R的GC和内存限制问题

Question

I am using R on some relatively big data and am hitting some memory issues. This is on Linux. I have significantly less data than the available memory on the system so it's an issue of managing transient allocation.

When I run gc(), I get the following listing

           used   (Mb) gc trigger   (Mb)  max used   (Mb)
Ncells   2147186  114.7    3215540  171.8   2945794  157.4
Vcells 251427223 1918.3  592488509 4520.4 592482377 4520.3

yet R appears to have 4gb allocated in resident memory and 2gb in swap. I'm assuming this is OS-allocated memory that R's memory management system will allocate and GC as needed. However, lets say that I don't want to let R OS-allocate more than 4gb, to prevent swap thrashing. I could always ulimit, but then it would just crash instead of working within the reduced space and GCing more often. Is there a way to specify an arbitrary maximum for the gc trigger and make sure that R never os-allocates more? Or is there something else I could do to manage memory usage?

Answer 1

In short: no. I found that you simply cannot micromanage memory management and gc() .

On the other hand, you could try to keep your data in memory, but 'outside' of R. The bigmemory makes that fairly easy. Of course, using a 64bit version of R and ample ram may make the problem go away too.