heap size trouble
Jim Lemon <bitwrit at ozemail.com.au> writes:
karamian wrote: ...I want to load a file that contains 93 thousand raws and 22 colums of data (essentially float)... I just had to process over 199000 records with four numeric values. If I remember correctly, I used: --vsize 30M --nsize 500000 which pretty much ate all the RAM (64M) I had. Don't forget to "rm" big data sets before you exit, or R will bomb when you next try to load without the increased memory. Just reread from the data file when you need them again (and it helps to exit other apps before starting R to avoid disk thrashing).
Another approach is to use a relational database to store such a large table and load the table into R from the database. There are several interfaces into R from relational databases. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._