Hello,
It normally takes few milliseconds to execute the query.
The issue is occurring only at specific times where another application is inserting data into routing tables (not the live tables used by Kamailio, which will be swapped later to the live tables) , where 300 CPS is flowing into kamailio.
Regards, Ali Taher
From: sr-users sr-users-bounces@lists.kamailio.org On Behalf Of David Villasmil Sent: Tuesday, December 10, 2019 5:04 PM To: Kamailio (SER) - Users Mailing List sr-users@lists.kamailio.org Subject: Re: [SR-Users] Kamailio delayed reponse in case of database load
Hello,
Have you checked yourself how long PGSQL takes to answer a query from a different host? This really doesn't seem Kamalio-related, but PGSQL-related.
Regards,
David Villasmil email: david.villasmil.work@gmail.commailto:david.villasmil.work@gmail.com phone: +34669448337
On Tue, Dec 10, 2019 at 12:41 PM Ali Taher <ataher@vanrise.commailto:ataher@vanrise.com> wrote: Hello,
I have Kamailio installed as SIP redirect for an SBC to make routing decisions. I’m using SQLOps module with postgresql 11.5 where I have multiple tables containing each around 6M record of routing codes: Code options ----------------------- 392342 sup1|sup2|sup3
Where code field is of prefix_range data type and has a gist index. I’m sending traffic of 300 CPS to SBC which is forwarding it to Kamailio, and Kamailio respond with 300 multiple choice with the routing decision. In normal cases, everything is going smoothly where Kamailio repsonds up to 50 ms. But during the process of loading data to the routing tables, Kamailio response to SBC is dramatically delayed , where for some calls it takes up to 7 seconds to respond. Noting that during this process the data are loaded to staging tables and not to live tables used by Kamailio. Kamailio is installed on a VM with 32GB RAM and 16 vcores. Following configuration is used in Kamailio: fork=yes children=10
following are the customized parameters in postgresql.conf max_connections = 100 shared_buffers = 8GB effective_cache_size = 24GB maintenance_work_mem = 2GB checkpoint_completion_target = 0.7 wal_buffers = 16MB default_statistics_target = 100 random_page_cost = 1.1 effective_io_concurrency = 200 work_mem = 5242kB min_wal_size = 1GB max_wal_size = 2GB max_worker_processes = 16 max_parallel_workers_per_gather = 8 max_parallel_workers = 16
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