Archive for the ‘Tuning’ Category.

12c Adaptive Optimization

Since everyone seems to be all twitterpated about Oracle Database 12c this week, I thought I’d post a quick note to let you know that the slides from the presentation on 12c Adaptive Optimization I did at the Hotsos Symposium 2013 (with a lot of help from Maria) are now available in the Whitepapers / Presentations section of this blog.

While I’m on the topic, I found this little blurb in the Oracle Database 12c Release 1 New Features Guide:

Zero Effort Performance

That’s the section that talks about the Adaptive Optimization stuff. I think the documentation folks meant that they were describing performance features that didn’t require any manual intervention, but it sort of reads like the features are really easy to describe, or maybe that the writers weren’t going to work very hard on describing them. At any rate, the wording struck me as humorous. 🙂

SQL Gone Bad – But Plan Not Changed? – Part 2

In Part 1 of this series I talked about the basic problem, which is that plan_hash_values are not based on the whole plan. One of the main missing components is the predicates associated with a plan, but there are other missing parts as was pointed out in Part 1 of Randolf Geist’s post on the topic. At any rate, predicates seem to be the most critical of the missing parts.

The purpose of this second post on the topic is to talk about diagnosis. Basically how do you identify when some other part of a plan has changed that doesn’t affect the plan_hash_value, specifically a predicate.

So first I thought I would show a few examples of statements with the same sql_id and plan_hash_value that have other plan differences (in the predicate section). To do this I used a method proposed by Randolf Geist a few years back in his 2nd post on the topic which covered Alternative Ways to Calculate a PLAN_HASH_VALUE In that post, Randolf shows several ways to compute a hash value on any or all of the columns in the v$sql_plan table. I wrote a simple script around one of the those methods (find_pred_mismatch.sql), and as you might guess from the name, I limited this version to not include all the columns in v$sql_plan, but to only identify statements with mismatched predicates. To be more explicit, the script will locate statements in the shared_pool that have multiple child cursors, where there are more than one set of predicates to go with a single plan_hash_value. Here’s an example:

SYS@DEMO1> @find_pred_mismatch

Type created.


SQL_ID        PLAN_HASH_VALUE CHILD_NUMBER   THE_HASH ARE_H
------------- --------------- ------------ ---------- -----
063m5s0cvrr19      1502175119            0 2709091620 DIFF!
093fgfvygm51m      3114044936            0 3689661040 DIFF!
0cn2wm9d7zq8d      1540383338            0 3746559344 DIFF!
0pt4jfmq9f1q0      3078496799            0 1309675335 DIFF!
155cwuv2pfp1d       768389713            0 2982291916 DIFF!
18c2yb5aj919t      1032442798            0 1714458756 DIFF!
1n9crga6mbw2x      4174841998            0 2752042257 DIFF!
1ytxrt5qp9qdd      2707146560            0 3757837347 DIFF!
23buxzfxyp1vy      3143617369            0 2089881285 DIFF!
23nad9x295gkf       891847141            0 4056778555 DIFF!
24zvjzuyrxh3w      1877711096            0 1680905434 DIFF!
28n17ru48jnh5      1665111388            0 3584687734 DIFF!
2j0fw19fph49j      1337823903            0 2431841938 DIFF!
2kd6nusgzc3uw      3151266570            0 3024843785 DIFF!
2rpwgryn7pxz5      3329544515            0  452505826 DIFF!
35nhk48nxwc0v      2553960494            0  117262982 DIFF!
3bc73t2h9mwxc      1420457580            0 1226225583 DIFF!
3gputsqv4u1j3      3161304745            0 2252819340 DIFF!
3zauy2zqryrsx      1420457580            0 1128973296 DIFF!
42q1qby3huf2c      3069437562            0 4008632079 DIFF!
47mm81hm9sggy      1836210496            0 1554180227 DIFF!
4g46czps3t55u      2714703948            0 4063401817 DIFF!
4n2gca427719q      1360319091            0 4013571180 DIFF!
4tpsnbkt1dm5j      2960949352            0 3341004783 DIFF!
5dyhfnkzta2zm      3767331201            0 4238766232 DIFF!
5h91zx386wbht       293199272            0  949799344 DIFF!
5s34t44u10q4g      2693539438            0  839739072 DIFF!
5uw1u291s3m0k       219265157            0  642280427 DIFF!
61tn3mam0vq0b      2012170170            0 2048362545 DIFF!
63t3ufgq37m0c      1155609947            0  844291465 DIFF!
69k5bhm12sz98      3091659676            0  356777601 DIFF!
6cp74g22fzahf        76968983            0 1617454724 DIFF!
6wm3n4d7bnddg      1772758172            0 1148123313 DIFF!
78kp0fcyxavzb      2960949352            0 1085639264 DIFF!
7ah4afrggrw5c      4213028598            0 4285032606 DIFF!
7g4rxwbvhdh3q      3170022080            0 2083442940 DIFF!
7hspvruktu52b      4016032974            0 2538340188 DIFF!
84p3g5b5bsfvn       681044650            0 3826083810 DIFF!
86521pa77y28j      3760090177            0 3887843475 DIFF!
8ak9gkw2mjhvr      1526940012            0 2946674232 DIFF!
8p9z2ztb272bm       408663731            0 3293625021 DIFF!
aca4xvmz0rzup       427901911            0 4215668999 DIFF!
akh9zqqkx3wj7      2306922995            0 2084689096 DIFF!
akx4284f2vjnv      3948068913            0 2662025793 DIFF!
amycufzt6uq5f      3283312188            0 1896511712 DIFF!
atnkqhrp3t7xa      2196914545            0   26873046 DIFF!
aw2x7hh2a9ag0      1148557212            0  719001678 DIFF!
b41wak2bb7atw       108532975            0 1699960507 DIFF!
bhvyz9bgyrhb2      1134671139            0 2402404248 DIFF!
c8gnrhxma4tas      4024720576            0 2473084105 DIFF!
cc7vvmrsxzyq1      1849127868            0 1912933403 DIFF!
cjtaqp92v10bn       922118807            0 2313573387 DIFF!
ckfgcyv05xptf      2869192503            0 3932622422 DIFF!
cw860p03hy5ff      1502175119            0 2915988156 DIFF!
cyw0c6qyrvsdd       192117504            0 2551186960 DIFF!
d53nc7j6n1057      1356236608            0  582788179 DIFF!
dyj1ssw8jw54f      1836210496            0   66902761 DIFF!
fkjkrv5ycz96u      2247257083            0 1809299677 DIFF!
gdn3ysuyssf82      4024720576            0 2473084105 DIFF!
gwbdd5m45ugpm      3180770434            0  235716193 DIFF!

60 rows selected.

SYS@DEMO1> select * from table(dbms_xplan.display_cursor('&sql_id','&child_no','typical'));
Enter value for sql_id: 24zvjzuyrxh3w
Enter value for child_no: 

PLAN_TABLE_OUTPUT
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
SQL_ID  24zvjzuyrxh3w, child number 0
-------------------------------------
SELECT script FROM sys.metaxsl$ WHERE xmltag=:1 AND transform=:2  AND
model=:3

Plan hash value: 1877711096

--------------------------------------------------------------------------------------
| Id  | Operation                 | Name     | Rows  | Bytes | Cost (%CPU)| Time     |
--------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT          |          |       |       |     3 (100)|          |
|*  1 |  TABLE ACCESS STORAGE FULL| METAXSL$ |     3 |    99 |     3   (0)| 00:00:01 |
--------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - storage(("XMLTAG"=:1 AND "TRANSFORM"=:2 AND "MODEL"=:3))
       filter(("XMLTAG"=:1 AND "TRANSFORM"=:2 AND "MODEL"=:3))

SQL_ID  24zvjzuyrxh3w, child number 1
-------------------------------------
SELECT script FROM sys.metaxsl$ WHERE xmltag=:1 AND transform=:2  AND
model=:3

Plan hash value: 1877711096

----------------------------------------------
| Id  | Operation                 | Name     |
----------------------------------------------
|   0 | SELECT STATEMENT          |          |
|*  1 |  TABLE ACCESS STORAGE FULL| METAXSL$ |
----------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - storage(("MODEL"=:3 AND "TRANSFORM"=:2 AND "XMLTAG"=:1))
       filter(("MODEL"=:3 AND "TRANSFORM"=:2 AND "XMLTAG"=:1))

Note
-----
   - rule based optimizer used (consider using cbo)


44 rows selected.

Continue reading ‘SQL Gone Bad – But Plan Not Changed? – Part 2’ »

Tuning paramon.sql

I know no one really likes the term “tuning” these days, but it’s a short catchy word that gets the idea across. So I’ll just stick with it for the title of this post.

Note that this is one of those posts that’s not really supposed to be about how to solve a particular problem. It’s really just a story about a distraction that I ran into and I how I thought about getting around the issue and then ultimately resolving the root cause. Maybe you will find it instructive to see the process.

So I have this script that I use occasionally (paramon.sql) to see what parallel query slaves are doing. Unfortunately the script doesn’t have a header in it, but I’m pretty sure I lifted it from Randolf Geist. I can’t find it on his blog anywhere, but it looks like his style of writing SQL, and PX Query is something he’s written a lot about, so I’m pretty sure that’s where I got it. (Update: see Jonathan Lewis’s comment below attributing the script to Andy Brooker) Anyway, the script has worked great for me in the past but I recently noticed that it was really sluggish on a couple of 11gR2 DB’s running on Exadata. Here’s an example:

-bash-3.2$ !sql
sqlp

SQL*Plus: Release 11.2.0.3.0 Production on Mon Jan 14 12:23:15 2013

Copyright (c) 1982, 2011, Oracle.  All rights reserved.


Connected to:
Oracle Database 11g Enterprise Edition Release 11.2.0.3.0 - 64bit Production
With the Partitioning, Real Application Clusters, Automatic Storage Management, OLAP,
Data Mining and Real Application Testing options


INSTANCE_NAME    STARTUP_TIME               CURRENT_TIME                  DAYS    SECONDS
---------------- -------------------------- -------------------------- ------- ----------
dbm1             09-JAN-2013 03:25          14-JAN-2013 12:23             5.37     464246

SYS@dbm1> set SQLPROMPT "11.2.0.3> "
11.2.0.3>
11.2.0.3> @paramon
Enter value for status: 

 Node Name Status       Pid   Sid Parent OSUSER                         Schema     CHILD_WAIT                     PARENT_WAIT
----- ---- ---------- ----- ----- ------ ------------------------------ ---------- ------------------------------ ------------------------------
      P000 AVAILABLE     35
      P001 AVAILABLE     36
      P002 AVAILABLE     37
      P003 AVAILABLE     38
      P004 AVAILABLE     39
      P005 AVAILABLE     40
      P006 AVAILABLE     41
      P007 AVAILABLE     42
      P008 AVAILABLE     43
      P009 AVAILABLE     44
      P010 AVAILABLE     45
      P011 AVAILABLE     46
      P012 AVAILABLE     47
      P013 AVAILABLE     48
      P014 AVAILABLE     49
      P015 AVAILABLE     50
      P016 AVAILABLE     51
      P017 AVAILABLE     52
      P018 AVAILABLE     53
      P019 AVAILABLE     54
      P020 AVAILABLE     55
      P021 AVAILABLE     56
      P022 AVAILABLE     57
      P023 AVAILABLE     58
      P024 AVAILABLE     59
      P025 AVAILABLE     60
      P026 AVAILABLE     61
      P027 AVAILABLE     62
      P028 AVAILABLE     63
      P029 AVAILABLE     64
      P030 AVAILABLE     65
      P031 AVAILABLE     66


32 rows selected.

Elapsed: 00:00:23.11

So on this 11g DB it took 23 seconds to run the query. On one of my 10g DB’s though the performance was stellar.

Continue reading ‘Tuning paramon.sql’ »

Tuning Oracle to Make a Query Slower

I had an interesting little project this morning. Of course it takes longer to write it down than to do actually do it, but it was kind of interesting and since I haven’t done a post in quite some time (and it’s the day before Thanksgiving, so it’s pretty quite at the office anyway) I decided to share. One of the Enkitec guys (Tim Fox) was doing a performance comparison between various platforms (Exadata using it’s IB Storage Network, Oracle Database Appliance (ODA) using it’s direct attached storage, and a standard database on a Dell box using EMC fiber channel attached storage). The general test idea was simple – see how the platforms stacked up for a query that required a full scan of a large table. More specifically, what Tim wanted to see was the relative speed at which the various storage platforms could return data. The expectation was that the direct attached storage would be fastest and the fibre channel storage would be slowest (especially since we only had a single 2G HBA). He tested ODA and Exadata and got basically what he expected, but when he went to test the database on the Dell he was surprised that it was actually faster than either of the other two tests. So here’s some output from the initial tests: First the Exadata. It’s an X2 quarter rack with one extra storage server. Note that we had to set cell_offload_processing to false to turn off the Exadata storage optimizations, thus giving us a measurement of the hardware capabilities without the Exadata offloading.

> !sqlp
sqlp
 
SQL*Plus: Release 11.2.0.2.0 Production on Wed Nov 23 11:08:28 2011
 
Copyright (c) 1982, 2010, Oracle.  All rights reserved.
 
 
Connected to:
Oracle Database 11g Enterprise Edition Release 11.2.0.2.0 - 64bit Production
With the Partitioning, Real Application Clusters, Automatic Storage Management, OLAP,
Data Mining and Real Application Testing options
 
SYS@DEMO1> @uptime
 
INSTANCE_NAME    STARTUP_TIME      CURRENT_TIME         DAYS    SECONDS
---------------- ----------------- ----------------- ------- ----------
DEMO1            07-NOV-2011 12:37 23-NOV-2011 11:08   15.94    1377058
 
SYS@DEMO1> set sqlprompt "_USER'@'EXADATA'>' "
SYS@EXADATA> 
SYS@EXADATA> ! cat /etc/redhat-release
Enterprise Linux Enterprise Linux Server release 5.5 (Carthage)
 
SYS@EXADATA> ! uname -a
Linux enkdb03.enkitec.com 2.6.18-194.3.1.0.3.el5 #1 SMP Tue Aug 31 22:41:13 EDT 2010 x86_64 x86_64 x86_64 GNU/Linux
 
SYS@EXADATA> alter session set "_serial_direct_read"=always;
 
Session altered.
 
SYS@EXADATA> alter session set cell_offload_processing=false;
 
Session altered.
 
SYS@EXADATA> set autotrace on
SYS@EXADATA> set timing on
SYS@EXADATA> select count(*) from instructor.class_sales;
 
  COUNT(*)
----------
  90000000
 
Elapsed: 00:00:43.01
 
Execution Plan
----------------------------------------------------------
Plan hash value: 3145879882
 
----------------------------------------------------------------------------------
| Id  | Operation                  | Name        | Rows  | Cost (%CPU)| Time     |
----------------------------------------------------------------------------------
|   0 | SELECT STATEMENT           |             |     1 |   314K  (1)| 00:00:02 |
|   1 |  SORT AGGREGATE            |             |     1 |            |          |
|   2 |   TABLE ACCESS STORAGE FULL| CLASS_SALES |    90M|   314K  (1)| 00:00:02 |
----------------------------------------------------------------------------------
 
 
Statistics
----------------------------------------------------------
          1  recursive calls
          0  db block gets
    1168567  consistent gets
    1168557  physical reads
          0  redo size
        526  bytes sent via SQL*Net to client
        524  bytes received via SQL*Net from client
          2  SQL*Net roundtrips to/from client
          0  sorts (memory)
          0  sorts (disk)
          1  rows processed
 
SYS@EXADATA> set autotrace off
SYS@EXADATA> @fss
Enter value for sql_text: select count(*) from instructor.class_sales
Enter value for sql_id: 
 
SQL_ID         CHILD      EXECS   AVG_ROWS     AVG_ETIME       AVG_CPU       AVG_PIO      AVG_LIO SQL_TEXT
------------- ------ ---------- ---------- ------------- ------------- ------------- ------------ ----------------------------------------
b2br1x82p9862      0          1          1         43.00          3.16  1,168,557.00    1,168,567 select count(*) from instructor.class_sa
 
Elapsed: 00:00:00.08

So the test on the Exadata took 43 seconds to read and transport roughly 1 million 8K blocks. The same test on the ODA looked like this: Continue reading ‘Tuning Oracle to Make a Query Slower’ »

New create_1_hint_sql_profile.sql

I modified my create_1_hint_sql_profile.sql script (which I blogged about here: Single Hint Profiles) to allow any arbitrary text sting including quote characters. This is a script that I use fairly often to apply a hint to a single SQL statement that is executing in a production system where we can’t touch the code for some reason. For example, it’s sometimes useful to add a MONITOR hint or a GATHER_PLAN_STATISTICS hint to a statement that’s behaving badly so we can get more information about what the optimizer is thinking. I recently updated the script to allow special characters in the hint syntax. This feature is useful when you want to add something like an OPT_PARAM hint that takes quoted arguments. The change makes use of the q-Quote feature which I blogged about here: q-Quote. (the original version just barfed on quotes being input as part of the hint)

Here’s an example of how to use it:

SYS@SANDBOX1> alter session set cell_offload_processing=false;

Session altered.

Elapsed: 00:00:00.00
SYS@SANDBOX1> select avg(pk_col) from kso.skew3 where col1 < 0;

AVG(PK_COL)
-----------
  1849142.5

1 row selected.

Elapsed: 00:00:28.08
SYS@SANDBOX1> @fsx
Enter value for sql_text: select avg(pk_col) from kso.skew3 where col1 < 0
Enter value for sql_id: 

SQL_ID         CHILD  PLAN_HASH  EXECS  AVG_ETIME AVG_PX OFFLOAD IO_SAVED_% SQL_TEXT
------------- ------ ---------- ------ ---------- ------ ------- ---------- ----------------------------------------------------------------------
a6j7wgqf84jvg      0 2684249835      1      28.07      0 No             .00 select avg(pk_col) from kso.skew3 where col1 < 0

1 row selected.

Elapsed: 00:00:00.02
SYS@SANDBOX1> @create_1_hint_sql_profile.sql
Enter value for sql_id: a6j7wgqf84jvg
Enter value for profile_name (PROFILE_sqlid_MANUAL): 
Enter value for category (DEFAULT): 
Enter value for force_matching (false): 
Enter value for hint_text: opt_param('cell_offload_processing' 'true')

Profile PROFILE_a6j7wgqf84jvg_MANUAL created.

Elapsed: 00:00:00.07
SYS@SANDBOX1> @sql_profile_hints
Enter value for profile_name: PROFILE_a6j7wgqf84jvg_MANUAL

HINT
------------------------------------------------------------------------------------------------------------------------------------------------------
opt_param('cell_offload_processing' 'true')

1 rows selected.

Elapsed: 00:00:00.04
SYS@SANDBOX1> select avg(pk_col) from kso.skew3 where col1 < 0;

AVG(PK_COL)
-----------
  1849142.5

1 row selected.

Elapsed: 00:00:05.11
SYS@SANDBOX1> @fsx
Enter value for sql_text: select avg(pk_col) from kso.skew3 where col1 < 0
Enter value for sql_id: 

SQL_ID         CHILD  PLAN_HASH  EXECS  AVG_ETIME AVG_PX OFFLOAD IO_SAVED_% SQL_TEXT
------------- ------ ---------- ------ ---------- ------ ------- ---------- ----------------------------------------------------------------------
a6j7wgqf84jvg      0 2684249835      1      28.07      0 No             .00 select avg(pk_col) from kso.skew3 where col1 < 0
a6j7wgqf84jvg      1 2684249835      1       5.10      0 Yes          99.99 select avg(pk_col) from kso.skew3 where col1 < 0

In the example I turned off cell offload processing with the ALTER SESSION and ran a SQL statement that took 28 seconds. Then I used my fsx.sql script to verify that the statement was not offloaded and to find the SQL_ID. Next I created a 1 hint Profile with an OPT_PARAM hint that set the cell_offload_processing parameter back to TRUE using the new version of my create_1_hint_sql_profile.sql script. Next I used my sql_profile_hints.sql script to verify the text of the hint that was added to the Profile. It looked good including the quotes. When I executed the statement a second time it ran in 5 seconds. I then used fsx.sql again to see that the statement was offloaded for the second execution (child 1).

Cardinality Feedback

I ran into an interesting issue last week having to do with plan stability. The problem description went something like this:

“I have a statement that runs relatively quickly the first time I run it (around 12 seconds). Subsequent executions always run much slower, usually around 20 or 30 minutes. If I flush the shared pool and run it again elapsed time is back to 12 seconds or so.”

The query looked a little like this:

Continue reading ‘Cardinality Feedback’ »

Embarcadero Performance Panel

Karen Morton, Cary MIllsap and I will be participating in a on-line panel discussion about Oracle Performance on July 28th. Since we all worked together in the past we thought it would be a fun to listen to each other answer questions. Embarcadero is sponsoring this event and invited us to participate. Here’s a graphic from the mailer they sent out.

I only point it out because Cary and Karen look like they are posing for a picture, while I, as usual, look like someone just poured a drink down my pants. That’s normal though. I’ve been told I have a great face for radio.

You can sign up here: Register Now!

How to Lock SQL Profiles Generated by SQL Tuning Advisor

I’ve mentioned (many times) that I think SQL Profiles that are generated by the SQL Tuning Advisor (STA) tend to sour over time.

After seeing it happen at a few sites I began to wonder why. So first a few facts about the SQL Profiles that STA generates:

  1. They are simply a set hints that get applied to statements behind the scenes during parsing
  2. They consist mainly of OPT_ESTIMATE hints which modify optimizer calculations
  3. They also may contain direct statistics modification hints (COLUMN_STATS, TABLE_STATS)
  4. They usually contain a OPTIMIZER_FEATURES_ENABLED hint
  5. They very occasionally contain other environment type hints (FIRST_ROWS, etc…)
  6. They do not contain directive hints (FULL, INDEX, NESTED_LOOP, etc..)
  7. The names of STA profiles start with SYS_SQLPROF
  8. STA’s goal is to do a more through job of analyzing a SQL statement to get a better plan

I wrote a little query (sql_profile_distinct_hint.sql) to pull a list of hints from a 10g database along with the number of their occurrences and ran it on several production systems where STA Profiles had been created. Here’s the output from a  system that had 14 STA Profiles.

SQL> @sql_profile_distinct_hints
Enter value for profile_name: SYS_SQLPROF%
 
HINT                                                 COUNT(*)
-------------------------------------------------- ----------
COLUMN_STATS                                               13
FIRST_ROWS                                                  1
IGNORE_OPTIM_EMBEDDED_HINTS                                 1
INDEX_STATS                                                 1
OPTIMIZER_FEATURES_ENABLE                                  14
OPT_ESTIMATE                                              178
TABLE_STATS                                                 2

Notice that the vast majority of hints are of the OPT_ESTIMATE variety. Now let’s have a look at the actual hints contained in a STA Profile.


SYS@LAB112> @sql_profile_hints
Enter value for profile_name: SYS_SQLPROF_0126f1743c7d0005

HINT
------------------------------------------------------------------------------------------------
IGNORE_OPTIM_EMBEDDED_HINTS
OPTIMIZER_FEATURES_ENABLE(default) 
OPT_ESTIMATE(@"SEL$86A1760A", TABLE, "A"@"SEL$6", SCALE_ROWS=2207.090256)
OPT_ESTIMATE(@"SEL$86A1760A", TABLE, "A"@"SEL$5", SCALE_ROWS=2261.586312)
COLUMN_STATS("KSO"."SKEW", "PK_COL", scale, length=5)
COLUMN_STATS("KSO"."SKEW", "COL1", scale, length=4 distinct=828841 nulls=12.8723033 min=1 max=1000000)
TABLE_STATS("KSO"."SKEW", scale, blocks=162294 rows=35183107.66)

7 rows selected.

So on this particular STA Profile, the OPT_ESTIMATE hint has been used to tell the optimizer to change the estimate of rows for table A in query block SEL$6 by multiplying it by 2207 (roughly). In addition, there are hints which are basically hard coding table stats and column stats. So as you can see, these hints, while they may be accurate when the Profile is created, are unlikely to remain accurate over the long haul. In fairness, the OPT_ESTIMATE hint does make sense in situations where the optimizer will never get a calculation correct because of a short coming in it’s abilities (correlated columns is a good example of this type of situation). And in those conditions, implementing a STA generated Profile is a valid long term approach. But in my experience this is the exception rather than the rule.

So what are STA Profiles good for? Well two things:

First, they are very good at showing us where the optimizer is having a problem. If you look at the hints that are generated, it is easy to identify the OPT_ESTIMATE hints where the scaling factors are off the chart (hint: anything with an exponent is a place where the optimizer is struggling). This is easy to do with my sql_profile_hints.sql script by the way. Here’s a set of OPT_ESTIMATE hints. Can you spot the place where the optimizer is really having a problem?

OPT_ESTIMATE(@"SEL$5DA710D3", INDEX_FILTER, "F"@"SEL$1", IDX$$_1AA260002, SCALE_ROWS=8.883203639e-06) 
OPT_ESTIMATE(@"SEL$5DA710D3", INDEX_SKIP_SCAN, "F"@"SEL$1", IDX$$_1AA260002, SCALE_ROWS=8.883203639e-06) 
OPT_ESTIMATE(@"SEL$5DA710D3", JOIN, ("B"@"SEL$1", "A"@"SEL$1"), SCALE_ROWS=4.446153275) 
OPT_ESTIMATE(@"SEL$5DA710D3", JOIN, ("C"@"SEL$1", "A"@"SEL$1"), SCALE_ROWS=7.884506683) 
OPT_ESTIMATE(@"SEL$5DA710D3", JOIN, ("E"@"SEL$1", "A"@"SEL$1"), SCALE_ROWS=25.60960842) 
OPT_ESTIMATE(@"SEL$5DA710D3", JOIN, ("F"@"SEL$1", "B"@"SEL$1"), SCALE_ROWS=26.34181566) 
OPT_ESTIMATE(@"SEL$5DA710D3", JOIN, ("F"@"SEL$1", "B"@"SEL$1", "A"@"SEL$1"), SCALE_ROWS=839.9683673) 
OPT_ESTIMATE(@"SEL$5DA710D3", TABLE, "D"@"SEL$1", SCALE_ROWS=5.083144561)
OPT_ESTIMATE(@"SEL$5", INDEX_SCAN, "C"@"SEL$5", ORDER_FG_ITEM_IX3, SCALE_ROWS=0.2507281101) 

It’s the first two lines and whatever alias F refers to is our problem area. The OPT_ESTIMATE hint tells the optimizer to decrease it’s estimate by a factor of 8.883203639e-06. So the optimizer has vastly overestimated the rows that will be returned by the index.

Second, STA Profiles are sometimes capable of producing better plans. This is primarily due to the fact that STA can take as long as you give it to analyze a statement, making sure that all the optimizer’s calculations are correct. It does this by running various pieces of the statement and checking that the number of rows the optimizer has estimated are actually correct. Obviously this can take a while on complex statements, much longer than the optimizer is allowed when parsing a statement. But as I’ve already shown, the SQL Profiles that get created to enable those better plans have a pretty good chance of going sour on us over time.

Which leads me to the point of this post. We can have our cake and eat it too! We can create the SQL Profile as recommended by STA and then “lock” the plan into place by converting the OPT_ESTIMATE hints to directive type hints. I put the word “lock” in quotes because there is really no such thing as “locking” a plan. It’s just that using directive hints as opposed to OPT_ESTIMATE hints, significantly lowers the probability of the plan changing in the future. So how do we make this conversion. Well I have a script for that called lock_STA_profile.sql. Here’s an example showing how it works.


SYS@LAB112> @sql_profiles
Enter value for sql_text: 
Enter value for name: 

NAME                           CATEGORY        STATUS   SQL_TEXT                                                               FORCE
------------------------------ --------------- -------- ---------------------------------------------------------------------- -----
PROFILE_fgn6qzrvrjgnz          DEFAULT         DISABLED select /*+ index(a SKEW_COL1) */ avg(pk_col) from kso.skew a           NO
PROFILE_8hjn3vxrykmpf          DEFAULT         DISABLED select /*+ invalid_hint (doda) */ avg(pk_col) from kso.skew where col1 NO
PROFILE_69k5bhm12sz98          DEFAULT         DISABLED SELECT dbin.instance_number,        dbin.db_name, dbin.instance_name,  NO
PROFILE_8js5bhfc668rp          DEFAULT         DISABLED select /*+ index(a SKEW_COL2_COL1) */ avg(pk_col) from kso.skew a wher NO
PROFILE_bxd77v75nynd8          DEFAULT         DISABLED select /*+ parallel (a 4) */ avg(pk_col) from kso.skew a where col1 >  NO
PROFILE_7ng34ruy5awxq          DEFAULT         DISABLED select i.obj#,i.ts#,i.file#,i.block#,i.intcols,i.type#,i.flags,i.prope NO
PROF_6kymwy3guu5uq_1388734953  DEFAULT         ENABLED  select 1                                                               YES
PROFILE_cnpx9s9na938m_MANUAL   DEFAULT         ENABLED  select /*+ opt_param('statistics_level','all') */ * from kso.skew wher NO
PROF_79m8gs9wz3ndj_3723858078  DEFAULT         ENABLED  /* SQL Analyze(252,1) */ select avg(pk_col) from kso.skew              NO
PROFILE_9ywuaagwscbj7_GPS      DEFAULT         ENABLED  select avg(pk_col) from kso.skew                                       NO
PROF_arcvrg5na75sw_3723858078  DEFAULT         ENABLED  select /*+ index(skew@sel$1 skew_col1) */ avg(pk_col) from kso.skew wh NO
SYS_SQLPROF_01274114fc2b0006   DEFAULT         ENABLED  select i.table_owner, i.table_name, i.index_name, FUNCIDX_STATUS, colu NO
SYS_SQLPROF_0127d10ffaa60000   DEFAULT         ENABLED  select table_owner||'.'||table_name tname , index_name, index_type, st NO
SYS_SQLPROF_01281e513ace0000   DEFAULT         ENABLED  SELECT TASK_LIST.TASK_ID FROM (SELECT /*+ NO_MERGE(T) ORDERED */ T.TAS NO
coe_abwg9nwg8prsj_3723858078   DEFAULT         ENABLED                                                                         NO
PROF_84q0zxfzn5u6s_2650913906  TEST            ENABLED  select avg(pk_col) from kso.skew                                       NO
PROF_0pvj94afp6faw_FULL        DEFAULT         ENABLED  select /* test 1 hint */ avg(pk_col) from kso.skew a where col1 = 2222 NO
PROF_875qbqc2gw2qz_4201340344  DEFAULT         ENABLED  select /* NOT IN */ department_name                                    NO
PROF_09gdkwq1bs48h_167097056   DEFAULT         ENABLED  select /*+ index (skew skew_col3_col2_col1) */ count(*) from kso.skew  NO
PROFILE_4cp821ufcwvgc_moved    DEFAULT         ENABLED  select count(*) from kso.skew where col3 = '01-jan-10'                 NO
PROF_8wvgj0n4kh6dx_2650913906  DEFAULT         ENABLED  select avg(pk_col) from kso.skew a where col1 = 333333                 NO
PROFILE_g737q1pfmbvjj_moved    DEFAULT         ENABLED  select /*+ full (skew) */ avg(pk_col) from kso.skew where col1 = 13613 NO
PROFILE_cvdnr0b8dcxzz_MANUAL   DEFAULT         ENABLED  select /* aasdas */ avg(pk_col) from kso.skew where col1 = 136133      NO
PROF_719syuvrm29tq_931251584   DEFAULT         ENABLED  SELECT IOBJID, IDOBJID, INAME, IOWNER, IOWNERID, ISPACE, ITSNO, IFILEN NO
PROF_g4gp07gt2z920_105323984   DEFAULT         ENABLED  update sys.scheduler$_job set  last_start_date = :1, running_instance  NO

25 rows selected.

SYS@LAB112> @sql_profile_hints
Enter value for profile_name: SYS_SQLPROF_01281e513ace0000

HINT
------------------------------------------------------------------------------------------------
IGNORE_OPTIM_EMBEDDED_HINTS
OPTIMIZER_FEATURES_ENABLE(default)
FIRST_ROWS(1)
OPT_ESTIMATE(@"SEL$86A1760A", TABLE, "A"@"SEL$6", SCALE_ROWS=2207.090256)
OPT_ESTIMATE(@"SEL$86A1760A", TABLE, "A"@"SEL$5", SCALE_ROWS=2261.586312)

5 rows selected.

SYS@LAB112> @find_sql
Enter value for sql_text: SELECT TASK_LIST.TASK_ID FROM (SELECT /*+ NO_MERGE(T) ORD%
Enter value for sql_id: 

SQL_ID         CHILD  PLAN_HASH EXECS AVG_ETIME  AVG_LIO SQL_TEXT
------------- ------ ---------- ----- --------- -------- --------------------------------------------------
bqfx5q2jas08u      0 2496534803    86       .00       12 SELECT TASK_LIST.TASK_ID FROM (SELECT /*+ NO_MERGE
                                                         (T) ORDERED */ T.TASK_ID FROM (SELECT * FROM DBA_A
                                                         DVISOR_TASKS ORDER BY TASK_ID DESC) T, DBA_ADVISOR
                                                         _PARAMETERS_PROJ P1, DBA_ADVISOR_PARAMETERS_PROJ P
                                                         2 WHERE T.ADVISOR_NAME='ADDM' AND T.STATUS = 'COMP
                                                         LETED' AND T.EXECUTION_START >= (SYSDATE - 1) AND
                                                         T.HOW_CREATED = 'AUTO' AND T.TASK_ID = P1.TASK_ID
                                                         AND P1.PARAMETER_NAME = 'INSTANCE' AND P1.PARAMETE
                                                         R_VALUE = SYS_CONTEXT('USERENV','INSTANCE') AND T.
                                                         TASK_ID = P2.TASK_ID AND P2.PARAMETER_NAME = 'DB_I
                                                         D' AND P2.PARAMETER_VALUE = TO_CHAR(:B1 ) ORDER BY
                                                          T.TASK_ID DESC) TASK_LIST WHERE ROWNUM = 1


1 row selected.

SYS@LAB112> @dplan
Enter value for sql_id: bqfx5q2jas08u
Enter value for child_no: 

PLAN_TABLE_OUTPUT
------------------------------------------------------------------------------------------------------------------------------------------------------
SQL_ID  bqfx5q2jas08u, child number 0
-------------------------------------
SELECT TASK_LIST.TASK_ID FROM (SELECT /*+ NO_MERGE(T) ORDERED */
T.TASK_ID FROM (SELECT * FROM DBA_ADVISOR_TASKS ORDER BY TASK_ID DESC)
T, DBA_ADVISOR_PARAMETERS_PROJ P1, DBA_ADVISOR_PARAMETERS_PROJ P2 WHERE
T.ADVISOR_NAME='ADDM' AND T.STATUS = 'COMPLETED' AND T.EXECUTION_START
>= (SYSDATE - 1) AND T.HOW_CREATED = 'AUTO' AND T.TASK_ID = P1.TASK_ID
AND P1.PARAMETER_NAME = 'INSTANCE' AND P1.PARAMETER_VALUE =
SYS_CONTEXT('USERENV','INSTANCE') AND T.TASK_ID = P2.TASK_ID AND
P2.PARAMETER_NAME = 'DB_ID' AND P2.PARAMETER_VALUE = TO_CHAR(:B1 )
ORDER BY T.TASK_ID DESC) TASK_LIST WHERE ROWNUM = 1

Plan hash value: 2496534803

-------------------------------------------------------------------------------------------------------------
| Id  | Operation                          | Name                   | Rows  | Bytes | Cost (%CPU)| Time     |
-------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                   |                        |       |       |     9 (100)|          |
|*  1 |  COUNT STOPKEY                     |                        |       |       |            |          |
|   2 |   VIEW                             |                        |     2 |    26 |     9   (0)| 00:00:01 |
|   3 |    NESTED LOOPS                    |                        |       |       |            |          |
|   4 |     NESTED LOOPS                   |                        |     2 |   240 |     9   (0)| 00:00:01 |
|*  5 |      FILTER                        |                        |       |       |            |          |
|   6 |       NESTED LOOPS OUTER           |                        |     2 |   188 |     7   (0)| 00:00:01 |
|   7 |        NESTED LOOPS                |                        |     2 |   126 |     5   (0)| 00:00:01 |
|*  8 |         TABLE ACCESS BY INDEX ROWID| WRI$_ADV_TASKS         |     2 |    74 |     3   (0)| 00:00:01 |
|   9 |          INDEX FULL SCAN DESCENDING| WRI$_ADV_TASKS_PK      |   822 |       |     2   (0)| 00:00:01 |
|* 10 |         TABLE ACCESS BY INDEX ROWID| WRI$_ADV_PARAMETERS    |     1 |    26 |     1   (0)| 00:00:01 |
|* 11 |          INDEX UNIQUE SCAN         | WRI$_ADV_PARAMETERS_PK |     1 |       |     0   (0)|          |
|* 12 |        TABLE ACCESS BY INDEX ROWID | WRI$_ADV_EXECUTIONS    |     1 |    31 |     1   (0)| 00:00:01 |
|* 13 |         INDEX UNIQUE SCAN          | WRI$_ADV_EXECS_PK      |     1 |       |     0   (0)|          |
|* 14 |      INDEX UNIQUE SCAN             | WRI$_ADV_PARAMETERS_PK |     1 |       |     0   (0)|          |
|* 15 |     TABLE ACCESS BY INDEX ROWID    | WRI$_ADV_PARAMETERS    |     1 |    26 |     1   (0)| 00:00:01 |
-------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - filter(ROWNUM=1)
   5 - filter((DECODE(NVL("E"."STATUS","A"."STATUS"),1,'INITIAL',2,'EXECUTING',3,'COMPLETED',4,'INTER
              RUPTED',5,'CANCELLED',6,'FATAL ERROR')='COMPLETED' AND
              NVL("E"."EXEC_START","A"."EXEC_START")>=SYSDATE@!-1))
   8 - filter(("A"."ADVISOR_NAME"='ADDM' AND "A"."HOW_CREATED"='AUTO' AND
              BITAND("A"."PROPERTY",6)=4))
  10 - filter("A"."VALUE"=TO_CHAR(:B1))
  11 - access("A"."ID"="A"."TASK_ID" AND "A"."NAME"='DB_ID')
  12 - filter("A"."ADVISOR_ID"="E"."ADVISOR_ID")
  13 - access("A"."ID"="E"."TASK_ID" AND "A"."LAST_EXEC_NAME"="E"."NAME")
  14 - access("A"."ID"="A"."TASK_ID" AND "A"."NAME"='INSTANCE')
  15 - filter("A"."VALUE"=SYS_CONTEXT('USERENV','INSTANCE'))

Note
-----
   - automatic DOP: Computed Degree of Parallelism is 1 because of parallel threshold
   - SQL profile SYS_SQLPROF_01281e513ace0000 used for this statement


57 rows selected.

SYS@LAB112> @lock_STA_profile
Enter value for sql_id: bqfx5q2jas08u
Enter value for child_no (0): 0
Enter value for new_profile_name (PROF_sqlid_planhash): 
Enter value for force_matching (FALSE): 

PL/SQL procedure successfully completed.

SYS@LAB112> @sql_profiles
Enter value for sql_text: 
Enter value for name: %bqfx5q2jas08u%

NAME                           CATEGORY        STATUS   SQL_TEXT                                                               FORCE
------------------------------ --------------- -------- ---------------------------------------------------------------------- -----
PROF_bqfx5q2jas08u_2496534803  DEFAULT         ENABLED  SELECT TASK_LIST.TASK_ID FROM (SELECT /*+ NO_MERGE(T) ORDERED */ T.TAS NO

SYS@LAB112> @sql_profile_hints
Enter value for profile_name: PROF_bqfx5q2jas08u_2496534803

HINT
------------------------------------------------------------------------------------------------
IGNORE_OPTIM_EMBEDDED_HINTS
OPTIMIZER_FEATURES_ENABLE('11.2.0.1')
DB_VERSION('11.2.0.1')
FIRST_ROWS(1)
NO_PARALLEL
OUTLINE_LEAF(@"SEL$86A1760A")
MERGE(@"SEL$5")
MERGE(@"SEL$532C0C35")
MERGE(@"SEL$6")
OUTLINE_LEAF(@"SEL$1")
OUTLINE(@"SEL$2")
OUTLINE(@"SEL$5")
OUTLINE(@"SEL$532C0C35")
MERGE(@"SEL$4")
OUTLINE(@"SEL$6")
OUTLINE(@"SEL$58B2FD6B")
ELIMINATE_OBY(@"SEL$3")
OUTLINE(@"SEL$4")
OUTLINE(@"SEL$3")
NO_ACCESS(@"SEL$1" "TASK_LIST"@"SEL$1")
INDEX_DESC(@"SEL$86A1760A" "A"@"SEL$4" ("WRI$_ADV_TASKS"."ID"))
INDEX_RS_ASC(@"SEL$86A1760A" "A"@"SEL$6" ("WRI$_ADV_PARAMETERS"."TASK_ID" "WRI$_ADV_PARAMETERS"."NAME"))
INDEX_RS_ASC(@"SEL$86A1760A" "E"@"SEL$4" ("WRI$_ADV_EXECUTIONS"."TASK_ID" "WRI$_ADV_EXECUTIONS"."NAME"))
INDEX(@"SEL$86A1760A" "A"@"SEL$5" ("WRI$_ADV_PARAMETERS"."TASK_ID" "WRI$_ADV_PARAMETERS"."NAME"))
LEADING(@"SEL$86A1760A" "A"@"SEL$4" "A"@"SEL$6" "E"@"SEL$4" "A"@"SEL$5")
USE_NL(@"SEL$86A1760A" "A"@"SEL$6")
USE_NL(@"SEL$86A1760A" "E"@"SEL$4")
USE_NL(@"SEL$86A1760A" "A"@"SEL$5")
NLJ_BATCHING(@"SEL$86A1760A" "A"@"SEL$5")

29 rows selected.

SYS@LAB112> @sql_profiles
Enter value for sql_text: 
Enter value for name: SYS%

NAME                           CATEGORY        STATUS   SQL_TEXT                                                               FORCE
------------------------------ --------------- -------- ---------------------------------------------------------------------- -----
SYS_SQLPROF_01274114fc2b0006   DEFAULT         ENABLED  select i.table_owner, i.table_name, i.index_name, FUNCIDX_STATUS, colu NO
SYS_SQLPROF_0127d10ffaa60000   DEFAULT         ENABLED  select table_owner||'.'||table_name tname , index_name, index_type, st NO
SYS_SQLPROF_01281e513ace0000   SAVED           ENABLED  SELECT TASK_LIST.TASK_ID FROM (SELECT /*+ NO_MERGE(T) ORDERED */ T.TAS NO

3 rows selected.

SYS@LAB112> @sql_profile_hints
Enter value for profile_name: SYS_SQLPROF_01281e513ace0000

HINT
------------------------------------------------------------------------------------------------
IGNORE_OPTIM_EMBEDDED_HINTS
OPTIMIZER_FEATURES_ENABLE(default)
FIRST_ROWS(1)
OPT_ESTIMATE(@"SEL$86A1760A", TABLE, "A"@"SEL$6", SCALE_ROWS=2207.090256)
OPT_ESTIMATE(@"SEL$86A1760A", TABLE, "A"@"SEL$5", SCALE_ROWS=2261.586312)

5 rows selected.

SYS@LAB112> 

So in this example I listed all the SQL Profiles in existence on the system (using sql_profiles.sql). Then I showed the hints associated with STA Profile, SYS_SQLPROF_01281e513ace0000 with sql_profile_hints.sql. Then I located the sql statement in v$sql using the find_sql.sql script. Then I used dbms_xplan (via the dplan.sql script) to show the plan for the statement (proving that it was using the STA Profile). Then I used the lock_STA_profile.sql script to create a directive hint based Profile in place of the OPT_ESTIMATE hint based Profile. Then I showed the hints for the new SQL Profile. Note that the original STA Profile is not dropped, but rather moved to the SAVED category, so you can still look at its hints as I have done at the end of this example.

So that’s it. This is a complex topic and I have blogged about it before on numerous occasions. You may want to look back at this post, Oracle Support Sanctions Manually Created SQL Profiles, to get a better feel for where the hints came from that are used to replace the OPT_ESTIMATE hints. By the way, Jonathan Lewis and Tom Kyte have also written about this feature. (I trust you can find them via Google)

Also, I have written a chapter on Plan Stability in the upcoming Apress book, Pro Oracle SQL. The chapter is 65 or so pages long and it covers SQL Profiles in depth, so if you are hungry for more info on this topic, I highly recommend it. 😉

You can pre-order the book here: Pro Oracle SQL (if you are so inclined)

It should be released in a few weeks.

Hotsos Symposium 2010 Presentations

I got an email a few days ago asking if I would provide the scripts from my Hotsos Symposium 2010 presentations. I didn’t even realize the presentations had been posted anywhere but I managed to find them on my company’s website. So anyway, I decided to go ahead and post a link to the PDF’s and the scripts here as well. So click on the pretty pictures to get the PDFs and the cleverly titled text links to get the accompanying zip files with the scripts.

Controlling Execution Plans Zip File

My Favorite Scripts 2010 Zip File


Oh and Bob Sneed as “Disco Duck” (Thanks Marco)

Oracle Support Sanctions Manually Created SQL Profiles!

I originally titled this post: “SQLT – coe_xfr_sql_profile.sql”

Catchy title huh? – (that’s why I changed it)

I’ve been promoting the use of SQL Profiles as a plan control mechanism for some time. The basic idea is to use the undocumented procedure dbms_sqltune.import_sql_profile to build a set of hints to be applied behind the scenes via a SQL Profile. The hints can be created anyway can think of, but one of my favorite ways to generate them is to pull the hints from the other_xml field of v$sql_plan. This is a technique suggested to me originally by Randolf Geist. I have used this approach several times in the past but occasionally I’ve had a few doubts as to whether this is a good idea or even if SQL Profiles can apply all valid hints (see Jonathan Lewis’s comments on this post, Why Oracle Isn’t Using My Profile, where he expresses some doubts as well – he’s also written a bit about SQL Profiles on his site as you might imagine).

So anyway, I just found out this week that there is a script published on Oracle’s Support site that does exactly the same thing. It’s part of the SQLT zip file published in note 215187.1. By the way, SQLT has quite a bit of interesting information in it and the source (PL/SQL) is not wrapped, so it’s worth having a look at. There’s not much in the way of information about it out there, although I did see a reference to it in a comment on one of Jonathan’s recent posts. Maybe I’ll get around to doing another post on that topic some other time. Anyway, the name of the SQL Profile building script is coe_xfr_sql_profile.sql. It basically pulls the hints from the other_xml field of v$sql_plan and turns them into a SQL Profile. So I’m feeling better about myself now that I know that this approach is at least in some way sanctioned by Oracle support.

Here’s an example:


SYS@LAB112> @fs
Enter value for sql_text: %skew%
Enter value for sql_id: 

SQL_ID         CHILD  PLAN_HASH      EXECS     AVG_ETIME      AVG_LIO SQL_TEXT
------------- ------ ---------- ---------- ------------- ------------ ------------------------------------------------------------
688rj6tv1bav0      0  568322376          1          6.78      163,077 select avg(pk_col) from kso.skew where col1 = 1
abwg9nwg8prsj      0 3723858078          1           .01           39 select avg(pk_col) from kso.skew where col1 = 136135

2 rows selected.

SYS@LAB112> @sql_hints
Enter value for sql_id: abwg9nwg8prsj
Enter value for child_no: 0

OUTLINE_HINTS
-----------------------------------------------------------------------------------------------------------------------------------------------------------
IGNORE_OPTIM_EMBEDDED_HINTS
OPTIMIZER_FEATURES_ENABLE('11.2.0.1')
DB_VERSION('11.2.0.1')
ALL_ROWS
OUTLINE_LEAF(@"SEL$1")
INDEX_RS_ASC(@"SEL$1" "SKEW"@"SEL$1" ("SKEW"."COL1"))

6 rows selected.

SYS@LAB112> @coe_xfr_sql_profile    

Parameter 1:
SQL_ID (required)

Enter value for 1: abwg9nwg8prsj          


PLAN_HASH_VALUE AVG_ET_SECS
--------------- -----------
     3723858078        .006

Parameter 2:
PLAN_HASH_VALUE (required)

Enter value for 2: 3723858078

Values passed:
~~~~~~~~~~~~~
SQL_ID         : "abwg9nwg8prsj"
PLAN_HASH_VALUE: "3723858078"


Execute coe_xfr_sql_profile_abwg9nwg8prsj_3723858078.sql
on TARGET system in order to create a custom SQL Profile
with plan 3723858078 linked to adjusted sql_text.


COE_XFR_SQL_PROFILE completed.
SQL>@coe_xfr_sql_profile_abwg9nwg8prsj_3723858078.sql
SQL>REM
SQL>REM $Header: 215187.1 coe_xfr_sql_profile_abwg9nwg8prsj_3723858078.sql 11.4.1.4 2010/07/23 csierra $
SQL>REM
SQL>REM Copyright (c) 2000-2010, Oracle Corporation. All rights reserved.
SQL>REM
SQL>REM AUTHOR
SQL>REM   carlos.sierra@oracle.com
SQL>REM
SQL>REM SCRIPT
SQL>REM   coe_xfr_sql_profile_abwg9nwg8prsj_3723858078.sql
SQL>REM
SQL>REM DESCRIPTION
SQL>REM   This script is generated by coe_xfr_sql_profile.sql
SQL>REM   It contains the SQL*Plus commands to create a custom
SQL>REM   SQL Profile for SQL_ID abwg9nwg8prsj based on plan hash
SQL>REM   value 3723858078.
SQL>REM   The custom SQL Profile to be created by this script
SQL>REM   will affect plans for SQL commands with signature
SQL>REM   matching the one for SQL Text below.
SQL>REM   Review SQL Text and adjust accordingly.
SQL>REM
SQL>REM PARAMETERS
SQL>REM   None.
SQL>REM
SQL>REM EXAMPLE
SQL>REM   SQL> START coe_xfr_sql_profile_abwg9nwg8prsj_3723858078.sql;
SQL>REM
SQL>REM NOTES
SQL>REM   1. Should be run as SYSTEM or SYSDBA.
SQL>REM   2. User must have CREATE ANY SQL PROFILE privilege.
SQL>REM   3. SOURCE and TARGET systems can be the same or similar.
SQL>REM   4. To drop this custom SQL Profile after it has been created:
SQL>REM  EXEC DBMS_SQLTUNE.DROP_SQL_PROFILE('coe_abwg9nwg8prsj_3723858078');
SQL>REM   5. Be aware that using DBMS_SQLTUNE requires a license
SQL>REM  for the Oracle Tuning Pack.
SQL>REM
SQL>WHENEVER SQLERROR EXIT SQL.SQLCODE;
SQL>REM
SQL>VAR signature NUMBER;
SQL>REM
SQL>DECLARE
  2  sql_txt CLOB;
  3  h       SYS.SQLPROF_ATTR;
  4  BEGIN
  5  sql_txt := q'[
  6  select avg(pk_col) from kso.skew where col1 = 136135
  7  ]';
  8  h := SYS.SQLPROF_ATTR(
  9  q'[BEGIN_OUTLINE_DATA]',
 10  q'[IGNORE_OPTIM_EMBEDDED_HINTS]',
 11  q'[OPTIMIZER_FEATURES_ENABLE('11.2.0.1')]',
 12  q'[DB_VERSION('11.2.0.1')]',
 13  q'[ALL_ROWS]',
 14  q'[OUTLINE_LEAF(@"SEL$1")]',
 15  q'[INDEX_RS_ASC(@"SEL$1" "SKEW"@"SEL$1" ("SKEW"."COL1"))]',
 16  q'[END_OUTLINE_DATA]');
 17  :signature := DBMS_SQLTUNE.SQLTEXT_TO_SIGNATURE(sql_txt);
 18  DBMS_SQLTUNE.IMPORT_SQL_PROFILE (
 19  sql_text    => sql_txt,
 20  profile     => h,
 21  name        => 'coe_abwg9nwg8prsj_3723858078',
 22  description => 'coe abwg9nwg8prsj 3723858078 '||:signature||'',
 23  category    => 'DEFAULT',
 24  validate    => TRUE,
 25  replace     => TRUE,
 26  force_match => FALSE /* TRUE:FORCE (match even when different literals in SQL). FALSE:EXACT (similar to CURSOR_SHARING) */ );
 27  END;
 28  /

PL/SQL procedure successfully completed.

SQL>WHENEVER SQLERROR CONTINUE
SQL>SET ECHO OFF;

            SIGNATURE
---------------------
 15022055147995020558


... manual custom SQL Profile has been created


COE_XFR_SQL_PROFILE_abwg9nwg8prsj_3723858078 completed

SYS@LAB112> @sql_profiles
Enter value for sql_text: 
Enter value for name: 

NAME                           CATEGORY        STATUS   SQL_TEXT                                                               FORCE
------------------------------ --------------- -------- ---------------------------------------------------------------------- -----
PROFILE_fgn6qzrvrjgnz          DEFAULT         DISABLED select /*+ index(a SKEW_COL1) */ avg(pk_col) from kso.skew a           NO
PROFILE_8hjn3vxrykmpf          DEFAULT         DISABLED select /*+ invalid_hint (doda) */ avg(pk_col) from kso.skew where col1 NO
PROFILE_69k5bhm12sz98          DEFAULT         DISABLED SELECT dbin.instance_number,        dbin.db_name, dbin.instance_name,  NO
PROFILE_8js5bhfc668rp          DEFAULT         DISABLED select /*+ index(a SKEW_COL2_COL1) */ avg(pk_col) from kso.skew a wher NO
PROFILE_bxd77v75nynd8          DEFAULT         DISABLED select /*+ parallel (a 4) */ avg(pk_col) from kso.skew a where col1 >  NO
PROFILE_7ng34ruy5awxq          DEFAULT         DISABLED select i.obj#,i.ts#,i.file#,i.block#,i.intcols,i.type#,i.flags,i.prope NO
SYS_SQLPROF_0126f1743c7d0005   SAVED           ENABLED  select avg(pk_col) from kso.skew                                       NO
PROF_6kymwy3guu5uq_1388734953  DEFAULT         ENABLED  select 1                                                               YES
PROFILE_cnpx9s9na938m_MANUAL   DEFAULT         ENABLED  select /*+ opt_param('statistics_level','all') */ * from kso.skew wher NO
PROF_79m8gs9wz3ndj_3723858078  DEFAULT         ENABLED  /* SQL Analyze(252,1) */ select avg(pk_col) from kso.skew              NO
PROFILE_9ywuaagwscbj7_GPS      DEFAULT         ENABLED  select avg(pk_col) from kso.skew                                       NO
PROF_arcvrg5na75sw_3723858078  DEFAULT         ENABLED  select /*+ index(skew@sel$1 skew_col1) */ avg(pk_col) from kso.skew wh NO
SYS_SQLPROF_01274114fc2b0006   DEFAULT         ENABLED  select i.table_owner, i.table_name, i.index_name, FUNCIDX_STATUS, colu NO
SYS_SQLPROF_0127d10ffaa60000   DEFAULT         ENABLED  select table_owner||'.'||table_name tname , index_name, index_type, st NO
SYS_SQLPROF_01281e513ace0000   DEFAULT         ENABLED  SELECT TASK_LIST.TASK_ID FROM (SELECT /*+ NO_MERGE(T) ORDERED */ T.TAS NO
PROFILE_5bgcrdwfhbc83_EXACT    DEFAULT         ENABLED  select avg(pk_col) from kso.skew where col1 = :"SYS_B_0"               YES
coe_abwg9nwg8prsj_3723858078   DEFAULT         ENABLED                                                                         NO

17 rows selected.

SYS@LAB112> -- that's interesting - looks like the sql_text has gotten wiped out
SYS@LAB112> -- let's see if it works anyway
SYS@LAB112> 
SYS@LAB112> select avg(pk_col) from kso.skew where col1 = 136135;

AVG(PK_COL)
-----------
   15636135

SYS@LAB112> @fs
Enter value for sql_text: select avg(pk_col) from kso.skew where col1 = 136135
Enter value for sql_id: 

SQL_ID         CHILD  PLAN_HASH      EXECS     AVG_ETIME      AVG_LIO SQL_TEXT
------------- ------ ---------- ---------- ------------- ------------ ------------------------------------------------------------
abwg9nwg8prsj      0 3723858078          1           .02           47 select avg(pk_col) from kso.skew where col1 = 136135

1 row selected.

SYS@LAB112> @dplan
Enter value for sql_id: abwg9nwg8prsj
Enter value for child_no: 

PLAN_TABLE_OUTPUT
------------------------------------------------------------------------------------------------------------------------------------------------------
SQL_ID  abwg9nwg8prsj, child number 0
-------------------------------------
select avg(pk_col) from kso.skew where col1 = 136135

Plan hash value: 3723858078

------------------------------------------------------------------------------------------
| Id  | Operation                    | Name      | Rows  | Bytes | Cost (%CPU)| Time     |
------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT             |           |       |       |    32 (100)|          |
|   1 |  SORT AGGREGATE              |           |     1 |    24 |            |          |
|   2 |   TABLE ACCESS BY INDEX ROWID| SKEW      |    32 |   768 |    32   (0)| 00:00:01 |
|*  3 |    INDEX RANGE SCAN          | SKEW_COL1 |    32 |       |     3   (0)| 00:00:01 |
------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   3 - access("COL1"=136135)

Note
-----
   - SQL profile coe_abwg9nwg8prsj_3723858078 used for this statement


24 rows selected.

So it is very similar to my create_sql_profile.sql script. The Oracle COE script does have the advantage of creating an output script that can be run to create the SQL Profile. That means you have a chance to edit the hints before creating the SQL Profile. It also means you can easily move a SQL Profile from one environment (TEST for example) to another (PROD for example).

But the best thing about it is that I no longer have to be concerned about using an undocumented procedure to do something that it may not have been intended to do in the first place!