[R] memory management in R

[Jens Oehlschlägel]

You might want to mention/talk about packages that enhance R's ability to work with less RAM / more data, such as package SOAR (transparently moving objects between RAM and disk) and ff (which allows vectors and dataframes larger than RAM and which supports dense datatypes like true boolean, short integers etc.). 

Jens Oehlschlägel



-----Ursprüngliche Nachricht-----
Von: john <mullers at fastmail.fm>
Gesendet: Jun 16, 2010 12:20:17 PM
An: r-help at r-project.org
Betreff: [R] memory management in R

>
>
>I have volunteered to give a short talk on "memory management in R" 
>   to my local R user group, mainly to motivate myself to learn about it. 
>
>The focus will be on what a typical R coder might want to know  ( e.g. how
>objects are created, call by value, basics of garbage collection ) but I
>want to go a little deeper just in case there are some advanced users in the
>crowd. 
>
>Here are the resources I am using right now
>  Chambers book "Software for Data Analysis" 
>  Manuals such as "R Internals" and "Writing R Extensions" 
>
>Any suggestions on other sources of information? 
>
>There are still some things that are not clear to me, such as
>  - how to make sense of the output from various memory diagnostics such as 
>        memory.profile ... are these counts? 
>        How to get the amount of memory used: gc() and memory.size() seem to
>differ
> -  what gets allocated on the heap versus stack
> - why the name "cons cells" for the stack allocation 
>
>Any help with these would be greatly appreciated. 
>
>Thanks greatly, 
>
>John Muller
>
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