[openstack-dev] [Nova] New DB column or new DB table?
sean at dague.net
Thu Jul 18 11:05:10 UTC 2013
On 07/17/2013 10:54 PM, Lu, Lianhao wrote:
> 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?
I'm really confused. Why are we talking about collecting host metrics in
nova when we've got a whole project to do that in ceilometer? I think
utilization based scheduling would be a great thing, but it really out
to be interfacing with ceilometer to get that data. Storing it again in
nova (or even worse collecting it a second time in nova) seems like the
I think there was an equiv patch series at the end of Grizzly that was
pushed out for the same reasons.
If there is a reason ceilometer can't be used in this case, we should
have that discussion here on the list. Because my initial reading of
this blueprint and the code patches is that it partially duplicates
ceilometer function, which we definitely don't want to do. Would be
happy to be proved wrong on that.
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