Busy preparing for Hotsos 2013. My presentation this year is “Working with Confidence: How Sure Is the Oracle CBO about Its Cardinality Estimates, and Why Does It Matter?” I know it is a mouthful. The presentation/white paper would be up to the point with lots of pictures though 🙂
The only thing I have for the blog now is a revised version of a query I posted the last time. The original version was way too crude.
select a.rollup_timestamp ,
sum(a.average*c.cpu_count)/ sum(c.cpu_count) ,
sum(a.maximum*c.cpu_count)/ sum(c.cpu_count) ,
sum((a.average+3*a.standard_deviation)*c.cpu_count) / sum(c.cpu_count)
mgmt$metric_hourly a ,
mgmt$target b ,
a.metric_name = 'Load'
and a.column_label = 'CPU Utilization (%)'
and a.target_guid = b.target_guid
and b.target_name like 'dev%'
and c.hostname||'.'||c.domain = b.target_name
and c.vendor_name = 'Intel Based Hardware'
group by a.rollup_timestamp
order by 5 desc
The query now takes into account the number of CPUs on a server. I use the undocumented MGMT_ECM_HW view – it contains a wealth of information.
The query assumes that all CPUs are identical – not perfect, but much better than the original.