R devel - Apr 2001 - Rgui 1.2.3 for Windows crashes reading huge CSV file (PR#927)

Full_Name: M. Edward Borasky
Version: 1.2.3 (2001-04-26)
OS: Windows 2000
Submission from: (NULL) (206.98.121.224)


I have a Celeron with 192 MB of RAM. My paging file is 288 MB, which is the
Windows recommended size. Here's the starting screen:
--------------------------------------------------------------------------------
R : Copyright 2001, The R Development Core Team
Version 1.2.3  (2001-04-26)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type `license()' or `licence()' for distribution details.

R is a collaborative project with many contributors.
Type `contributors()' for more information.

Type `demo()' for some demos, `help()' for on-line help, or
`help.start()' for a HTML browser interface to help.
Type `q()' to quit R.

[Previously saved workspace restored]
> memory.size()
[1] 8504720
> memory.limit()
[1] 200720384
> ls()
character(0)
---------------------------------------------------------------------------------
Now I try to read a huge (60 megabytes, 688,500 rows by 10 columns) CSV file
with "read.csv". Rgui grinds on it for some time before finally
crashing. The
error message is:

The exception unknown software exception (0xc00000fd) occurred in the
application at location 0x02672dcf.

I watched this in the Task Manager and it peaked around 160 MB.

Here's the first few lines of the input file (stock price data for all NYSE
stocks for the past year) if you want to try this with some fake data -- just
add 688,499 more rows of this stuff :-)

Symbol,Date,Cvf,IsStock,Open,High,Low,Close,Volume,OpenInt
"WLP",20000428,2,1,75.25,75.25,72.5,73.75,4151,0
"WLP",20000501,2,1,74,74.5,72.120002746582,72.4300003051758,2229,0
"WLP",20000502,2,1,72.370002746582,72.370002746582,71,71.870002746582,3629,0

I haven't tried this with the Linux version yet to see if it handles the
situation a little more gracefully. I'll do that sometime and attach the
results
to this bug report. This isn't a major problem for me; it's easy for me
to break
the file up into individual stocks, or substitute weekly data for the daily
data, which will reduce the file to 12 megabytes or so.


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