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--
-- File name:   sql_performance_changed.sql
--
-- Purpose:     Lists SQL Statements with Elapsed Time per Execution changing over time
--
-- Author:      Carlos Sierra
--
-- Version:     2014/10/31
--
-- Usage:       Lists statements that have changed their elapsed time per execution over
--              some history.
--              Uses the ration between "elapsed time per execution" and the median of
--              this metric for SQL statements within the sampled history, and using
--              linear regression identifies those that have changed the most. In other
--              words where the slope of the linear regression is larger. Positive slopes
--              are considered "improving" while negative are "regressing".
--
-- Example:     @sql_performance_changed.sql
--
-- Notes:       Developed and tested on 11.2.0.3.
--
--              Requires an Oracle Diagnostics Pack License since AWR data is accessed.
--
--              To further investigate poorly performing SQL use sqltxplain.sql or sqlhc
--              (or planx.sql or sqlmon.sql or sqlash.sql).
--            
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--
SPO sql_performance_changed.txt;
DEF days_of_history_accessed = '31';
DEF captured_at_least_x_times = '10';
DEF captured_at_least_x_days_apart = '5';
DEF med_elap_microsecs_threshold = '1e4';
DEF min_slope_threshold = '0.1';
DEF max_num_rows = '20';
 
SET lin 200 ver OFF;
COL row_n FOR A2 HEA '#';
COL med_secs_per_exec HEA 'Median Secs|Per Exec';
COL std_secs_per_exec HEA 'Std Dev Secs|Per Exec';
COL avg_secs_per_exec HEA 'Avg Secs|Per Exec';
COL min_secs_per_exec HEA 'Min Secs|Per Exec';
COL max_secs_per_exec HEA 'Max Secs|Per Exec';
COL plans FOR 9999;
COL sql_text_80 FOR A80;
 
PRO SQL Statements with "Elapsed Time per Execution" changing over time
 
WITH
per_time AS (
SELECT h.dbid,
       h.sql_id,
       SYSDATE - CAST(s.end_interval_time AS DATE) days_ago,
       SUM(h.elapsed_time_total) / SUM(h.executions_total) time_per_exec
  FROM dba_hist_sqlstat h,
       dba_hist_snapshot s
 WHERE h.executions_total > 0
   AND s.snap_id = h.snap_id
   AND s.dbid = h.dbid
   AND s.instance_number = h.instance_number
   AND CAST(s.end_interval_time AS DATE) > SYSDATE - &&days_of_history_accessed.
 GROUP BY
       h.dbid,
       h.sql_id,
       SYSDATE - CAST(s.end_interval_time AS DATE)
),
avg_time AS (
SELECT dbid,
       sql_id,
       MEDIAN(time_per_exec) med_time_per_exec,
       STDDEV(time_per_exec) std_time_per_exec,
       AVG(time_per_exec)    avg_time_per_exec,
       MIN(time_per_exec)    min_time_per_exec,
       MAX(time_per_exec)    max_time_per_exec      
  FROM per_time
 GROUP BY
       dbid,
       sql_id
HAVING COUNT(*) >= &&captured_at_least_x_times.
   AND MAX(days_ago) - MIN(days_ago) >= &&captured_at_least_x_days_apart.
   AND MEDIAN(time_per_exec) > &&med_elap_microsecs_threshold.
),
time_over_median AS (
SELECT h.dbid,
       h.sql_id,
       h.days_ago,
       (h.time_per_exec / a.med_time_per_exec) time_per_exec_over_med,
       a.med_time_per_exec,
       a.std_time_per_exec,
       a.avg_time_per_exec,
       a.min_time_per_exec,
       a.max_time_per_exec
  FROM per_time h, avg_time a
 WHERE a.sql_id = h.sql_id
),
ranked AS (
SELECT RANK () OVER (ORDER BY ABS(REGR_SLOPE(t.time_per_exec_over_med, t.days_ago)) DESC) rank_num,
       t.dbid,
       t.sql_id,
       CASE WHEN REGR_SLOPE(t.time_per_exec_over_med, t.days_ago) > 0 THEN 'IMPROVING' ELSE 'REGRESSING' END change,
       ROUND(REGR_SLOPE(t.time_per_exec_over_med, t.days_ago), 3) slope,
       ROUND(AVG(t.med_time_per_exec)/1e6, 3) med_secs_per_exec,
       ROUND(AVG(t.std_time_per_exec)/1e6, 3) std_secs_per_exec,
       ROUND(AVG(t.avg_time_per_exec)/1e6, 3) avg_secs_per_exec,
       ROUND(MIN(t.min_time_per_exec)/1e6, 3) min_secs_per_exec,
       ROUND(MAX(t.max_time_per_exec)/1e6, 3) max_secs_per_exec
  FROM time_over_median t
 GROUP BY
       t.dbid,
       t.sql_id
HAVING ABS(REGR_SLOPE(t.time_per_exec_over_med, t.days_ago)) > &&min_slope_threshold.
)
SELECT LPAD(ROWNUM, 2) row_n,
       r.sql_id,
       r.change,
       TO_CHAR(r.slope, '990.000MI') slope,
       TO_CHAR(r.med_secs_per_exec, '999,990.000') med_secs_per_exec,
       TO_CHAR(r.std_secs_per_exec, '999,990.000') std_secs_per_exec,
       TO_CHAR(r.avg_secs_per_exec, '999,990.000') avg_secs_per_exec,
       TO_CHAR(r.min_secs_per_exec, '999,990.000') min_secs_per_exec,
       TO_CHAR(r.max_secs_per_exec, '999,990.000') max_secs_per_exec,
       (SELECT COUNT(DISTINCT p.plan_hash_value) FROM dba_hist_sql_plan p WHERE p.dbid = r.dbid AND p.sql_id = r.sql_id) plans,
       REPLACE((SELECT DBMS_LOB.SUBSTR(s.sql_text, 80) FROM dba_hist_sqltext s WHERE s.dbid = r.dbid AND s.sql_id = r.sql_id), CHR(10)) sql_text_80
  FROM ranked r
 WHERE r.rank_num <= &&max_num_rows.
 ORDER BY
       r.rank_num
/
 
SPO OFF;