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I remember back in the early 2010's that a large selling point of SAS (besides the ridiculous point that R/python were freeware and therefore cannot be trusted
by skwb 7y ago
I remember back in the early 2010's that a large selling point of SAS (besides the ridiculous point that R/python were freeware and therefore cannot be trusted on important projects ) was that it can chew through large data sets that perhaps couldn't be moved into RAM (but maybe it takes a week or whatever....).
This was a fairly salient point, and remember circa 2012/2013 struggling to fit large bioinfomatics data into an older iMac with base R.
- vasili111 7y agoI have not tested it myself but now there is a disk.frame ( https://github.com/xiaodaigh/disk.frame https://github.com/xiaodaigh/disk.frame ). As far as I know, other options exist too.
- dredmorbius 7y agoSAS Institute have long claimed this. It's been provably bullshit for decades. In practice, an awk script frequently ran circles around processing. On a direct basis, awk corresponds quite closely to the SAS DATA Step (and was intended to be paired with tools such as S, the precursor to R, for similar types of processing). The fact that awk had associative arrays (which SAS long lacked, it's since ... come up with something along those lines) and could perform extremely rapid sort-merge or pattern matches (equivalent to SAS data formats, which internally utilise a b-tree structure) helped. With awk, sort, unique, and a few hand-rolled statistics awk libraries / scripts, you can replace much of the functionality of SAS. And that's without even touching R or gnuplot, each of which offer further vast capabilities. And at an aggreable annual license fee.