After import, it takes 3-6 hours additionally to create indexes for those tables.
I think the main problem was that I had text indices. I'm not an expert in RDBMS and used a simple join that was taking ages to start producing the actual data. There are definitely a lot of ways to tune such queries and PostgreSQL configs, but I wanted a simple and universal solution.
We have a CSV for timeseries data, where for some reason someone decided to force each line to represent one data point. However, for some cases, one data point may contain around 30 different statistics for 4 million different IPs, which get represented as 120 million columns in the CSV (think a CSV header like 'timestamp,10.0.0.1—Throughput,10.0.0.1-DroppedBytes,[...],10.215.188.251-Throughput,[...]'). With large numbers represented as text in a CSV, this can sometimes reach more than one 1GB per line.
And how much of that time was just getting the data into the tables? There are fast and slow ways to do that, too...