Calibrating an Oracle Cluster Health Advisor Model for a Cluster Deployment
As shipped with default node and database models, Oracle Cluster Health Advisor is designed not to generate false warning notifications.
You can increase the sensitivity and accuracy of the Oracle Cluster Health Advisor models for a specific workload using the chactl calibrate command.
Oracle recommends that a minimum of 6 hours of data be available and that both the cluster and databases use the same time range for calibration.
The chactl calibrate command analyzes a user-specified time interval that includes all workload phases operating normally. This data is collected while Oracle Cluster Health Advisor is monitoring the cluster and all the databases for which you want to calibrate.
To check if sufficient data is available, run the
query calibrationcommand.Note:
The
query calibrationcommand is supported only with GIMR. GIMR is optionally supported in Oracle Database 19c. However, it's desupported in Oracle AI Database 26ai.If 720 or more records are available, then Oracle Cluster Health Advisor successfully performs the calibration. The calibration function may not consider some data records to be normally occurring for the workload profile being used. In this case, filter the data by using the
KPISETparameters in both thequery calibrationcommand and thecalibratecommand.For example:
$ chactl query calibration -db oltpacdb -timeranges 'start=2016-07-26 01:00:00,end=2016-07-26 02:00:00,start=2016-07-26 03:00:00,end=2016-07-26 04:00:00' -kpiset 'name=CPUPERCENT min=20 max=40, name=IOTHROUGHPUT min=500 max=9000' -interval 2Start the calibration and store the model under a user-specified name for the specified date and time range.
For example:
$ chactl calibrate cluster -model weekday -timeranges 'start=2016-07-03 20:50:00,end=2016-07-04 15:00:00'Use the new model to monitor the cluster as follows:
For example:
$ chactl monitor cluster -model weekday
Example 4-6 Output for the chactl query calibrate command
Database name : oltpacdb
Start time : 2016-07-26 01:03:10
End time : 2016-07-26 01:57:25
Total Samples : 120
Percentage of filtered data : 8.32%
The number of data samples may not be sufficient for calibration.
1) Disk read (ASM) (Mbyte/sec)
MEAN MEDIAN STDDEV MIN MAX
4.96 0.20 8.98 0.06 25.68
<25 <50 <75 <100 >=100
97.50% 2.50% 0.00% 0.00% 0.00%
2) Disk write (ASM) (Mbyte/sec)
MEAN MEDIAN STDDEV MIN MAX
27.73 9.72 31.75 4.16 109.39
<50 <100 <150 <200 >=200
73.33% 22.50% 4.17% 0.00% 0.00%
3) Disk throughput (ASM) (IO/sec)
MEAN MEDIAN STDDEV MIN MAX
2407.50 1500.00 1978.55 700.00 7800.00
<5000 <10000 <15000 <20000 >=20000
83.33% 16.67% 0.00% 0.00% 0.00%
4) CPU utilization (total) (%)
MEAN MEDIAN STDDEV MIN MAX
21.99 21.75 1.36 20.00 26.80
<20 <40 <60 <80 >=80
0.00% 100.00% 0.00% 0.00% 0.00%
5) Database time per user call (usec/call)
MEAN MEDIAN STDDEV MIN MAX
267.39 264.87 32.05 205.80 484.57
<10000000 <20000000 <30000000 <40000000 <50000000 <60000000 <70000000 >=70000000
100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%
Database name : oltpacdb
Start time : 2016-07-26 03:00:00
End time : 2016-07-26 03:53:30
Total Samples : 342
Percentage of filtered data : 23.72%
The number of data samples may not be sufficient for calibration.
1) Disk read (ASM) (Mbyte/sec)
MEAN MEDIAN STDDEV MIN MAX
12.18 0.28 16.07 0.05 60.98
<25 <50 <75 <100 >=100
64.33% 34.50% 1.17% 0.00% 0.00%
2) Disk write (ASM) (Mbyte/sec)
MEAN MEDIAN STDDEV MIN MAX
57.57 51.14 34.12 16.10 135.29
<50 <100 <150 <200 >=200
49.12% 38.30% 12.57% 0.00% 0.00%
3) Disk throughput (ASM) (IO/sec)
MEAN MEDIAN STDDEV MIN MAX
5048.83 4300.00 1730.17 2700.00 9000.00
<5000 <10000 <15000 <20000 >=20000
63.74% 36.26% 0.00% 0.00% 0.00%
4) CPU utilization (total) (%)
MEAN MEDIAN STDDEV MIN MAX
23.10 22.80 1.88 20.00 31.40
<20 <40 <60 <80 >=80
0.00% 100.00% 0.00% 0.00% 0.00%
5) Database time per user call (usec/call)
MEAN MEDIAN STDDEV MIN MAX
744.39 256.47 2892.71 211.45 45438.35
<10000000 <20000000 <30000000 <40000000 <50000000 <60000000 <70000000 >=70000000
100.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.00%