AWR Baseline

Ttypical performance tuning exercise starts with a capturing a baseline set of metrics, making changes, and then taking another baseline set. These two sets can be compared to examine the effect of the changes made. In AWR, the same kind of analogy can be implemented for existing snapshots taken. Suppose a particularly resource intensive process named apply_interest ran between 1:00 and 3:00PM, corresponding to snapshot IDs 56 through 59. We could define a baseline named apply_interest_1 for these snapshots:

exec dbms_workload_repository.create_baseline (56,59,'apply_interest_1')

This action marks the snapshots 56 through 59 as part of a baseline named above. Checking for existing baselines:

select * from dba_hist_baseline;

     DBID BASELINE_ID BASELINE_NAME        START_SNAP_ID END_SNAP_ID
---------- ----------- -------------------- ------------- -----------
4133493568           1 apply_interest_1                56          59

After a few tuning steps, we can create another baseline--called, say apply_interest_2--and compare the metrics for only those snapshots related to these two baselines. Isolating snapshots to only a few sets like this helps in studying the effects of tuning on performance metrics. You can drop the baselines after the analysis using the procedure drop_baseline(); the snapshots will be preserved. Also, when the purge routine kicks in to delete the old snapshots, the ones related to baselines are not purged, allowing for further analysis.