Thanks Dirk and Hadley. Dirk, asap I will try your b) and c) suggestions. While for suggestion a), I didn't really understand how to implement it.
Hadley, I am determining rsession process memory looking at osx activity monitor utility, under Real Mem column. This is what I get (I am using your own mem() function to determine r memory usage) testMatrix <- Matrix(data=0,nrow=1e7,ncol=1e7,sparse=TRUE) gc() mem() # [1] 123.3, rsession Real Mem 203.1 MB sparse(testMatrix) mem() # [1] 161.5 gc() mem() # [1] 123.4, rsession Real Mem 507.8 MB sparse(testMatrix) mem() # [1] 161.5 gc() mem() # [1] 123.4, rsession Real Mem 585.0 MB sparse(testMatrix) mem() # [1] 161.5 gc() mem() # [1] 123.4, rsession Real Mem 661.3 MB and so on. If I call the function too many times (in fact I discovered it while using benchmark() ), it fills up the memory and the computer gets totally unresponsive. On 18 Nov, 2013, at 15:24 , Hadley Wickham wrote: >> After every call, the memory from gc() is stable, while rsession process >> memory keeps growing of around 100Mb at each call and doesn't decrease after >> the garbage collection. > > You don't mention how you're determining the size of the rsession > process, but you shouldn't necessarily expect it to decrease after > calling gc() - there may be memory fragmentation, but also the OS is > lazy about reclaiming memory from processes, so it may only be > returned to the OS when it actually needs it. > > Hadley > > -- > Chief Scientist, RStudio > http://had.co.nz/ _______________________________________________ Rcpp-devel mailing list Rcpp-devel@lists.r-forge.r-project.org https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel
