32. AAS – Average Active Sessions
Kyle Hailey: http://www.perfvision.com/ftp/class/02_AAS.ppt
Max CPU
Max CPU
33. AAS – the Golden Metric
AAS & CPU count as a yardstick for a possible performance problem:
if AAS < 1
-- Database is not blocked
AAS ~= 0
-- Database basically idle
-- Problems are in the APP not DB
AAS < # of CPUs
-- CPU available
-- Database is probably not blocked
-- Are any single sessions 100% active?
AAS > # of CPUs
-- Could have performance problems
AAS >> # of CPUS
-- There is a bottleneck
50. Filter the data points
• AAS range
aas > 1
• Per SNAP_ID or range of SNAP_IDs
id in (336)
where id >= 336 and id <= 340
• Oracle CPU Utilization
oracpupct > 50
• OS CPU Utilization
oscpupct > 50
• Workload periods
AND TO_CHAR(s0.END_INTERVAL_TIME,'D') >= 1 -- Day of week: 1=Sunday 7=Saturday
AND TO_CHAR(s0.END_INTERVAL_TIME,'D') <= 7
AND TO_CHAR(s0.END_INTERVAL_TIME,'HH24MI') >= 0900 -- Hour
AND TO_CHAR(s0.END_INTERVAL_TIME,'HH24MI') <= 1800
AND s0.END_INTERVAL_TIME >= TO_DATE('2010-jan-17 00:00:00','yyyy-mon-dd hh24:mi:ss') -- Data range
AND s0.END_INTERVAL_TIME <= TO_DATE('2010-aug-22 23:59:59','yyyy-mon-dd hh24:mi:ss‘)
51.
52. core need = # of cores * utilization * 1.25
Database Consolidation Best Practices
http://husnusensoy.files.wordpress.com/2010/05/database-consolidation-best-practices.pdf
53.
54.
55. Total disk IOPS = (IOPS * Read Ratio) + (IOPS * Write Ratio * RAID penalty)
Number of disk = Total disk IOPS / IOPS per disk
65. x data (CPU) = is the "independent value", used to predict the value of y
y data (AAS) = is the "dependent value", variable whose value is to be predicted
66.
67.
68.
69.
70.
71. r2toolkit
Uses the following
inbuilt Oracle functions:
•regr_count
•regr_r2
•regr_intercept
•regr_slope
72. r2toolkit
The toolkit systematically
gets the statistic with
highest correlation
coefficient (relationship)
No guess work!
73. Linear Regression – what’s the value?
Lets you do forecast that can
guide you with targeted response
time optimizations and workload
reduction.
• Drill down on SNAP_IDs (data
samples) with high AAS
• Know what’s causing the high AAS
on those SNAP_IDs
• Tune the bottleneck - results to
huge savings on system resources!
74. Linear Regression on 2 node RAC
http://karlarao.tiddlyspot.com/#r2project
racnode1 racnode2