Sometimes it might be useful to analyze top time-consuming filter and access predicates from ASH, especially in cases when db load is spread evenly enough by different queries and top segments do not show anything interesting, except usual things like “some tables are requested more often than others”.
Of course, we can start from analysis of SYS.COL_USAGE$: col_usage.sql
But it’s not enough, for example it doesn’t show predicates combinations. In this case we can use v$active_session_history and v$sql_plan:
As you can see it shows top 50 predicates and their columns for last 3 hours. Despite the fact that ASH stores just sampled data, its results are representative enough for high-load databases.
Just few details:
- Column “COLS” shows “search columns”, and total_by_cols – their number of occurrences
- I think it’s obvious, that this info is not unambiguous marker of the problem, because for example few full table scans can misrepresent the statistics, so sometimes you will need to analyze such queries deeper (v$sqlstats,dba_hist_sqlstat)
- We need to group data by OBJECT_ALIAS within SQL_ID and plan_hash_value, because in case of index access with lookup to table(“table access by rowid”) some predicates are in the row with index access and others are in the row with table access.
Depending on the needs, we can modify this query to analyze ASH data by different dimensions, for example with additional analysis of partitioning or wait events.