Oracle 11g Adaptive Cursor Sharing (ACS)

Ah, the long awaited fix for the Bind Variable Peeking problem.

Adaptive Cursor Sharing (ACS) sounds great if you say it fast. Unfortunately it doesn’t work quite as well as I had hoped (at least as of 11.1.0.7). I was really hoping that we’d never have to worry about plan instability due to bind variable peeking again, but it seems that will remain an elusive goal for a while longer.

So the goal of this post is to provide some data about how ACS works based on observations of a couple of production systems. By the way, this post assumes you already have a basic understanding of how ACS works. There are some links at the bottom of this post to other references and in particular, this post is a good basic description of ACS.

So here’s some background info:
Observations were made on a version 10.2.0.4 RAC database that was being migrated to an 11.1.0.7 RAC database. Both are on Redhat Linux and similar Dell hardware. The version 10 database had several queries which suffered from bind variable peeking issues which were addressed with Outlines (while the developers considered using literals). Also, the statements were using real bind variables, not the fake kind that result from setting the cursor_sharing parameter. We were hoping that ACS would solve the bind variable peeking problem without manual intervention (i.e. without using Outlines or SQL Profiles or Baselines to lock in a specific plan).

I have used several scripts in this post:

unstable_plans.sql – this one shows statements that have multiple plans with large variance in execution time
awr_plan_change.sql – history of how the statement plan changes over time
awr_plan_stats.sql – aggregate statement stats (like elapsed_time, lio, etc) grouped by plan
find_sql_acs.sql – A queries v$sql and shows ACS related columns
mismatch3.sql – A variation of Dion Cho’s script to display data from v$sql_shared_cursor (see his post here)

The first couple of these scripts I discussed in a previous post on Plan Instability. I also did a previous post that is a basic overview of the Bind Variable Peeking issue, if you want a little more background info.

So here’s a look at what’s going on with that newly migrated system:

SQL*Plus: Release 11.1.0.7.0 - Production on Mon May 4 19:53:00 2009
 
Copyright (c) 1982, 2008, Oracle.  All rights reserved.
 
 
Connected to:
Oracle Database 11g Enterprise Edition Release 11.1.0.7.0 - 64bit Production
With the Partitioning, Real Application Clusters, OLAP, Data Mining
and Real Application Testing options
 
SQL> -- find statements with multiple plans with big differences in elapsed time
SQL>
SQL> @unstable_plans
Enter value for min_stddev:
Enter value for min_etime: 1
 
SQL_ID        SUM(EXECS)   MIN_ETIME   MAX_ETIME   NORM_STDDEV
------------- ---------- ----------- ----------- -------------
f2pz10qx59awc          2       11.75       45.31        2.0197
5mh2127hkzbtr         70        2.64       18.06        3.0272
0hur96bxr18jn         24        1.65        9.14        3.1981
76gduk3urk91d          6        9.75       57.82        3.4880
cqxkwk9hp8rpf         31        7.18       43.77        3.6015
3u2bxt4y0740a         17        0.49        4.19        4.1316
af6j2dyzawp7w         78        6.83       60.31        4.4492
2mzzy3u2rtgqx         93        4.55       34.13        4.6025
6vb3gxdfzbhuz         33        0.63        5.21        5.1502
gc69y3vv5ws31         72        0.87        7.64        5.5128
b6zcb86sub9gv          2        0.95        8.74        5.8349
6pdbja617d2g7          2        2.24       23.55        6.7132
cc7yv55yn2wzm          5        0.26        3.05        7.4533
ach69kkyac77x          5        0.23        2.65        7.5202
09xqs3yhmnnc2         82        0.31        4.47        7.5534
3zqwzanpnddt1          2        0.69        8.75        8.2026
70zr1cg7ssfkw          2        0.71        9.04        8.2487
664tcunn5nks9          3        0.36        4.83        8.7858
39f6bx40awrms          2        0.74       10.15        9.0125
5z7v0n6amf8yx        116        9.06      125.53        9.0942
3q67n6qh7tcqv          2        0.08        1.20        9.2843
30yrz0qst88mj         68        0.21        2.97        9.3903
a1mk6hw6s20an         19        0.26        3.78        9.6454
26070mzfxps8d         72        0.18        2.75       10.0027
byznf81kmwumv          2        0.75       11.45       10.0407
1fj1qcqtmgmd1          2        0.54        9.33       11.4092
fg96c4y95u3s8          2        0.49        9.18       12.6745
chxn6vwj02xj4          2        0.65       12.27       12.7001
2xg8psmr3k7vz          2        0.76       14.38       12.7429
grysxv4s2hhkb          2        0.63       12.10       12.8338
2bfs79h84xsch        148        5.65      108.87       12.9179
4qz01hjwat4u3         39        0.27        5.50       13.6528
3wj5ngbv1sa9x          2        0.40        8.70       14.7151
g68szg2ydq6dg         14        0.26        7.48       19.4587
9vt6aaf5xcmh2        381        0.67       24.90       19.9706
cs8ng5sv7jgj4          4        1.12       35.70       21.8969
12a2xbmwn5v6z          7        0.23        8.08       23.7235
d2x7g9wr30v33          4       12.45      638.60       25.4008
4ymph98r42nbj        192        0.11        4.43       26.9188
1uby0zcw55cnp          4        0.63       31.22       34.3088
4jhx8qrkzztqg         15        1.22       66.07       37.6215
7xu6y0cvs55gh         34        0.44       30.08       37.9640
6hstnb2fghg76         77        0.65       49.01       39.2329
gzwgbycgs0fx9        265        0.08        7.37       47.4965
f028rmkp3qjvq         47        0.03        1.99       48.5307
7s1nc9wa2pc4r          2        0.19       15.53       57.6592
f2tm6xrb26y51          2        0.17       14.80       61.7260
0xz1j5y313f3c        206        0.02        2.38       71.6444
3dhwvfmkjzwtv         72        1.24      154.56       87.6684
fb90nawgwx3mj         37        0.34       51.96      108.3873
b7d0d3gu5fvqp         22        0.13       33.85      137.5321
ghdy23pftj44q       1100        0.02        5.93      143.7765
7v2jtb3u02qx6         10        0.43      139.36      172.2951
fw9ntwzhygmcq         87        0.32      100.44      220.3149
gxv6umvct0xsv       4188        0.84      333.79      225.1338
6jdu11g4zzjkh         42        0.41      137.88      234.5440
2wrngntk7v0st        183        0.11       50.61      333.9597
27wha8b8s21xw       1112        0.01        7.08      408.3026
dhmvcrmgdk3sn        881        0.05       46.99      620.1920
6u4c54k36ngwf       4329        0.00        4.39      656.4506
8jt9yh7jf8tn8       4788        0.09      160.35    1,251.5684
4fy7uznh9zz27       4723        0.03       47.16    1,256.8971
2ddh1h012t8au         12        0.03       67.62    1,491.8099
fw9hrrv37hb3v          5        0.04      100.86    1,503.5361
68wg4gjb51dsh       4411        0.01       16.44    1,539.4726
7d407h5cqmv81       4202        0.00      180.63   28,768.6107
 
66 rows selected.

Please note that the unstable_plan.sql script is not guaranteed to find every statement that suffers from plan instability, because some of the good plans never make it into the AWR tables. This is due to the fact that AWR only grabs the “worst” statements in the various categories that AWR reports (i.e. elapsed time, cpu time, gets, reads, and executions). But you could argue that it will find the most important ones, because even when they run fast they still end up in the top of at least one category. Anyway, it’s obvious that there are many statements that are running with multiple plans with wide variances in their execution time.

So let’s look a little closer:

SQL> -- Let's check out the worst one on the list
SQL> --   first let's see how many plans have been used and how they stack up
SQL>
SQL> @awr_plan_stats
Enter value for sql_id: 7d407h5cqmv81
Enter value for snap_id:
 
SQL_ID        PLAN_HASH_VALUE        EXECS          ETIME    AVG_ETIME        AVG_LIO
------------- --------------- ------------ -------------- ------------ --------------
7d407h5cqmv81      4289789142          840            2.4        0.003          273.7
7d407h5cqmv81      1007536393          551          116.2        0.211       14,563.1
7d407h5cqmv81      1723168170        2,852       44,716.2       15.679      255,603.3
7d407h5cqmv81      2337118685            1          180.6      180.629    6,495,990.0
 
SQL> -- So the best plan was executed 840 times and took .003 seconds on average 
SQL> -- The worst one was only executed once but took 180.6 seconds and did about 6.5M lios
SQL>
SQL>  -- Now let's see if it looks like bind variable peeking - (i.e. the plan is flip-flopping)
SQL>
SQL> @awr_plan_change
Enter value for sql_id: 7d407h5cqmv81
 
   SNAP_ID   NODE BEGIN_INTERVAL_TIME            SQL_ID        PLAN_HASH_VALUE        EXECS    AVG_ETIME        AVG_LIO
---------- ------ ------------------------------ ------------- --------------- ------------ ------------ --------------
      1732      2 22-APR-09 01.00.06.582 PM      7d407h5cqmv81      1007536393            1        1.478        5,269.0
      1733      2 22-APR-09 02.00.06.425 PM      7d407h5cqmv81                            8        1.635       14,580.0
      1734      2 22-APR-09 03.00.01.366 PM      7d407h5cqmv81                            6        0.196       14,580.0
      1734      3 22-APR-09 03.00.00.710 PM      7d407h5cqmv81      1723168170            2        8.891      228,740.5
      1735      2 22-APR-09 04.00.19.942 PM      7d407h5cqmv81      1007536393            3        0.189       14,580.0
      1736      2 22-APR-09 05.00.06.982 PM      7d407h5cqmv81                           63        0.188       14,580.0
      1736      3 22-APR-09 05.00.06.350 PM      7d407h5cqmv81      1723168170           22        9.564      236,902.3
      1737      2 22-APR-09 06.00.03.582 PM      7d407h5cqmv81      1007536393          244        0.187       14,580.0
      1737      3 22-APR-09 06.00.04.267 PM      7d407h5cqmv81      1723168170           76        9.505      236,959.9
      1738      2 22-APR-09 07.00.28.278 PM      7d407h5cqmv81      1007536393          226        0.188       14,580.0
      1738      3 22-APR-09 07.00.28.926 PM      7d407h5cqmv81      1723168170           71        9.395      240,745.0
      1739      2 22-APR-09 08.00.09.681 PM      7d407h5cqmv81                           81       11.114      253,481.2
      1739      3 22-APR-09 08.00.10.422 PM      7d407h5cqmv81                           22        9.866      249,882.3
      1740      2 22-APR-09 09.00.43.176 PM      7d407h5cqmv81                          215       13.682      256,467.0
      1740      3 22-APR-09 09.00.43.910 PM      7d407h5cqmv81                           80       12.605      252,606.0
      1741      2 22-APR-09 10.00.16.298 PM      7d407h5cqmv81                          367       20.209      256,157.1
      1741      3 22-APR-09 10.00.17.072 PM      7d407h5cqmv81                          214       15.039      257,287.3
      1742      2 22-APR-09 11.00.28.426 PM      7d407h5cqmv81                          376       17.855      257,066.5
      1742      3 22-APR-09 11.00.27.666 PM      7d407h5cqmv81                          178       13.437      255,902.4
      1743      2 23-APR-09 12.00.16.137 AM      7d407h5cqmv81                          352       18.639      257,326.6
      1743      3 23-APR-09 12.00.15.386 AM      7d407h5cqmv81                          182       13.787      258,192.2
      1744      2 23-APR-09 01.00.03.520 AM      7d407h5cqmv81                          285       16.275      256,335.3
      1744      3 23-APR-09 01.00.02.838 AM      7d407h5cqmv81                           94       13.492      258,508.9
      1745      2 23-APR-09 02.00.21.107 AM      7d407h5cqmv81                          132       14.876      258,913.5
      1745      3 23-APR-09 02.00.20.482 AM      7d407h5cqmv81                          103       13.113      256,821.0
      1750      2 23-APR-09 07.00.33.920 AM      7d407h5cqmv81      4289789142           77        0.002          267.0
      1753      2 23-APR-09 09.34.00.440 AM      7d407h5cqmv81                          278        0.001          267.0
      1754      2 23-APR-09 11.00.06.058 AM      7d407h5cqmv81                           96        0.001          267.0
      1754      3 23-APR-09 11.00.05.422 AM      7d407h5cqmv81                           42        0.000          267.0
      1755      2 23-APR-09 11.17.45.649 AM      7d407h5cqmv81                          283        0.001          267.0
      1756      2 23-APR-09 12.00.35.977 PM      7d407h5cqmv81                           62        0.000          267.0
      1894      3 29-APR-09 06.00.09.823 AM      7d407h5cqmv81                            1        0.444        2,777.0
      1900      2 29-APR-09 12.00.36.427 PM      7d407h5cqmv81      2337118685            1      180.629    6,495,990.0
      1943      3 01-MAY-09 07.00.02.507 AM      7d407h5cqmv81      4289789142            1        1.199        3,426.0
 
34 rows selected.
 
SQL> -- It does look like a typical bind variable peeking flip-flop pattern
SQL>
SQL> -- Now let's see if it's still in the shared pool and if it's bind aware
SQL>
SQL> @find_sql_acs
Enter value for sql_text:
Enter value for sql_id: 7d407h5cqmv81
Enter value for is_bind_aware:
 
SQL_ID         CHILD PLAN_HASH_VALUE IBS IBA ISH      EXECS ROWS_PROCESSED  AVG_ETIME    AVG_CPU    AVG_PIO    AVG_LIO SQL_TEXT
------------- ------ --------------- --- --- --- ---------- -------------- ---------- ---------- ---------- ---------- ------------------------------
7d407h5cqmv81      0      4289789142 N   N   Y            2              2       0.62       0.07     315.50      1,758 SELECT COUNT(*) as total_recor
7d407h5cqmv81      1      4289789142 N   N   Y            2              2       0.03       0.01       1.00        264
 
SQL> -- It is in the shared pool, but it is not bind aware
SQL>

So the previous example showed a statement that had several plans, one of which definitely had better performance characteristics. But since there was only one plan in the shared pool at the time we examined it, there is is no reason to expect that Oracle would have recognized that the statement should be bind aware. This brings up an interesting point. It does not appear that (at least as of 11.1.0.7) Oracle keeps track of bind sensitivity of a statement persistently. That is to say, if the statement gets flushed for any reason, the optimizer appears to completely forget about any analysis it has done up to that point. Thus the painful (for the user) process of discovering which sets of bind variables should go with which plan starts all over.

So here’s another statement:

SQL> -- another example from the list of unstable_plans
SQL>
SQL> @awr_plan_stats
Enter value for sql_id: 8jt9yh7jf8tn8
 
SQL_ID        PLAN_HASH_VALUE        EXECS          ETIME    AVG_ETIME        AVG_LIO
------------- --------------- ------------ -------------- ------------ --------------
8jt9yh7jf8tn8      1093407144        4,818          481.5        0.100        2,818.6
8jt9yh7jf8tn8      4076066623           21        3,269.3      155.679    5,901,988.0
 
SQL> @awr_plan_change
Enter value for sql_id: 8jt9yh7jf8tn8
 
   SNAP_ID   NODE BEGIN_INTERVAL_TIME            SQL_ID        PLAN_HASH_VALUE        EXECS    AVG_ETIME        AVG_LIO
---------- ------ ------------------------------ ------------- --------------- ------------ ------------ --------------
      1785      3 24-APR-09 05.00.13.361 PM      8jt9yh7jf8tn8      1093407144            6        1.102        2,872.7
      1786      2 24-APR-09 06.00.02.510 PM      8jt9yh7jf8tn8                          158        0.024        2,873.0
      1786      3 24-APR-09 06.00.03.170 PM      8jt9yh7jf8tn8                          223        0.023        2,873.0
      1787      2 24-APR-09 07.00.30.171 PM      8jt9yh7jf8tn8                          749        0.020        2,873.0
      1787      3 24-APR-09 07.00.30.935 PM      8jt9yh7jf8tn8                          873        0.019        2,873.0
      1788      2 24-APR-09 08.00.03.359 PM      8jt9yh7jf8tn8                          726        0.020        2,873.9
      1788      3 24-APR-09 08.00.04.148 PM      8jt9yh7jf8tn8                          871        0.020        2,873.9
      1789      2 24-APR-09 09.00.28.203 PM      8jt9yh7jf8tn8                          373        0.016        2,874.0
      1789      3 24-APR-09 09.00.27.481 PM      8jt9yh7jf8tn8                          566        0.016        2,874.0
      1892      2 29-APR-09 04.00.02.385 AM      8jt9yh7jf8tn8                            1        2.613        3,811.0
      1894      2 29-APR-09 06.00.09.154 AM      8jt9yh7jf8tn8                            2        0.462          733.0
      1894      3 29-APR-09 06.00.09.823 AM      8jt9yh7jf8tn8                            2        1.056          847.0
      1895      2 29-APR-09 07.00.00.226 AM      8jt9yh7jf8tn8                            7        1.714        2,869.6
      1895      3 29-APR-09 07.00.00.921 AM      8jt9yh7jf8tn8                            2        0.856        1,208.0
      1896      2 29-APR-09 08.00.20.446 AM      8jt9yh7jf8tn8                            9        1.635        2,103.0
      1897      2 29-APR-09 09.00.09.367 AM      8jt9yh7jf8tn8                            2        8.179        8,529.0
      1897      3 29-APR-09 09.00.10.115 AM      8jt9yh7jf8tn8                           17        1.714        3,416.5
      1898      2 29-APR-09 10.00.43.551 AM      8jt9yh7jf8tn8                            5        2.553        2,733.2
      1898      3 29-APR-09 10.00.42.788 AM      8jt9yh7jf8tn8                            6        3.751        4,484.2
      1899      3 29-APR-09 11.00.10.447 AM      8jt9yh7jf8tn8                            7        1.742        3,284.4
      1900      3 29-APR-09 12.00.35.788 PM      8jt9yh7jf8tn8                            2        1.199          966.0
      1901      2 29-APR-09 01.00.18.515 PM      8jt9yh7jf8tn8                            8        2.345        2,409.6
      1902      3 29-APR-09 02.00.15.910 PM      8jt9yh7jf8tn8                            2        3.941        2,649.5
      1905      2 29-APR-09 05.00.02.254 PM      8jt9yh7jf8tn8                            1        0.887        1,230.0
      1918      2 30-APR-09 06.00.09.089 AM      8jt9yh7jf8tn8                            1        0.653        1,248.0
      1918      3 30-APR-09 06.00.08.403 AM      8jt9yh7jf8tn8                            2        0.421          485.5
      1919      2 30-APR-09 07.00.28.148 AM      8jt9yh7jf8tn8                            1        1.152        1,242.0
      1920      2 30-APR-09 08.00.03.733 AM      8jt9yh7jf8tn8                            4        3.273        3,200.3
      1920      3 30-APR-09 08.00.04.389 AM      8jt9yh7jf8tn8                           12        2.491        3,314.2
      1921      2 30-APR-09 09.00.10.125 AM      8jt9yh7jf8tn8                            5        3.947        3,333.4
      1921      3 30-APR-09 09.00.10.838 AM      8jt9yh7jf8tn8                            2        2.416        1,769.5
      1922      3 30-APR-09 10.00.25.754 AM      8jt9yh7jf8tn8      4076066623            2       54.237    2,291,432.5
      1923      2 30-APR-09 11.00.17.345 AM      8jt9yh7jf8tn8      1093407144            2        0.812          975.0
      1923      3 30-APR-09 11.00.18.032 AM      8jt9yh7jf8tn8      4076066623            3      134.031      933,124.3
      1924      3 30-APR-09 12.00.15.448 PM      8jt9yh7jf8tn8                            3      227.009    6,987,169.3
      1926      2 30-APR-09 02.00.11.921 PM      8jt9yh7jf8tn8      1093407144            8        0.818        1,574.5
      1926      3 30-APR-09 02.00.11.174 PM      8jt9yh7jf8tn8      4076066623            2      175.709    8,963,417.0
      1927      2 30-APR-09 03.00.24.923 PM      8jt9yh7jf8tn8      1093407144            4        1.344        1,068.8
      1927      3 30-APR-09 03.00.24.306 PM      8jt9yh7jf8tn8      4076066623            5      156.378   10,159,992.0
      1928      2 30-APR-09 04.00.30.061 PM      8jt9yh7jf8tn8      1093407144            6        0.923        1,225.8
      1928      3 30-APR-09 04.00.29.416 PM      8jt9yh7jf8tn8      4076066623            1      180.488    2,150,190.0
      1930      3 30-APR-09 06.00.37.119 PM      8jt9yh7jf8tn8                            2      180.371    8,255,881.5
      1934      3 30-APR-09 10.00.12.055 PM      8jt9yh7jf8tn8                            1      180.491    3,102,577.0
      1939      2 01-MAY-09 03.00.31.764 AM      8jt9yh7jf8tn8      1093407144           21        0.825        1,041.8
      1939      3 01-MAY-09 03.00.32.453 AM      8jt9yh7jf8tn8                            4        0.575        1,211.8
      1944      3 01-MAY-09 08.00.15.686 AM      8jt9yh7jf8tn8                            6        1.328        1,788.3
      1946      2 01-MAY-09 10.00.17.105 AM      8jt9yh7jf8tn8                            1        1.170        2,411.0
      1946      3 01-MAY-09 10.00.16.458 AM      8jt9yh7jf8tn8                            4        2.041        2,414.3
      1947      3 01-MAY-09 11.00.14.385 AM      8jt9yh7jf8tn8                           10        1.725        2,937.1
      1948      3 01-MAY-09 12.00.08.928 PM      8jt9yh7jf8tn8                            3        2.232        3,415.7
      1987      2 03-MAY-09 03.00.03.550 AM      8jt9yh7jf8tn8                            7        1.029          901.0
      1990      3 03-MAY-09 06.00.07.641 AM      8jt9yh7jf8tn8                            3        1.225        1,465.7
      1991      3 03-MAY-09 07.00.05.445 AM      8jt9yh7jf8tn8                           26        0.370          710.5
      1992      2 03-MAY-09 08.00.20.010 AM      8jt9yh7jf8tn8                            6        0.213          685.7
      1992      3 03-MAY-09 08.00.19.366 AM      8jt9yh7jf8tn8                            3        0.658          883.0
      1993      2 03-MAY-09 09.00.04.983 AM      8jt9yh7jf8tn8                            8        0.769          950.9
      1996      2 03-MAY-09 12.00.19.205 PM      8jt9yh7jf8tn8                            2        0.101          861.5
      2015      3 04-MAY-09 07.00.13.869 AM      8jt9yh7jf8tn8                            4        0.376          854.5
      2016      3 04-MAY-09 08.00.09.477 AM      8jt9yh7jf8tn8                            6        0.143          571.0
      2019      2 04-MAY-09 11.00.11.317 AM      8jt9yh7jf8tn8                           12        0.937        1,352.1
      2019      3 04-MAY-09 11.00.10.691 AM      8jt9yh7jf8tn8                           10        1.612        1,341.9
      2019      3 04-MAY-09 11.00.10.691 AM      8jt9yh7jf8tn8      4076066623            1       41.592    3,942,672.0
      2020      2 04-MAY-09 12.00.06.355 PM      8jt9yh7jf8tn8      1093407144           15        1.037        1,734.6
      2020      3 04-MAY-09 12.00.06.919 PM      8jt9yh7jf8tn8      4076066623            1      181.044    1,764,007.0
      2022      2 04-MAY-09 02.00.26.599 PM      8jt9yh7jf8tn8      1093407144            2        2.214        2,780.5
 
65 rows selected.
 
SQL> -- typical bind variable peeking pattern
SQL> -- let's look at just one node - it'll be a little more clear
SQL> l8
  8* and ss.instance_number = S.instance_number
SQL> i
  9i and s.instance_number = &inst
 10i
SQL>
SQL> /
Enter value for sql_id: 8jt9yh7jf8tn8
Enter value for inst: 3
 
   SNAP_ID   NODE BEGIN_INTERVAL_TIME            SQL_ID        PLAN_HASH_VALUE        EXECS    AVG_ETIME        AVG_LIO
---------- ------ ------------------------------ ------------- --------------- ------------ ------------ --------------
      1785      3 24-APR-09 05.00.13.361 PM      8jt9yh7jf8tn8      1093407144            6        1.102        2,872.7
      1786      3 24-APR-09 06.00.03.170 PM      8jt9yh7jf8tn8                          223        0.023        2,873.0
      1787      3 24-APR-09 07.00.30.935 PM      8jt9yh7jf8tn8                          873        0.019        2,873.0
      1788      3 24-APR-09 08.00.04.148 PM      8jt9yh7jf8tn8                          871        0.020        2,873.9
      1789      3 24-APR-09 09.00.27.481 PM      8jt9yh7jf8tn8                          566        0.016        2,874.0
      1894      3 29-APR-09 06.00.09.823 AM      8jt9yh7jf8tn8                            2        1.056          847.0
      1895      3 29-APR-09 07.00.00.921 AM      8jt9yh7jf8tn8                            2        0.856        1,208.0
      1897      3 29-APR-09 09.00.10.115 AM      8jt9yh7jf8tn8                           17        1.714        3,416.5
      1898      3 29-APR-09 10.00.42.788 AM      8jt9yh7jf8tn8                            6        3.751        4,484.2
      1899      3 29-APR-09 11.00.10.447 AM      8jt9yh7jf8tn8                            7        1.742        3,284.4
      1900      3 29-APR-09 12.00.35.788 PM      8jt9yh7jf8tn8                            2        1.199          966.0
      1902      3 29-APR-09 02.00.15.910 PM      8jt9yh7jf8tn8                            2        3.941        2,649.5
      1918      3 30-APR-09 06.00.08.403 AM      8jt9yh7jf8tn8                            2        0.421          485.5
      1920      3 30-APR-09 08.00.04.389 AM      8jt9yh7jf8tn8                           12        2.491        3,314.2
      1921      3 30-APR-09 09.00.10.838 AM      8jt9yh7jf8tn8                            2        2.416        1,769.5
      1922      3 30-APR-09 10.00.25.754 AM      8jt9yh7jf8tn8      4076066623            2       54.237    2,291,432.5
      1923      3 30-APR-09 11.00.18.032 AM      8jt9yh7jf8tn8                            3      134.031      933,124.3
      1924      3 30-APR-09 12.00.15.448 PM      8jt9yh7jf8tn8                            3      227.009    6,987,169.3
      1926      3 30-APR-09 02.00.11.174 PM      8jt9yh7jf8tn8                            2      175.709    8,963,417.0
      1927      3 30-APR-09 03.00.24.306 PM      8jt9yh7jf8tn8                            5      156.378   10,159,992.0
      1928      3 30-APR-09 04.00.29.416 PM      8jt9yh7jf8tn8                            1      180.488    2,150,190.0
      1930      3 30-APR-09 06.00.37.119 PM      8jt9yh7jf8tn8                            2      180.371    8,255,881.5
      1934      3 30-APR-09 10.00.12.055 PM      8jt9yh7jf8tn8                            1      180.491    3,102,577.0
      1939      3 01-MAY-09 03.00.32.453 AM      8jt9yh7jf8tn8      1093407144            4        0.575        1,211.8
      1944      3 01-MAY-09 08.00.15.686 AM      8jt9yh7jf8tn8                            6        1.328        1,788.3
      1946      3 01-MAY-09 10.00.16.458 AM      8jt9yh7jf8tn8                            4        2.041        2,414.3
      1947      3 01-MAY-09 11.00.14.385 AM      8jt9yh7jf8tn8                           10        1.725        2,937.1
      1948      3 01-MAY-09 12.00.08.928 PM      8jt9yh7jf8tn8                            3        2.232        3,415.7
      1990      3 03-MAY-09 06.00.07.641 AM      8jt9yh7jf8tn8                            3        1.225        1,465.7
      1991      3 03-MAY-09 07.00.05.445 AM      8jt9yh7jf8tn8                           26        0.370          710.5
      1992      3 03-MAY-09 08.00.19.366 AM      8jt9yh7jf8tn8                            3        0.658          883.0
      2015      3 04-MAY-09 07.00.13.869 AM      8jt9yh7jf8tn8                            4        0.376          854.5
      2016      3 04-MAY-09 08.00.09.477 AM      8jt9yh7jf8tn8                            6        0.143          571.0
      2019      3 04-MAY-09 11.00.10.691 AM      8jt9yh7jf8tn8      4076066623            1       41.592    3,942,672.0
      2019      3 04-MAY-09 11.00.10.691 AM      8jt9yh7jf8tn8      1093407144           10        1.612        1,341.9
      2020      3 04-MAY-09 12.00.06.919 PM      8jt9yh7jf8tn8      4076066623            1      181.044    1,764,007.0
      2031      3 04-MAY-09 11.00.03.519 PM      8jt9yh7jf8tn8      1093407144            1        0.737          482.0
      2039      3 05-MAY-09 07.00.27.610 AM      8jt9yh7jf8tn8      4076066623            5       42.900    4,295,251.8
      2041      3 05-MAY-09 09.00.09.829 AM      8jt9yh7jf8tn8                            2        3.282    1,968,698.5
      2044      3 05-MAY-09 12.00.16.920 PM      8jt9yh7jf8tn8      1093407144            2        1.535          844.5
      2045      3 05-MAY-09 01.00.08.637 PM      8jt9yh7jf8tn8                            2        2.384        1,683.5
 
41 rows selected.
 
SQL> -- the plans are clearly flip-flopping
SQL> -- and the performance of plan 1093407144 is clearly orders of magnitude better
SQL> 
SQL> -- Let's see what's in the shared pool
SQL>
SQL> @find_sql_acs
Enter value for sql_text:
Enter value for sql_id: 8jt9yh7jf8tn8
Enter value for is_bind_aware:
 
SQL_ID         CHILD PLAN_HASH_VALUE IBS IBA ISH      EXECS ROWS_PROCESSED  AVG_ETIME    AVG_CPU    AVG_PIO    AVG_LIO SQL_TEXT
------------- ------ --------------- --- --- --- ---------- -------------- ---------- ---------- ---------- ---------- -----------------------------------
8jt9yh7jf8tn8      0      4076066623 N   N   Y           19              6     160.35      29.28 ##########  6,222,898 SELECT row_order, cdr_id, site_id,
8jt9yh7jf8tn8      1      1093407144 N   N   Y           61              0       1.92       0.13     565.70      2,860 SELECT row_order, cdr_id, site_id,
8jt9yh7jf8tn8      2                 N   N   Y           55              0       1.01       0.06     252.09      1,555 SELECT row_order, cdr_id, site_id,
 
SQL> -- So there are children with both plans in the shared the pool (135 execs total)
SQL> -- But the cursors are not marked as bind aware
SQL> -- So why are there multiple child cursors?
SQL> -- (using a modified version of Dion Cho's script)
SQL>
SQL> @mismatch3
Enter value for sql_id: 8jt9yh7jf8tn8
SQL_ID                         = 8jt9yh7jf8tn8
CHILD_NUMBER                   = 1
--------------------------------------------------
SQL_ID                         = 8jt9yh7jf8tn8
CHILD_NUMBER                   = 0
ROLL_INVALID_MISMATCH          = Y
--------------------------------------------------
SQL_ID                         = 8jt9yh7jf8tn8
CHILD_NUMBER                   = 2
ROLL_INVALID_MISMATCH          = Y
--------------------------------------------------
 
PL/SQL procedure successfully completed.
 
SQL> -- none of the bind related flags show up, so it doesn't look promising for ACS
SQL> --

Brief Digression: The ROLL_INVALID_MISMATCH flag has to do with changing stats using AUTO_INVALIDATE which does not cause cursors to be immediately invalidated, but instead let’s them be invalidated over a rolling window (_optimizer_invalidation_period which defaults to 5 hours).

So then I got to wondering if any statements were being marked as bind aware.

SQL> @find_sql_acs
Enter value for sql_text:
Enter value for sql_id:
Enter value for is_bind_aware: Y
 
SQL_ID         CHILD PLAN_HASH_VALUE IBS IBA ISH      EXECS ROWS_PROCESSED  AVG_ETIME    AVG_CPU    AVG_PIO    AVG_LIO SQL_TEXT
------------- ------ --------------- --- --- --- ---------- -------------- ---------- ---------- ---------- ---------- ---------------
0qvgb3dyfg539      1       722236007 Y   Y   Y            2              0        .15        .02      23.00      3,487 SELECT row_orde
17uuqnvxmzxhj      1      3038781757 Y   Y   Y           31             31        .17        .01      43.74      1,126 SELECT COUNT(*)
                   3      3038781757 Y   Y   N           21             21        .02        .02       1.33      7,290
                   4      3038781757 Y   Y   Y           52             52        .23        .02     120.29      2,046
                   6      3038781757 Y   Y   Y           51             51        .00        .00        .10        284
34x6683rpwtxa      4       722236007 Y   Y   Y           18            164        .01        .00        .17        498 SELECT row_orde
3tfx8fzp64vkb      1      3038781757 Y   Y   Y            2              2        .01        .01        .00      1,178 SELECT COUNT(*)
4vb86f36xqc50      1      2983410489 Y   Y   Y           62           1683        .12        .01      53.76        960 SELECT row_orde
                   4      2983410489 Y   Y   Y            7            163        .69        .07     328.43        723
58p0j1q6rmv34      1      1144901783 Y   Y   Y            2              2        .02        .00        .00        335 SELECT COUNT(*)
5mxqphz5qfs4d      1      1144901783 Y   Y   Y            2              2        .02        .00        .00         54 SELECT COUNT(*)
dt1v1cmua9cnq      1      4076066623 Y   Y   Y            8             37       3.47       3.41      15.63  2,233,144 SELECT row_orde
ftxa99d89yzz0      1      4289789142 Y   Y   Y            2              2        .01        .00        .00        157 SELECT COUNT(*)
g375mcpc30dy5      2      1690109023 Y   Y   N            1             10        .03        .01        .00        767 SELECT row_orde
                   3      1690109023 Y   Y   Y            5             24        .02        .00       2.00        362
 
15 rows selected.
 
SQL> --

Sure enough, there are a few (10 statements to be exact with a total of 15 child cursors) that are marked as Bind Aware. However, there are only 3 statements that have multiple child cursors (sql_id: 17uuqnvxmzxhj, 4vb86f36xqc50, g375mcpc30dy5). And for each of those statements, the child cursors all have the same plan (sql_id: 17uuqnvxmzxhj, for example, has 3 children all using plan_hash_value: 3038781757). So even though they are marked Bind Aware, and have multiple child cursors, they are not producing distinct plans for those statements. So even the ones that the optimizer has noticed, do not appear to be providing us any benefit.

But back to the original question. We have many statements that are suffering from bind variable peeking issues that are apparently not being noticed. Why is that? Well I got to thinking about why ACS might be ignoring the statements that I know have this issue. One of the characteristics of these statements is that they have a relatively large number of bind variables. Some of them have as many as a couple of hundred. So I let my mind wander off into programmer land. How would the guys writing the optimizer code deal with a situation where they had a virtually unlimited number of bind variables. My first thought was to just put a hard limit on the number of variables to handle. Histograms have a relatively small number of potential buckets, and since ACS uses a histogram approach, it stands to reason the programmers might have put in a relatively small limit for their first pass. So I went off to test this idea (since this post is already so long I’ll cut right to the chase). There does appear to be a hard limit of 14 bind variables and statements that have more than that are apparently not evaluated for bind sensitivity. Here’s a test case:

> !sql
sqlplus "/ as sysdba"
 
SQL*Plus: Release 11.1.0.7.0 - Production on Mon May 11 11:16:06 2009
 
Copyright (c) 1982, 2008, Oracle.  All rights reserved.
 
 
Connected to:
Oracle Database 11g Enterprise Edition Release 11.1.0.7.0 - Production
With the Partitioning, OLAP, Data Mining and Real Application Testing options
 
SQL> !cat t14.sql
set echo off
variable v1 number
variable v2 varchar2(30)
variable v3 varchar2(30)
variable v4 varchar2(30)
variable v5 varchar2(30)
variable v6 varchar2(30)
variable v7 varchar2(30)
variable v8 varchar2(30)
variable v9 varchar2(30)
variable v9 varchar2(30)
variable v10 varchar2(30)
variable v11 varchar2(30)
variable v12 varchar2(30)
variable v13 varchar2(30)
variable v14 varchar2(30)
variable v15 varchar2(30)
variable v16 varchar2(30)
variable v17 varchar2(30)
variable v18 varchar2(30)
variable v19 varchar2(30)
exec :v1 := 999999;
exec :v2 := 'TESTING'
exec :v3 := '01-jan-08'
exec :v4 := '01-jan-09'
exec :v5 := 'Y'
exec :v6 := 'X'
exec :v7 := 'y'
exec :v8 := 'Z'
exec :v9 := 'a'
exec :v10 := 'b'
exec :v10 := 'c'
exec :v11 := 'd'
exec :v12 := 'e'
exec :v13 := 'f'
exec :v14 := 'g'
exec :v15 := 'h'
exec :v16 := 'i'
exec :v17 := 'j'
exec :v18 := 'k'
exec :v19 := 'l'
set echo on
select avg(pk_col) from kso.little_skew
where col1 = :v1
and col2 = :v2
and col3 between :v3 and :v4
and col4 in (:v5,:v6,:v7,:v8,:v9,:v10,:v11,:v12,:v13,:v14)
/
 
SQL> @flush_pool
SQL> @t14
SQL> @t14
SQL> @t14
SQL> @t14
SQL> 
SQL> -- 4 execs of the first bind variable set, now let's use a different set of bind variables
SQL> -- t14a.sql is the same except v1=1 - which (due to histogram) wants to use a different plan
SQL>
SQL> @t14a
SQL> @t14a
SQL> @t14a
SQL> @t14a
SQL> @t14a
SQL> @t14a
SQL> @t14a
SQL>
SQL> -- 7 execs with the new set of bind variables, should give it plenty of info to make it bind aware
SQL> -- now a few more with the original set of bind variables
SQL>
SQL> @t14
SQL> @t14
SQL> @t14
SQL> @t14
SQL>
SQL> -- now let's see what we've got
SQL>
SQL> @find_sql_acs 
Enter value for sql_text: %v14)%
Enter value for sql_id: 
Enter value for is_bind_aware: 
 
SQL_ID         CHILD PLAN_HASH_VALUE IBS IBA ISH      EXECS ROWS_PROCESSED  AVG_ETIME    AVG_CPU    AVG_PIO    AVG_LIO SQL_TEXT
------------- ------ --------------- --- --- --- ---------- -------------- ---------- ---------- ---------- ---------- -----------------------------------
2yk8hbkc4kbd5      0       376960484 N   N   N            8              8        .18        .18        .00      2,641 select avg(pk_col) from kso.little_
                                                                                                                       skew where col1 = :v1 and col2 = :v
                                                                                                                       2 and col3 between :v3 and :v4 and
                                                                                                                       col4 in (:v5,:v6,:v7,:v8,:v9,:v10,:
                                                                                                                       v11,:v12,:v13,:v14)
 
2yk8hbkc4kbd5      1      3746388338 N   Y   Y            3              3        .00        .00        .00         15 select avg(pk_col) from kso.little_
                                                                                                                       skew where col1 = :v1 and col2 = :v
                                                                                                                       2 and col3 between :v3 and :v4 and
                                                                                                                       col4 in (:v5,:v6,:v7,:v8,:v9,:v10,:
                                                                                                                       v11,:v12,:v13,:v14)
 
2yk8hbkc4kbd5      2       376960484 N   Y   Y            4              4        .00        .00        .00          3 select avg(pk_col) from kso.little_
                                                                                                                       skew where col1 = :v1 and col2 = :v
                                                                                                                       2 and col3 between :v3 and :v4 and
                                                                                                                       col4 in (:v5,:v6,:v7,:v8,:v9,:v10,:
                                                                                                                       v11,:v12,:v13,:v14)
 
 
3 rows selected.
 
SQL> -- As expected, the optimizer has noticed and marked it Bind Aware
SQL> -- Now let's try the same thing with 15 bind variables instead of 14
SQL> -- (note: t15 is the same with one more bind variable)
SQL>
SQL> @t15
SQL> @t15
SQL> @t15
SQL> @t15
SQL> @t15a
SQL> @t15a
SQL> @t15a
SQL> @t15a
SQL> @t15a
SQL> @t15a
SQL> @t15a
SQL> @t15
SQL> @t15
SQL> @t15
SQL> @t15
SQL> @find_sql_acs
Enter value for sql_text: %v15)%
Enter value for sql_id: 
Enter value for is_bind_aware: 
 
SQL_ID         CHILD PLAN_HASH_VALUE IOB IBA ISH      EXECS ROWS_PROCESSED  AVG_ETIME    AVG_CPU    AVG_PIO    AVG_LIO SQL_TEXT
------------- ------ --------------- --- --- --- ---------- -------------- ---------- ---------- ---------- ---------- -----------------------------------
4ndg8w1ga5dth      0       376960484 N   N   Y           15             15        .17        .16        .00      2,465 select avg(pk_col) from kso.little_
                                                                                                                       skew where col1 = :v1 and col2 = :v
                                                                                                                       2 and col3 between :v3 and :v4 and
                                                                                                                       col4 in (:v5,:v6,:v7,:v8,:v9,:v10,:
                                                                                                                       v11,:v12,:v13,:v14,:v15)
 
 
1 row selected.
 
SQL> -- no joy!
SQL>
SQL> -- so now I wondered if it really was just a hard limit or something more complicated
SQL> -- so I wrote a little script to count the number of bind variables in Bind Aware statements
SQL>
SQL> !cat acs_bind_count.sql
select distinct sql_id, bind_count from (
select sql_id, child_number, count(*) bind_count from v$sql_bind_capture
where sql_id in (
select sql_id from v$sqlarea where is_bind_aware = 'Y')
group by sql_id, child_number
)
order by bind_count
/
 
SQL> @acs_bind_count.sql
 
SQL_ID        BIND_COUNT
------------- ----------
2jmg3n6k2q82x          2
dxjvgtd3stafn          4
ck67mwdmdnaww          8
9pcw6qh83mj69          9
883uvnn2gz36u         10
4ysyd47nkap6d         11
7mygfqgs52au2         12
2744r65xx9h2h         13
2yk8hbkc4kbd5         14
 
9 rows selected.

So it looks like there probably is a hard limit. Let’s see if I can disprove that by looking at a couple of production systems. Here’s the output from the same script on four production instances (note: system 1 is that same one that I referenced earlier with the statements with known Bind Variable Peeking issues, where ACS was not noticing them):

-- System 1, Node 2
 
SQL> @acs_bind_count
 
SQL_ID        BIND_COUNT
------------- ----------
17uuqnvxmzxhj          8
58p0j1q6rmv34          8
5mxqphz5qfs4d          8
g375mcpc30dy5          8
3tfx8fzp64vkb          9
4vb86f36xqc50          9
34x6683rpwtxa         10
dt1v1cmua9cnq         11
ftxa99d89yzz0         11
0qvgb3dyfg539         12
 
10 rows selected.
 
 
-- System 1, Node 3
 
SQL> @acs_bind_count
 
SQL_ID        BIND_COUNT
------------- ----------
5bjg6w9btv3zn          7
17uuqnvxmzxhj          8
6n1790gk5m0hy          8
2pv7g3nutnyq5          9
4vb86f36xqc50          9
11at9nnhrw3w9         10
4p9zp29bcu927         10
4axts2hm73n98         11
ftxa99d89yzz0         11
490gh9uugyqqq         13
 
10 rows selected.
 
-- System 2, Node 1
 
SQL> @acs_bind_count
 
SQL_ID        BIND_COUNT
------------- ----------
4rqy85b9r413x          1
7h47mb48s19t3          1
51z6b0kbduf8m          2
djkchp3qwadu1          2
9g5ng8xjj4h05          3
amyvvzzjccvsg          3
cuv2pyzvz7b4z          3
d68jnfnqs6uh7          3
dkc2kbj7kdsu7          3
fxmfhkkhcrdj6          3
6196v5td8pk4n          4
9m63xcj6sbswu          4
0mn3xx02ww6pd          5
c7k3pwbjg4d1d          5
dy98ajwqc8s2x          5
3qh6yw37n8m1a          6
3xxgg248shg62          6
83v17f53rnzcv          6
a2271k4f7j211          6
06n7rk2jw3rsy          7
f4xr9x5wh46zt          7
48ryzfg5dxpqn          8
an9114vtxukz2          8
 
23 rows selected.
 
-- System 2, Node 2
 
SQL> @acs_bind_count
 
SQL_ID        BIND_COUNT
------------- ----------
4rqy85b9r413x          1
7h47mb48s19t3          1
gvj749s4654hm          1
51z6b0kbduf8m          2
6qwznvjfajh7t          2
djkchp3qwadu1          2
2mhfdtyrvhz3c          3
92a7wu0891bjk          3
9g5ng8xjj4h05          3
9p9gsakw5qyrg          3
amyvvzzjccvsg          3
bs63sfxynwtc6          3
cuv2pyzvz7b4z          3
d68jnfnqs6uh7          3
dvh3d8g2f844j          3
0341h5ytqbv7k          4
...
gj0rzh6xw2msp          4
grvh9mmkynm4u          4
0mn3xx02ww6pd          5
7ys2u732cj1ag          5
9kfj6kj32p7ku          5
dy98ajwqc8s2x          5
83v17f53rnzcv          6
d79xsp0utuvm2          6
gqkx5bsg1zfzc          6
4q3n2wwqtghma          7
f4xr9x5wh46zt          7
g7c90sr77bb78          7
7gb24h57r0spb          8
9zcy2yz537z41          8
an9114vtxukz2          8
7uwy0uxauuabz          9
80xmux45pvkrr          9
 
73 rows selected.

So it appears that there probably is a hard limit and that it probably is 14 (although there certainly could be a more complicated algorithm in play). None of the 4 production systems I checked had a single statement that was marked bind aware with more than 14 bind variables.

So here are a few closing thoughts:

To me, ACS doesn’t seem to be completely cooked yet. In fact, it seems to be somewhat of a futile attempt, since in the very best case, one execution with a bad plan would be necessary for the optimizer to recognize that a bind variable peeking issue existed. This wouldn’t be so bad if the information was persisted, so that the same “learning” process wouldn’t have to be endured if/when a statement gets flushed from the shared pool. This issue alone is enough to keep this feature from being relied upon in situations where performance is critical. In my opinion, the best approach remains unchanged from version 10, that being the judicious use of literals where necessary to prevent plan instability due to bind variable peeking.

My impression of it is not completely negative though. It’s certainly better than the old approach of pick a plan and stick with it. And for systems that use a limited number of binds per statement where performance swings are not as dramatic and/or performance is not as critical, it seems to work pretty well.

Here are some other references:

OptimizerMagic Blog – Good basic description of ACS
OptimizerMagic Blog – Update on ACS
Ric Van Dyke – Intelligent Cusor Sharing in 11.1.0.6
Ric Van Dyke – Intelligent Cusor Sharing in 11.1.0.7
Section on ACS in Troubleshooting Oracle Performance By Christian Antognini

18 Comments

  1. Ric Van Dyke says:

    Kerry,
    This is some great stuff. I never did push the number of BINDs to see if there was a limit that way. Very interesting to see that, certainly not something I expected. Yes I fully agree that this isn’t quite done in the oven. Needs more time to get the kinks worked out, but like you I see this as a step in the right direction. The site I’m at is about to launch a production system under 11 soon, I hope to observe ACS in that system to see how it fairs here.

    - Ric

  2. osborne says:

    Thanks Ric.

    I’ll be interested to see how it works out for you.

    Kerry

  3. Timur Akhmadeev says:

    Hello, Kerry.

    Thanks for good example of real experience with ACS – very informative and to the point.
    Have you contacted Oracle Support about your wishes to permanently mark a statement as bind-aware? for ex., something similar to colored sql – it would be great improvement to current features of ACS and, I think, not so difficult to implement.

  4. osborne says:

    Timur,

    I have not contacted support to request an enhancement. I have seen a couple of references to the fact that they are already working on a hint to mark a statement as bind aware. It doesn’t seem like a great approach though as a hint would require changes to the code. I agree with you that something like the colored sql approach would be better. And as part of that process, it would need to save the plan details and supporting bind variable histogram data so that it didn’t have to re-discover which bind variables should go with which plans.

    Kerry

  5. Brian Wong says:

    Hello, Kerry:

    Very good info here. Have you tried it on 11gRel2? I wonder if it fixes this limitation/bug?

    Brian

  6. osborne says:

    Brian,

    Yes I have tested it in 11gR2. It appears to have the same 14 bind variable limit. I don’t think it’s a bug by the way. I think it’s just undocumented behavior.

    Kerry

  7. brebu says:

    Hi Kerry
    On 11.2.0.1.0

    SQL_ID BIND_COUNT
    ————- ———-
    749hy25rap500 5
    230zr866q6m7f 18
    affcc0gzgr7ar 18

    I thought that is not the number of bind variables which determine the numbere of shared cursors. Looks like bind variables are treated like histograms and bind variables are used in “buckets”….

  8. osborne says:

    I’m not sure I am following you. For sure the cursors are combined when distinct values of bind variable result in the same plan so yes it’s like histograms on bind variable values. And yes, the number of bind variables is not directly related to the number of child cursors.

    Kerry

  9. hank says:

    Hi Kerry

    i found something from ORACLE docs and it says :

    The management of private SQL areas is the responsibility of the user process. The allocation and deallocation of private SQL areas depends largely on which application tool you are using, although the number of private SQL areas that a user process can allocate is always limited by the initialization parameter OPEN_CURSORS. The default value of this parameter is 50.

    isn’t it what you are figuring out?

  10. osborne says:

    I was trying to show why ACS doesn’t always solve our Bind Variable Peeking issues. One of the main issues was that statements that have over 14 bind variables don’t appear to ever be marked as bind sensitive. (i.e. ACS never evaluates them at all) This was done on 11.1.0.7 so the behavior may change with subsequent releases. There is really no relation between this and the number of child cursors that get created for a statement – whether it is marked as bind aware or not.

    Kerry

  11. Mark says:

    Hi Kerry,
    In my 9i system I turned off the bind peeking. That was actually a recommendation from Oracle support which made sense to me. My app had a combination of SQLs with literals and bind variables. The idea was, those with literals would benefit from histograms, those with bind variables would be protected from plan instability.
    I didn’t see you mentioning this approach at all. What’s your opinion on disabling bind peeking in 11g instead of relying on ACS?

  12. osborne says:

    Well I don’t think ACS really solves the problem, so yes disabling peeking via setting _optim_peek_user_binds=false is still a viable option in my opinion.

    Kerry

  13. Jeff says:

    Excellent article. We’re running Exadata 11gR2 (11.2.0.1.0) and I’ve encountered the same issue with some SQL that has 21 bind vars. I had a hunch that we had a BP issue, but your work here saved me a lot of time in proving it out. I’ve created an SR and I’m curious what they come back with. Thanks for your contributions to the Exadata community!

  14. osborne says:

    Thanks for the kind words Jeff. Pleas let me know what response you get to the SR. I expected this would be addressed in fairly short order but to be honest I have not tested with 11.2.0.2 yet, but I did test 11.2.0.1 and it did appear that the same limitation was in place in that release.

    Kerry

  15. Jeff says:

    The interesting thing is our Java app makes heavy use of binds and not one SQL is bind aware according to V$SQL (out of 15k SQLs!) . Good news is ODM guys were able to reproduce this but haven’t been able to explain it so far. Sometimes thats half the battle!

  16. Jeff says:

    Update: Oracle believes it is due to the driver the app is using (ver 1 INet Seropto: http://www.inetsoftware.de/products/jdbc-driver/oracle/seropto). They believe the driver is not ‘passing the bind variables correctly for the compile parse’ – their words.

    I’ve patched up the problem using SQL Profiles, but I have to wait till July/Aug so App team can update to latest Oracle JDBC drivers.

    It seems odd that the CBO would care how the parms are passed.

  17. Aychin says:

    Hi, very interesting article! Thank You for spending Your time to share it! Please review my thoughts about ACS on http://aychin.wordpress.com/2011/04/04/adaptive-cursor-sharing-and-spm/ it will be very interesting to me to hear Your opinion about this issue. Thank You again!

  18. Amiel Davis says:

    Update:
    a. The 11.2 “Oracle® Database Performance Tuning Guide” state it clearly:

    “…Adaptive cursor sharing is enabled for the database by default and cannot be disabled. Note that adaptive cursor sharing does not apply to SQL statements containing more than 14 bind variables…”

    http://download.oracle.com/docs/cd/E11882_01/server.112/e16638/optimops.htm#sthref874

    looked in older documentation, and didn’t find it..

    b. Great blog, keep up the good work!

    Amiel Davis

Leave a Reply