Huge memory comsumption with foreign and RPgSQL

Perttu Muurim?ki <Perttu.Muurimaki at Helsinki.Fi> writes:

I know this is something R isn't meant to do well but I tried it anyway :)

I have this SPSS-datafile (size 31 MB). When I converted it to a R object
with read.spss("datafile.sav") I ended up with a .RData-file which was 229
MB big. Is this considered normal?

Doesn't sound completely unreasonable: If all your fields fit in a
single byte to begin with and get converted to double in the process,
you'll have an inflation by a factor of 8. 

Then I tried to dump that object into a database with RPgSQL-package
function db.write.table(object) (Memory ran out first time I tried to
convert SPSS-file into a R-object so I was quite prepared for the
database manouvre ; I increased the size of swap (working with linux) to
2500 MB) The process kept going and going and getting bigger and bigger.
After 6 hours and 30 minutes I aborted it. At that time the process had
grown into 1400 MB:s. Again, is this considered normal? And further more,
am I likely to succeed if I'm patient enough?

This, however, sounds a bit excessive, although I wouldn't know
exactly what goes on inside RPgSQL... If it is converting every field
in the entire data frame to string form before sending it to the
database, then I might understand. Might it be possible to send it in
smaller blocks?