Hi fellows, Currently we're implementing the BP https://blueprints.launchpad.net/nova/+spec/utilization-aware-scheduling. The main idea is to have an extensible plugin framework on nova-compute where every plugin can get different metrics(e.g. CPU utilization, memory cache utilization, network bandwidth, etc.) to store into the DB, and the nova-scheduler will use that data from DB for scheduling decision.
Currently we adds a new table to store all the metric data and have nova-scheduler join loads the new table with the compute_nodes table to get all the data(https://review.openstack.org/35759). Someone is concerning about the performance penalty of the join load operation when there are many metrics data stored in the DB for every single compute node. Don suggested adding a new column in the current compute_nodes table in DB, and put all metric data into a dictionary key/value format and store the json encoded string of the dictionary into that new column in DB. I'm just wondering which way has less performance impact, join load with a new table with quite a lot of rows, or json encode/decode a dictionary with a lot of key/value pairs? Thanks, -Lianhao _______________________________________________ OpenStack-dev mailing list OpenStack-dev@lists.openstack.org http://lists.openstack.org/cgi-bin/mailman/listinfo/openstack-dev
