next time you allocate past the end of the array, there's space
> already reserved.  This gives (IIRC) amortised O(n) behaviour.  R
> doesn't do this however, so has to copy the entire array every time
> giving O(n^2) behaviour.

In fact this is an implementation detail.  R has both 'length' and 
'truelength' fields in its headers for vectors (including lists) and could 
grow the allocation in the same way as you report Java does.  When I asked 
Ross what the intention had been (the 'truelength' field is almost unused) 
he mentioned this potential usage.  Given that these structures are opaque 
to all but R internal code it should not be hard to change R's scheme to 
over-allocate: to decide how much to do would be harder (but say rounding 
vectors in the large allocation class up to a VM page would get a 
noticeable benefit in some usages with a negligible impact on memory 
footprint).  Backwards compatibility of save() format would be an issue.

It seems the really inefficient uses are of the type

x <- NULL
for(i in 1:10000) x <- c(x, fn(i))

and those would be unaltered.

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595



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