[R] memory limits in R loading a dataset and using the package tree

From: domenico pestalozzi <statadat_at_gmail.com>
Date: Thu 04 Jan 2007 - 16:30:26 GMT

I think the question is discussed in other thread, but I don't exactly find what I want .
I'm working in Windows XP with 2GB of memory and a Pentium 4 - 3.00Ghx. I have the necessity of working with large dataset, generally from 300,000 records to 800,000 (according to the project), and about 300 variables (...but a dataset with 800,000 records could not be "large" in your opinion...). Because of we are deciding if R will be the official software in our company, I'd like to say if the possibility of using R with these datasets depends only by the characteristics of the "engine" (memory and processor).
In this case we can improve the machine (for example, what memory you reccomend?).

For example, I have a dataset of 200,000 records and 211 variables but I can't load the dataset because R doesn't work : I control the loading procedure (read.table in R) by using the windows task-manager and R is blocked when the file paging is 1.10 GB. After this I try with a sample of 100,000 records and I can correctly load tha dataset, but I'd like to use the package tree, but after some seconds ( I use this tree(variable1~., myDataset) ) I obtain the message "Reached total allocation of 1014Mb".

I'd like your opinion and suggestion, considering that I could improve (in memory) my computer.


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