Since the sqlite package is contributed, it is NOT related to "core R", and is in fact technically off-topic on this list.
FWIW all SQL implementations work better with indexes, but AFAIK the R data frame support does nothing with indexes. This may be related to your question, or not. I am not a regular sqlite user. As for fast reading of tsv files, I think arrow, readr, and data.table packages all offer high-performance import functions that could be relevant. On October 6, 2021 11:49:55 AM PDT, Rasmus Liland <j...@posteo.no> wrote: >Thank you Bert, I set up a new thread on >BioStars [1]. So far, I'm a bit >unfamilliar with Bioconductor (but will >hopefully attend a course about it in >November, which I'm kinda hyped about), >other than installing and updating R >packages using BiocManager .... Did you >think of something else than >BioStars.org when saying «Bioconductor?» > >The question could be viewed as gene >related, but I think it is really about >how can one easier than with sqlite >handle large tsv files, and why is that >parser thing so slow ... I think this >is more like a core R thing than gene >related question ... > >[1] https://www.biostars.org/p/9492486/ -- Sent from my phone. Please excuse my brevity. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
