1. Suppose one has a big data frame (say, m such that dim(m)=c(8610, 3521) )
If only a subset of m, say m[1:8600, ] is now needed, how to select it without 
creating large memory overhead? A natural solution, m <- m[1:8600,], seems to 
use in addition to memory needed to hold m roughly 2 times more memory - making 
the total memory required over 3 times object.size(m), as seen by using 
memory.size(max=T). This is understandable since the arguments are passed as 
value. However, is there a natural way around this memory overhead?

2. Similarly, if one has another data frame n such that dim(n)=c(10, 3521), 
doing m <- rbind(m,n) also needs the same amount of memory overhead. Is there 
any way around that?

I tried package ref, but could not solve the particular problems above.

Any help would be appreciated.

Piotr

Piotr Chmielowski
Chief Operating Officer/Group Risk Manager

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