1. Migration from one server to another. Newer OS (Debian 12 vs Ubuntu 20.04), same version of Postgres (17).
2. postgres_fdw is to different databases within the same cluster.
3. 17
4. No new analyze was done; migration was achieved by moving the disks between the virtual servers. We reindexed all text indexes to allow for the new glibc version on Debian 12.
5. That's the thing: I have no idea which queries the `fetch 100 from c2` are associated with because the `c2` seems to be reused for each query. The psycopg python library generates unique server-side cursor names, but postgres_fdw doesn't.
6. The 19 slowest queries in a 4 hour period are between 2 and 37 minutes, with an average of over 10 minutes; they are all `fetch 100 from c2`.
The slowness itself isn't my question here; it was caused by having too few cores in the new environment, while the application was still assuming the higher core count and generating too many concurrent processes.
My question is how to identify which connections / queries from postgres_fdw are generating the `fetch 100 from c2` queries, which, in turn, may quite possibly lead to a feature request for having these named uniquely.
Thanks,
Colin
On 1/21/26 00:18, Colin 't Hart wrote:
> Hi,
>
> One of my clients makes extensive use of postgres_fdw. After a migration
> performance isn't great. pgBadger reports show the slowest queries all
> being `fetch 100 from c2`.
>
> Anyone have any tricks for being able to associate those fetches with
> the queries that were used when declaring the server-side cursor?
This is going to need a lot more information. To start:
1) Migration of what and from what version to what version?
2) Where are the Postgres databases relative to each other on the network?
3) What versions of Postgres if not covered in 1.
4) If Postgres was what was being updated was an analyze done on the
instances?
5) Show a complete query using EXPLAIN ANALYZE.
6) Define slow.
>
> Thanks,
>
> Colin
--
Adrian Klaver
adrian.klaver@aklaver.com
