Dear Martin, I think you would be mostly good for just going ahead with this. You might look at the size of your tables, but I expect that all to be well within safe ranges.
Cheers, Jan > On 19 May 2026, at 16:27, Martin Mueller <[email protected]> > wrote: > > I use Postgres with a GUI frontend (Aquafold) as a very large spreadsheet on > steroids that analyzes rare or defective spellings in a corpus of 65,000 > texts and1.5 billion words. I typically extract data from the corpus with > python scripts, turn them into tables and load them into the database. > > On my Mac with 32 GB of memory performance is OK with queries that typically > within seconds extract data rows from tables with up to ten million rows. > If the result set is large, I suspect that most of time machine's time is > spent displaying result sets. I have used indexing sparingly. While it helps, > the time savings often don't matter much. > > I am thinking about scaling up to table with about 60 million rows. Are > there things to do or watch out for? Or should I proceed on the assumption > that that 60 million records are within scope and that the added timecost is > roughly linear? > > Martin Mueller > Professor emeritus of English and Classics > Northwestern University > > >
