
Hi, I just wanted to share a partial result from testing of engine db load during operation (SQL queries frequencies). Maybe, we can decide later, if some SQL queries result CACHING can boost throughput for larger deployments. The caching technology can be from a simple HashMap lookup to deployments of something like http://ehcache.org/ (memory database). I prepared two simple scenarios: - oVirt engine, 2 hosts, 1 VM, running 15 minutes (Power on + Up state) - oVirt engine, 2 hosts, 10 VMs from one pool, running 15 minutes (Power on + Up state) Appending 2 spreadsheets with data about the most used SQL queries (generated by PostgreSQL standard pg_statements_stat module). e.g. - 2nd row shows number of granted connections from the db pool (e.g. can be used to set optimal connection pool size) (check of connection health: select 1) - most of the queries are wrapped by a PLSQL function so we see a wrapper: /select * from getvdsgroupbyvdsgroupid($1, $2, $3)/ and near to it the 'real' query: /SELECT vds_groups_view.*// // FROM vds_groups_view// // WHERE vds_group_id = v_vds_group_id// // AND (NOT v_is_filtered OR EXISTS (SELECT 1// // FROM user_vds_groups_permissions_view// // WHERE user_id = v_user_id AND entity_id = v_vds_group_id))// / Just as an example, I selected in yellow color some queries, which probably do not change often, but are very frequent. Other tools like 'pg_top' can provide runtime statistics of db processes (cpu, mem, locks, ... views). By enabling debug level logging of PostgreSQL we can check real values to the queries. Of course, it would be useful to run such tests with many hosts and VMs to predict scaling issues. More info about tools configuration: http://www.ovirt.org/Engine_database_performance_monitoring Regards, Libor