Re: Storing thousands of csv files in postgresql - Mailing list pgsql-sql

On Tue, Feb 15, 2022 at 1:13 PM Rob Sargent <robjsargent@gmail.com> wrote:

I don't think you need a "federated" postgres network like Citus at all - I think this solves a different use case. For your design problem, I think that having a bunch of independent Pg servers would be fine - as long as you don't need to run searches across CSV tables stored across different databases (in which case you do need index/search federation of some kind).

Regarding Erik Brandsberg's point about XFS, I think this is a useful alternative approach, if I understand the idea. Instead of storing your CSV files in Postgres, just store them as CSV files on the file system. You can still store the schemas in Pg, but each schema would just point to a file in the file system and you'd manipulate the files in the filesystem using whatever language is appropriate (I find ruby to be excellent for managing CSV files). If you need to index those files to run searches against them, I'd direct your attention to https://prestodb.io/ which is the core technology that runs Amazon Athena. This allows you to search CSV files with various schema (among other data bindings). So you might find that Pg as your schema storage, XFS (or any modern FS) to store large numbers of CSV files, and Presto/Athena to index/search those files, along with some CSV management language (like Ruby or something even higher level) to manage the data.

I think if I were dealing with less than 10k CSV files (and therefore Pg tables), I might use Pg, and if I were dealing with 10k+ files, I'd start looking at file systems + Presto. But that's a WAG.

Steve

 

I think the add/remove column requirement alone justifies NOT using files.  The CSV approach will temp the system to handle some versioning nonsense. Using tables also provides some protection against the inevitable garbage data in the CSVs. 

I missed that requirement - totally agree. Adding columns to file-based CSVs is a huge PITA. Agree on your other point as well: just having the right charset requirements in Pg can help trim or identify some of the bad data that comes in from CSVs but the opportunities for all kinds of efficient data validation recommends storing the CSV data in Pg.

I'll add that I've used the postgres COPY command to move CSV data into tables so fast that I had to double take the rows/sec to believe it. I actually shared a gist to demonstrate how to implement this using Ruby and a low level postgres driver a few months ago: https://gist.github.com/science/393907d4123c87ed767bc81e9dd5a7da  Maybe useful..