Slides from OOW13 The optimizer must try to be all things to all people, and similarly, the collection of optimizer statistics must try to satisfy the needs of all. And many DBA's just leave it at that. But the optimizer offers so much more than that. With a little more effort and discipline, we can achieve much more than a "one-size-fits-all" policy, and maximize the benefit of all of the optimizer features. We'll look at the tools now available under DBMS_STATS to get more stability and better performance with optimizer statistics.

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WARNING
itty bitty fonts in this
presentation
SQL> exec sample_font
Can you read this ?
1
Connor McDonald
OracleDBA
co.uk
2
www.oracledba.co.uk
connormcdonald.wordpress.com
@connor_mc_d

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3

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bio slide
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gratuitous book plug
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8

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why ?
9

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11

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life was paradise
13
14

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(good) cost optimizer
15
16

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version 7.0
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optimizer_mode = CHOOSE

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"we choose RULE"
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20
SQL> analyze table SALES estimate statistics;

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21
eventually....
22

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it got better
23
added more functionality
24

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SQL> analyze table SALES estimate statistics
2 for table
3 for columns size 10
4 for ....;
SQL syntax engine
26

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oracle 8i
27
DBMS_STATS
28

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problem....
29
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analyze table SALES estimate statistics;SQL>
41 characters

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31
SQL>
2
3
4
5
6
7
8
128 characters
begin
dbms_stats.gather_table_stats(
ownname=>'HR',
tabname=>'SALES',
cascade=>true,
estimate_percent=>20
);
end;
don't get chaining
32

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s l o w e r
33
"I don't think so....."
34

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times have changed ...
35
36
SQL> desc DBMS_STATS
FUNCTION CLOB_TO_VARRAY
FUNCTION CONV_RAW
FUNCTION CREATE_EXTENDED_STATS
FUNCTION DIFF_TABLE_STATS_IN_HISTORY
FUNCTION DIFF_TABLE_STATS_IN_PENDING
FUNCTION DIFF_TABLE_STATS_IN_STATTAB
FUNCTION GET_COMPATIBLE
FUNCTION GET_PARAM
FUNCTION GET_PREFS
FUNCTION GET_STATS_HISTORY_AVAILABILITY
FUNCTION GET_STATS_HISTORY_RETENTION
FUNCTION GET_STAT_TAB_VERSION
FUNCTION REPORT_COL_USAGE
FUNCTION REPORT_GATHER_AUTO_STATS
FUNCTION REPORT_GATHER_DATABASE_STATS
FUNCTION REPORT_GATHER_DICTIONARY_STATS

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151 routines !
37
12c
38

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use DBMS_STATS
39
features
40
profiles
baselines
tuning sets
adaptive cursor sharing
bind peeking
column groups
extended statistics

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better stats
41
hard to convince
42

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stop using analyze
44

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ego
45
"good ol' days"
46

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47
48

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today....
49
optimizer is probably...
50

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... smarter than you
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52
SQL> select count(e.hiredate)
2 from DEPT d, EMP e
3 where e.deptno = d.deptno(+)
4 and e.sal > 10;
nested loop outer
sort merge outer
hash hash anti
nested loop anti

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-------------------------------------------
| Id | Operation | Name | Rows |
-------------------------------------------
| 0 | SELECT STATEMENT | | 1 |
| 1 | SORT AGGREGATE | | 1 |
|* 2 | TABLE ACCESS FULL| EMP | 14 |
-------------------------------------------
no DEPT ?
54
SQL> select count(e.hiredate)
2 from DEPT d, EMP e
3 where e.deptno = d.deptno(+)
4 and e.sal > 10;
not null
foreign key
key preserved

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Oracle's solution....
55
statistics by stealth...
56

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10g
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SQL> select owner, job_name, enabled
2 from dba_scheduler_jobs
3 where owner = 'SYS';
OWNER JOB_NAME ENABLED
--------------- ------------------------------ -------
SYS PURGE_LOG TRUE
SYS FGR$AUTOPURGE_JOB TRUE
SYS GATHER_STATS_JOB TRUE
SYS AUTO_SPACE_ADVISOR_JOB TRUE
FALSE

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11g
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SQL> select owner, job_name, enabled
2 from dba_scheduler_jobs
3 where owner = 'SYS';
OWNER JOB_NAME ENABLED
--------------- ------------------------------ -------
SYS AUTO_SPACE_ADVISOR_JOB FALSE
SYS BSLN_MAINTAIN_STATS_JOB TRUE
SYS DRA_REEVALUATE_OPEN_FAILURES TRUE
SYS FGR$AUTOPURGE_JOB FALSE
SYS GATHER_STATS_JOB FALSE
SYS HM_CREATE_OFFLINE_DICTIONARY FALSE
SYS ORA$AUTOTASK_CLEAN TRUE
SYS PURGE_LOG TRUE
SYS XMLDB_NFS_CLEANUP_JOB FALSE

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stats STILL being collected
61
automatic "tasks"
62
"super stealth mode"

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SQL> select client_name, status
2 from DBA_AUTOTASK_CLIENT;
CLIENT_NAME STATUS
------------------------------------ --------
auto optimizer stats collection ENABLED
auto space advisor ENABLED
sql tuning advisor ENABLED
most sites
64
stats every night
default options

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in this session...
65
default behaviour
66

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BAD
IDEA 67
collecting statistics
68

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BAD
IDEA 69
but....
70

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some default behaviour
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GOOD
IDEA 72

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collecting some statistics
73
GOOD
IDEA 74

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75
76
Inflammatory
statements
which will
alienate the
audience
Presentation Duration
1

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we're all hypocrites
77
statistical hypocrisy
78

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79
"I need to change some
reference data in my system"
wrong case

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SQL> update …
81
82
"nope...."

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ITIL
84
Information
Technology
Infrastructure
Library

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service
call
help
desk
problem
recordDONE !
86
easy....

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87
6 months later
corrected

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89
same site....
90
"Every night, I would like to
potentially change the
performance characteristics of
every single SQL statement in
the database"

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"no problem...."
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collecting stats = risk

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93
Ensor's paradox
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1987
performance group
bstat/estat
tkprof
BMC patrol

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95
"It is only safe to
gather statistics ..."
"...when to do so will
make no difference"
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recommendation #1

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unless things are bad...
do not change statistics

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99
"surely it can't hurt?"
100
10g

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options=>'GATHER STALE'
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options=>'GATHER EMPTY'

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options=>'GATHER AUTO'
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"no plans changed"

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105
"no queries ran slower"
still
106
created problems

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problem # 1
107
108
dbms_stats

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the goal of statistics
minimise expensive SQL....
110

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added more expensive SQL !
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SQL> alter session set sql_true = true;
Session altered.
SQL> begin
2 dbms_stats.gather_table_stats(
3 'DEMO',
4 'PEOPLE);
5 end;
6 /

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113
SQL> select
2 count(distinct GENDER),
3 min(GENDER),
4 max(GENDER),
5 count(distinct NAME),
6 min(NAME),
7 max(NAME)
...
...
21 from PEOPLE;
hard !
114

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problem #2
116

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lingering pain
invalidation
118

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library cache
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select *
from PEOPLE
insert into PEOPLE
select * from ...
select ...
from PEOPLE,
DEPT
where ...
delete from T
where X in
( select PID
from PEOPLE )
declare
v people.name%type;
begin
...
SQL> begin
2 dbms_stats.gather_table_stats(
3 'DEMO',
4 'PEOPLE);
5 end;
6 /
122

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oracle 9
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SQL> desc DBMS_STATS
PROCEDURE GATHER_TABLE_STATS
Argument Name Type In/Out Default?
----------------------- -------------- ------ --------
OWNNAME VARCHAR2 IN
TABNAME VARCHAR2 IN
PARTNAME VARCHAR2 IN DEFAULT
ESTIMATE_PERCENT NUMBER IN DEFAULT
BLOCK_SAMPLE BOOLEAN IN DEFAULT
METHOD_OPT VARCHAR2 IN DEFAULT
DEGREE NUMBER IN DEFAULT
GRANULARITY VARCHAR2 IN DEFAULT
CASCADE BOOLEAN IN DEFAULT
STATTAB VARCHAR2 IN DEFAULT
STATID VARCHAR2 IN DEFAULT
STATOWN VARCHAR2 IN DEFAULT
NO_INVALIDATE BOOLEAN IN DEFAULT
STATTYPE VARCHAR2 IN DEFAULT
FORCE BOOLEAN IN DEFAULT
NO_INVALIDATE BOOLEAN IN DEFAULT

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no_invalidate => false | true
?
?
126
oracle 10

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no_invalidate => auto
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SQL> select
2 x.ksppinm name,
3 y.kspftctxvl value
4 from
5 sys.x$ksppi x,
6 sys.x$ksppcv2 y
7 where
8 x.indx+1 = y.kspftctxpn and
9 x.ksppinm = '_optimizer_invalidation_period'
NAME VALUE
------------------------------ ------------
_optimizer_invalidation_period 18000

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SQL> exec dbms_stats.gather_table_stats(
user,'PEOPLE');
select *
from PEOPLE
insert into PEOPLE
select * from ...
select ...
from PEOPLE,
DEPT
where ...
delete from T
where X in
( select PID
from PEOPLE )
declare
v people.name%type;
begin
...
130
better ?

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131
hard parse storm avoided
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5 hours before problems

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recap
133
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"surely it can't hurt?"

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gathering statistics
135
really hard core SQL
belted CPU with hard parsing
everything ran the same
136

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137
unless things are bad...
do not change statistics
138
Inflammatory
statements
which will
alienate the
audience
Presentation Duration
1
2

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139
we don't know if things are bad
140
until its too late

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“why are SQL's so slow”
users phone
“the stats out of date”

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143

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2 hours to gather stats

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147
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collect stats

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in readiness
150

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you can !
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pending statistics

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"pending" - private
"published" – optimizer uses
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SQL> begin
2 dbms_stats.set_schema_prefs(
3 ownname=>'DEMO',
4 pname=>'PUBLISH',
5 pvalue=>'FALSE');
6 end;
database,
table

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155
SQL> alter session set
2 optimizer_use_pending_statistics = true;
156
SQL> begin
2 dbms_stats.publish_pending_stats(
3 ownname=>'DEMO',
4 tabname=>null);
5 end;

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157
recommendation #2
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when collecting statistics

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159
PUBLISH = false
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even if you immediately publish

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atomic publication
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and don't wait 5 hours

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_optimizer_invalidation_period
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then for most tables

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165
dbms_stats.lock_table_stats
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collecting system stats

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167
different story
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absolutely vital…
…to have them

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169
some history
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maximize I/O throughput

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171
SQL> set autotrace traceonly explain
SQL> select * from T;
---------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)|
---------------------------------------------------------------
| 0 | SELECT STATEMENT | | 53459 | 4489K| 113 (1)|
| 1 | TABLE ACCESS FULL| T | 53459 | 4489K| 113 (1)|
---------------------------------------------------------------
SQL> select value
2 from v$spparameter
3 where name = 'db_file_multiblock_read_count';
VALUE
-----------
16
172
SQL> alter session set events
2 = '10046 trace name context forever, level 8';
SQL> select * from T;
PARSING IN CURSOR #22 len=15 dep=0 uid=124 oct=3 lid=124 ...
select * from T
END OF STMT
PARSE #22:c=10000,e=108,p=0,cr=0,cu=0,mis=0,r=0,dep=0,og=4
EXEC #22:c=0,e=65,p=0,cr=0,cu=0,mis=0,r=0,dep=0,og=4
WAIT #22: nam='db file scattered read' ela= 3387
file#=5 block#=13122 blocks=16 obj#=199963
WAIT #22: nam='db file scattered read' ela= 3188
file#=5 block#=13234 blocks=16 obj#=199963
WAIT #22: nam='db file scattered read' ela= 3125
file#=5 block#=13250 blocks=16 obj#=199963
WAIT #22: nam='db file scattered read' ela= 3255
file#=5 block#=13266 blocks=16 obj#=199963
WAIT #22: nam='db file scattered read' ela= 3369
file#=5 block#=13282 blocks=16 obj#=199963

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173
SSTIOMAX
174
1 MB

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db_block_size = 8192
176
db_file_multiblock_read_count = 128

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177
?
178

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single block read (8KB)

multi block read (1MB)
180
the solution ?

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181
system stats (9i)
182
SQL> select pname, pval1
2 from sys.aux_stats$
3 /
PNAME PVAL1
------------------------------ ----------
SREADTIM 4.065
MREADTIM 6.173
CPUSPEED 567
MBRC 12
MAXTHR 48203776
SLAVETHR -1

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183
use MBRC to cost
184
use db_file_multiblock_read_count to read

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185
Inflammatory
statements
which will
alienate the
audience
Presentation Duration
1
2
3
186
forget about system statistics

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187
do not gather them
188
?

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189
190
absolutely vital…
…to have them
set change

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191
problem #1
192

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193
problem #2
194
monitoring for bad....

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195
optimizing for bad
196
recommendation #3

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197
gather
into STAT table
198
monitor

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set once
200
the defaults are probably fine

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SQL> select pname, pval1
2 from sys.aux_stats$
3 /
PNAME PVAL1
---------------------- ----------
IOSEEKTIM 10 (ms)
IOTFRSPEED 4096 (bytes/ms)
SREADTIM = IOSEEKTIM + 8k / IOTFRSPEED = 10ms
MREADTIM = IOSEEKTIM + mbrc * 8k / IOTFRSPEED = 26ms
202
10.2 and above

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db_file_multiblock_read_count
_db_file_exec_read_count
_db_file_optimizer_read_count
204
dbms_resource_manager
to calibrate

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205
so far...
206
not changing statistics

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207
eventually....
208
the time will come...

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209
one possible reason
210
even if stats unchanged …

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211
… your plans might !
212
cardinality is everything
212

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213
214

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215
same with Oracle
215
SQL> create table T as
2 select to_date('01-AUG-2013')+
3 trunc(dbms_random.value(0,7)) dte,
4 rpad('padding',20) padding
5 from dual
6 connect by level <= 100000;
Table created.

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SQL> select dte, count(*)
2 from t
3 group by dte
4 order by 1;
DTE COUNT(*)
--------- ----------
01-AUG-13 14334
02-AUG-13 14222
03-AUG-13 14167
04-AUG-13 14510
05-AUG-13 14346
06-AUG-13 14349
07-AUG-13 14072
218
15,000 rows per day always

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SQL> exec dbms_stats.gather_table_stats(user,'T')
PL/SQL procedure successfully completed.
SQL> create index IX on T ( dte ) ;
Index created.
pre 12c
SQL> select * from t where dte = '03-AUG-2013';
--------------------------------------------------
| Id | Operation | Name | Rows | Bytes |
--------------------------------------------------
| 0 | SELECT STATEMENT | | 14286 | 404K|
|* 1 | TABLE ACCESS FULL| T | 14286 | 404K|
--------------------------------------------------

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221
a week later…
222
another 15,000 rows per day

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SQL> insert into T
2 select to_date('08-AUG-2013')+
3 trunc(dbms_random.value(0,7)) dte,
4 rpad('padding',20) padding
5 from dual
6 connect by level <= 100000;
100000 rows created.
SQL> select dte, count(*)
2 from t
3 group by dte
4 order by 1;
DTE COUNT(*)
--------- ----------
01-AUG-13 14334
...
07-AUG-13 14072
08-AUG-13 14261
09-AUG-13 14106
10-AUG-13 14410
11-AUG-13 14289
12-AUG-13 14358
13-AUG-13 14252
14-AUG-13 14324

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225
statistics unchanged
226

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227
SQL> select * from t where dte = '12-AUG-2013';
----------------------------------------------------
| Id | Operation | Name | Rows |
----------------------------------------------------
| 0 | SELECT STATEMENT | | 2381 |
| 1 | TABLE ACCESS BY INDEX ROWID| T | 2381 |
|* 2 | INDEX RANGE SCAN | IX | 2381 |
----------------------------------------------------

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SQL> select * from t where dte = '14-AUG-2013';
----------------------------------------------------
| Id | Operation | Name | Rows |
----------------------------------------------------
| 0 | SELECT STATEMENT | | 1 |
| 1 | TABLE ACCESS BY INDEX ROWID| T | 1 |
|* 2 | INDEX RANGE SCAN | IX | 1 |
----------------------------------------------------
230
why ?

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SQL> select low_value, high_value
2 from user_tab_columns
3 where table_name = 'T'
4 and column_name = 'DTE';
LOW_VALUE HIGH_VALUE
-------------------- -----------------
78710801010101 78710807010101
SQL> set serverout on
SQL> declare
2 res date;
3 begin
4 dbms_stats.convert_raw_value(
5 '78710801010101',res);
6 dbms_output.put_line(res);
7 dbms_stats.convert_raw_value(
8 '78710807010101',res);
9 dbms_output.put_line(res);
10 end;
11 /
01-AUG-13
07-AUG-13

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01-AUG-13 07-AUG-13
234
when the time comes…

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235
as accurate as possible
236
as cheaply as possible

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237
statistics accurately
238
extended statistics

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239
some real data
239
240
SQL> desc VEHICLE
Name Null? Type
-------------------------- -------- -------------
ID NUMBER
MAKE VARCHAR2(12)
MODEL VARCHAR2(12)
...
SQL> select count(*)
2 from VEHICLE;
COUNT(*)
------------
4,770,662
240

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241
default stats not enough
241
242
SQL> select count(*)
2 from VEHICLE
3 where MAKE = 'TOYOTA';
COUNT(*)
----------
608822
------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost |
------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 7 | 18|
| 1 | SORT AGGREGATE | | 1 | 7 | |
|* 2 | INDEX RANGE SCAN| MAKE_IX | 6325 | 44275 | 18|
------------------------------------------------------------
242

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243
histogram
243
244
SQL> begin
2 dbms_stats.gather_table_stats(user,'VEHICLE',
3 method_opt=>'for all columns size 1,'||
4 'for columns MAKE size auto,'||
5 'for columns MODEL size auto');
6 end;
7 /
PL/SQL procedure successfully completed.
244

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245
SQL> select count(*)
2 from VEHICLE
3 where MAKE = 'TOYOTA';
COUNT(*)
----------
608822
-----------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost
-----------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 7 | 1465
| 1 | SORT AGGREGATE | | 1 | 7 |
|* 2 | INDEX RANGE SCAN| MAKE_IX | 589K| 4027K| 1465
-----------------------------------------------------------
245
246
make AND model
246

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247
SQL> select count(*)
2 from VEHICLE
3 where MAKE = 'TOYOTA'
4 and MODEL = 'COROLLA';
COUNT(*)
----------
257364
-----------------------------------------------------------------
| Id | Operation | Name | Rows |
-----------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 |
| 1 | SORT AGGREGATE | | 1 |
|* 2 | TABLE ACCESS BY INDEX ROWID BATCHED| VEHICLE | 301 |
|* 3 | INDEX RANGE SCAN | MODEL_IX | 2436 |
-----------------------------------------------------------------
247
248
40% (!) of Toyotas are Corollas
248

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249
two things
249
250

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251
251
252
2) no correlation
10g and before
252

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253
11g+
253
254
SQL> select
2 DBMS_STATS.CREATE_EXTENDED_STATS(
3 user, 'VEHICLE','(MAKE,MODEL)') tag
4 from dual;
TAG
----------------------------------
SYS_STU8QPK2S$PEWHARK2CP3#1F#G
254

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128
255
SQL> begin
2 dbms_stats.gather_table_stats(user,'VEHICLE',
3 method_opt=>
4 'for columns (make,model) size 254');
5 end;
6 /
PL/SQL procedure successfully completed.
255
256
SQL> select count(*)
2 from VEHICLE
3 where MAKE = 'TOYOTA'
4 and MODEL = 'COROLLA';
COUNT(*)
----------
257364
----------------------------------------------------------------
| Id | Operation | Name | Rows |
----------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 |
| 1 | SORT AGGREGATE | | 1 |
|* 2 | TABLE ACCESS BY INDEX ROWID BATCHED| VEHICLE | 248K|
|* 3 | INDEX RANGE SCAN | MODEL_IX | 2436|
----------------------------------------------------------------
256

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257
which columns to collect ?
257
258
11.2+ column groups
258

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259
SQL> exec DBMS_STATS.SEED_COL_USAGE(NULL,NULL,1800);
259
260
note ... 12c
260

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131
261
can be created automatically
261
262
its just another column
262

132. 9/26/2013
132
263
SQL> select "SYS_STU8QPK2S$PEWHARK2CP3#1F#G"
2 from vehicle
3 where rownum < 10;
SYS_STU8QPK2S$PEWHARK2CP3#1F#G
------------------------------
1.2706E+19
1.8075E+19
7.9949E+18
1.1730E+19
6.7142E+18
1.1730E+19
1.0779E+19
5.4051E+18
7.3555E+18
263
264
SQL> SELECT extension_name, extension
2 FROM USER_STAT_EXTENSIONS
3 WHERE table_name = 'VEHICLE';
EXTENSION_NAME EXTENSION
------------------------------ -----------------
SYS_STU8QPK2S$PEWHARK2CP3#1F#G ("MAKE","MODEL")
264

133. 9/26/2013
133
265
SQL> select SYS_OP_COMBINED_HASH(make,model) hashval,
2 "SYS_STU8QPK2S$PEWHARK2CP3#1F#G" colval
3 from VEHICLE
4 where rownum < 10;
HASHVAL COLVAL
---------- ----------
1.2706E+19 1.2706E+19
1.8075E+19 1.8075E+19
7.9949E+18 7.9949E+18
1.1730E+19 1.1730E+19
6.7142E+18 6.7142E+18
1.1730E+19 1.1730E+19
1.0779E+19 1.0779E+19
5.4051E+18 5.4051E+18
7.3555E+18 7.3555E+18
265
266
PARSING IN CURSOR #28
alter table "SH"."VEHICLE" add
(SYS_STU8QPK2S$PEWHARK2CP3#1F#G
as (SYS_OP_COMBINED_HASH(MAKE,MODEL))
virtual BY USER for statistics);
END OF STMT
266

134. 9/26/2013
134
267
virtual column
267
be careful
268
268
SYS_OP_COMBINED_HASH

135. 9/26/2013
135
269
hash means equality
269
270
SQL> select count(*)
2 from VEHICLE
3 where MAKE in ('FORD','TOYOTA')
4 and MODEL = 'COROLLA';
COUNT(*)
----------
214468
-----------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost
-----------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | 14 | 1921
| 1 | SORT AGGREGATE | | 1 | 14 |
|* 2 | VIEW | index$_join$_001 | 77818 | 1063K| 1921
|* 3 | HASH JOIN | | | |
|* 4 | INDEX RANGE SCAN | MODEL_IX | 77818 | 1063K| 502
| 5 | INLIST ITERATOR | | | |
|* 6 | INDEX RANGE SCAN| MAKE_IX | 77818 | 1063K| 2086
-----------------------------------------------------------------------
270

136. 9/26/2013
136
271
better in 12
271
272
SQL> select count(*)
2 from VEHICLE
3 where MAKE in ('FORD','TOYOTA')
4 and MODEL = 'COROLLA';
COUNT(*)
----------
214468
-----------------------------------------------------------------
| Id | Operation | Name | Rows |
-----------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 |
| 1 | SORT AGGREGATE | | 1 |
|* 2 | TABLE ACCESS BY INDEX ROWID BATCHED| VEHICLE | 272K|
|* 3 | INDEX RANGE SCAN | MODEL_IX | 2436 |
-----------------------------------------------------------------
272

137. 9/26/2013
137
273
273
11.2+
274
actual versus estimate
274

138. 9/26/2013
138
275
SQL> select /*+ GATHER_PLAN_STATISTICS */ count(*)
2 from VEHICLE
3 where MAKE = 'FORD'
4 and MODEL = 'FOCUS';
COUNT(*)
----------
214468
SQL> SELECT *
2 FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(
3 NULL, NULL, 'ALLSTATS LAST'));
----------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | A-Rows |
----------------------------------------------------------------
| 1 | SORT AGGREGATE | | 1 | 1 | 1 |
|* 2 | TABLE ACCESS FULL| VEHICLE | 1 | 220K| 214K|
-----------------------------------------------------------------
275
276
276
employ someone....

139. 9/26/2013
139
277
277
check every query...
278
SQL> select /*+ GATHER_PLAN_STATISTICS */ count(*)
2 from VEHICLE
3 where MAKE = 'FORD'
4 and MODEL = 'FOCUS';
COUNT(*)
----------
214468
SQL> SELECT *
2 FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(
3 NULL, NULL, 'ALLSTATS LAST'));
-----------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | A-Rows |
-----------------------------------------------------------------
| 1 | SORT AGGREGATE | | 1 | 1 | 1 |
|* 2 | TABLE ACCESS FULL| VEHICLE | 1 | 220K| 214K|
-----------------------------------------------------------------
278
"ok"

140. 9/26/2013
140
279
279
280
280
but just maybe ....

141. 9/26/2013
141
281
281
... someone already is
282
cool

142. 9/26/2013
142
SQL> create table EMP as
2 select rownum empno,
3 mod(rownum,10) jobid,
4 mod(rownum,10)*1000 salary,
5 mod(rownum,50)+1 deptno
6 from dual
7 connect by rownum < 100000;
SQL> create table DEPT as
2 select rownum deptno,
3 'dept'||rownum dname
4 from dual
5 connect by rownum <= 100;
283
100,000 rows
100 rows
SQL> exec dbms_stats.gather_table_stats(user,'EMP');
SQL> exec dbms_stats.gather_table_stats(user,'DEPT');
SQL> create index EMP_IX on EMP ( deptno );
SQL> create index DEPT_IX on DEPT ( deptno );
284

143. 9/26/2013
143
SQL> select e.empno, d.dname
2 from emp e, dept d
3 where d.deptno = e.deptno
4 and e.jobid < 3
5 and e.salary > 9000;
no rows selected
----------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes |
----------------------------------------------------------------
| 0 | SELECT STATEMENT | | | |
| 1 | MERGE JOIN | | 1500 | 36000 |
| 2 | TABLE ACCESS BY INDEX ROWID| DEPT | 100 | 1000 |
| 3 | INDEX FULL SCAN | DEPT_IX | 100 | |
|* 4 | SORT JOIN | | 1500 | 21000 |
|* 5 | TABLE ACCESS FULL | EMP | 1500 | 21000 |
----------------------------------------------------------------
285
4 and e.jobid < 3
5 and e.salary > 9000;
hard to
optimize
re-run the query
286

144. 9/26/2013
144
287
no anythingchanges to
SQL> select e.empno, d.dname
2 from emp e, dept d
3 where d.deptno = e.deptno
4 and e.jobid < 3
5 and e.salary > 9000;
no rows selected
---------------------------------------------------
| Id | Operation | Name | Rows | Bytes |
---------------------------------------------------
| 0 | SELECT STATEMENT | | | |
|* 1 | HASH JOIN | | 67 | 1608 |
| 2 | TABLE ACCESS FULL| DEPT | 1 | 10 |
|* 3 | TABLE ACCESS FULL| EMP | 3333 | 46662 |
---------------------------------------------------
Note
-----
- statistics feedback used for this statement
288

145. 9/26/2013
145
11.2
289
the optimizer knows what "hard" is
290

146. 9/26/2013
146
cardinality feedback
291
statistics feedback
292
12c

147. 9/26/2013
147
its not continuous
293
12c better
294

148. 9/26/2013
148
see it !
295
SQL> select sql_id,
2 child_number,
3 is_reoptimizable,
4 is_shareable
2 from v$sql s
3 where sql_text like 'select ...';
SQL_ID CHILD_NUMBER I I
------------- ------------ - -
68vghuy0cr298 0 Y N
68vghuy0cr298 1 N Y
296

149. 9/26/2013
149
hangs around
297
SQL> exec dbms_spd.flush_sql_plan_directive;
PL/SQL procedure successfully completed.
SQL> select d.type, d.reason, o.object_name
2 from dba_sql_plan_directives d,
3 dba_sql_plan_dir_objects o
4 where o.directive_id = d.directive_id
5 and o.owner = 'SCOTT';
TYPE REASON OBJ
---------------- ------------------------------------ -----
DYNAMIC_SAMPLING SINGLE TABLE CARDINALITY MISESTIMATE DEPT
298

150. 9/26/2013
150
problem with statistics feedback
299
pay the price once !
300

151. 9/26/2013
151
301
302
"I'll take a different route tomorrow"

152. 9/26/2013
152
303
the reality...
304

153. 9/26/2013
153
305
adaptive optimization
12c
306
accurate stats not always possible...

154. 9/26/2013
154
307
you can't have stats
308
on everything !

155. 9/26/2013
155
309
when stats wont do...
310
... use the real data

156. 9/26/2013
156
311
dynamic sampling
312
SQL> drop table TOUGH_DATA purge;
Table dropped.
SQL> create table TOUGH_DATA nologging as
2 select
3 rownum pk,
4 dbms_random.string('U',10) str
5 from dual
6 connect by level < 1000000
7 /
Table created.
SQL> exec dbms_stats.gather_table_stats(
user,'TOUGH_DATA')

157. 9/26/2013
157
313
SQL> select count(*)
2 from TOUGH_DATA
3 where str like '%XX'
4 /
COUNT(*)
----------
1452
hard
314
SQL> select count(*)
2 from TOUGH_DATA
3 where str like '%XX'
4 /
-------------------------------------------------
| Id | Operation | Name | Rows |
-------------------------------------------------
| 0 | SELECT STATEMENT | | 1 |
| 1 | SORT AGGREGATE | | 1 |
|* 2 | TABLE ACCESS FULL| TOUGH_DATA | 50000 |
-------------------------------------------------
5% assumption

158. 9/26/2013
158
315
SQL> select /*+ dynamic_sampling(t 2) */ count(*)
2 from TOUGH_DATA t
3 where str like '%XX'
4 /
-------------------------------------------------
| Id | Operation | Name | Rows |
-------------------------------------------------
| 0 | SELECT STATEMENT | | 1 |
| 1 | SORT AGGREGATE | | 1 |
|* 2 | TABLE ACCESS FULL| TOUGH_DATA | 1252 |
-------------------------------------------------
316
simple queries as well

159. 9/26/2013
159
317
SQL> create table EASY_DATA nologging as
2 select
3 rownum pk,
4 chr(65+trunc(rownum/40000)) str
5 from dual
6 connect by level < 1000000
7 /
Table created.
SQL> exec dbms_stats.gather_table_stats(user,'EASY_DATA')
PL/SQL procedure successfully completed.
A,A,A,A,A,….B,B,B,B,.....1,2,3,4,5,6......
318
SQL> select count(*)
2 from EASY_DATA
3 where str = 'F'
4 and pk > 900000;
COUNT(*)
----------
0

160. 9/26/2013
160
319
SQL> select count(*)
2 from EASY_DATA
3 where str = 'F'
4 and pk > 900000;
------------------------------------------------
| Id | Operation | Name | Rows |
------------------------------------------------
| 0 | SELECT STATEMENT | | 1 |
| 1 | SORT AGGREGATE | | 1 |
|* 2 | TABLE ACCESS FULL| EASY_DATA | 4000 |
------------------------------------------------
320
SQL> select /*+ dynamic_sampling(t 2) */ count(*)
2 from EASY_DATA t
3 where str = 'F'
4 and pk > 900000;
------------------------------------------------
| Id | Operation | Name | Rows |
------------------------------------------------
| 0 | SELECT STATEMENT | | 1 |
| 1 | SORT AGGREGATE | | 1 |
|* 2 | TABLE ACCESS FULL| EASY_DATA | 23 |
------------------------------------------------

161. 9/26/2013
161
321
or ...
322
someone else's problem

162. 9/26/2013
162
323
12c
324
dynamic sampling
statistics

163. 9/26/2013
163
325
SQL> select /*+ dynamic_sampling(t 2) */ count(*)
2 from TOUGH_DATA t
3 where str like '%XX'
4 /
-------------------------------------------------
| Id | Operation | Name | Rows |
-------------------------------------------------
| 0 | SELECT STATEMENT | | 1 |
| 1 | SORT AGGREGATE | | 1 |
|* 2 | TABLE ACCESS FULL| TOUGH_DATA | 1252 |
-------------------------------------------------
326
SQL> alter session set optimizer_dynamic_sampling = 11;
SQL> select count(*)
2 from TOUGH_DATA t
3 where str like '%XX'
4 /
-------------------------------------------------
| Id | Operation | Name | Rows |
-------------------------------------------------
| 0 | SELECT STATEMENT | | 1 |
| 1 | SORT AGGREGATE | | 1 |
|* 2 | TABLE ACCESS FULL| TOUGH_DATA | 1252 |
-------------------------------------------------
Note
-----
- dynamic statistics used (level=AUTO)
no hint

164. 9/26/2013
164
327
11.2+
328
parallel queries (may be) sampled

165. 9/26/2013
165
329
SQL> select count(*)
2 from EASY_DATA t
3 where str = 'F'
4 and pk > 900000;
----------------------------------------------------
| Id | Operation | Name | Rows |
----------------------------------------------------
| 0 | SELECT STATEMENT | | 1 |
| 1 | SORT AGGREGATE | | 1 |
| 2 | PX COORDINATOR | | |
| 3 | PX SEND QC (RANDOM) | :TQ10000 | 1 |
| 4 | SORT AGGREGATE | | 1 |
| 5 | PX BLOCK ITERATOR | | 4 |
|* 6 | TABLE ACCESS FULL| EASY_DATA | 4 |
----------------------------------------------------
Note
-----
- dynamic sampling used for this statement (level=4)
330
low frequency

166. 9/26/2013
166
331
high cost
332
statistics cheaply

167. 9/26/2013
167
333
SQL> desc DBA_TABLES
Name Null? Type
----------------------------- -------- -------------
OWNER NOT NULL VARCHAR2(30)
TABLE_NAME NOT NULL VARCHAR2(30)
COLUMN_NAME NOT NULL VARCHAR2(30)
...
NUM_ROWS NUMBER
334
SQL> desc DBA_TAB_COLS
Name Null? Type
----------------------------- -------- -------------
OWNER NOT NULL VARCHAR2(30)
TABLE_NAME NOT NULL VARCHAR2(30)
COLUMN_NAME NOT NULL VARCHAR2(30)
...
NUM_DISTINCT NUMBER
LOW_VALUE RAW(32)
HIGH_VALUE RAW(32)
...

168. 9/26/2013
168
335
SQL> desc PEOPLE
Name Null? Type
----------------------------- -------- -------------
PID NUMBER
GENDER CHAR(1)
NAME VARCHAR2(47)
AGE NUMBER
336
SQL> alter session set sql_true = true;
Session altered.
SQL> begin
2 dbms_stats.gather_table_stats(
3 'DEMO',
4 'PEOPLE);
5 end;
6 /

169. 9/26/2013
169
337
select
/*+ no_parallel(t)
no_parallel_index(t)
dbms_stats
cursor_sharing_exact
use_weak_name_resl
dynamic_sampling(0)
no_monitoring
no_substrb_pad */
count(*),
...
count("GENDER"),
count(distinct "GENDER"),
substrb(dump(min("GENDER"),16,0,32),1,120),
substrb(dump(max("GENDER"),16,0,32),1,120),
...
from "MCDONAC"."PEOPLE" t
count("GENDER")
count(distinct "GENDER")
min("GENDER")
max("GENDER")
338
count("GENDER")
count(distinct "GENDER")
min("GENDER")
max("GENDER")
one pass
one pass
one pass
hard

170. 9/26/2013
170
339
SQL> select count(*) from PEOPLE;
COUNT(*)
------------
500,000,000
Elapsed: 00:04:43.73
340
SQL> select count(distinct GENDER) g
2 from PEOPLE;
G
------------
2
Elapsed: 00:13:12.92

171. 9/26/2013
171
341
SQL> begin
2 dbms_stats.gather_table_stats(
3 user,
4 'PEOPLE',
5 estimate_percent=>25);
6 end;
7 /
ERROR at line 1:
ORA-01652: unable to extend temp
segment by 128 in tablespace TEMP
Elapsed: 00:16:37.12
342
11g

172. 9/26/2013
172
343
one pass ~NDV
344
HASH
12 6 3 12 3 7 11 12 33 6 11 12 6 45 15 7 15 17 45 6 17
12 6 3 7 11 33 45 15 17

173. 9/26/2013
173
345
NDV = 9
12 6 3 7 11 33 45 15 17
346
what about large NDV ?
12
6
3
7
11
33
45
15
17
21
92
71
34
56
615
2
41
64
91
73

174. 9/26/2013
174
347
"Big" HASH
348
NDV =
remaining hashes x
2^number of splits

175. 9/26/2013
175
349
demo
350
SQL> create table ONE_PASS nologging
2 as select substr(text,1,1) single_char
3 from DBA_SOURCE;
Table created.
SQL> select count(distinct single_char) ndv
2 from one_pass;
NDV
----------
83

176. 9/26/2013
176
351
0 127
16 buckets...
352
64 127

177. 9/26/2013
177
353
96 127
354
SQL> set serverout on
SQL> declare
2 type t_bucket is table of varchar2(1);
3 l_synopsis t_bucket;
4 l_splits number := 0;
5 l_hash int;
6 l_min_val int := 0;
7 l_synopsis_size int := 16;
8 begin
9 for i in ( select single_char from one_pass ) loop
10 l_hash := ascii(i.single_char);
11
12 if l_synopsis.count = l_synopsis_size then
13 l_min_val :=
14 case
15 when l_min_val = 0 then 64
16 when l_min_val = 64 then 96
17 when l_min_val = 96 then 112
18 when l_min_val = 112 then 120
19 end;
20 l_splits := l_splits + 1;

178. 9/26/2013
178
355
22
23 for j in 1 .. l_min_val loop
24 if l_synopsis.exists(j) then
25 l_synopsis.delete(j);
26 end if;
27 end loop;
28 end if;
29
30 if l_hash > l_min_val then
31 l_synopsis(l_hash) := 'Y';
32 end if;
33 end loop;
34 dbms_output.put_line(l_synopsis.count *
35 power(2,l_splits));
36 end;
37 /
Splitting, keeping entries above 64
Splitting, keeping entries above 96
Splitting, keeping entries above 112
88
356
the reality
16384 bucket limit
18,446,744,073,709,551,616 hash range

179. 9/26/2013
179
357
SQL> begin
2 dbms_stats.gather_table_stats(
3 user,
4 'PEOPLE',
5 estimate_percent=>25);
6 end;
7 /
PL/SQL procedure successfully completed.
Elapsed: 00:05:39.82
358
recommendation #4

180. 9/26/2013
180
359
estimate_percent
use DEFAULT size (AUTO)
360
only for columns
without histograms*
(* better in 12c)

181. 9/26/2013
181
361
cheaply .... other options
362
do it elsewhere...

182. 9/26/2013
182
363
SQL> alter database convert to snapshot standby;
SQL> begin
2 dbms_scheduler.open_window(
3 'MONDAY_WINDOW',force=>true)
4 end;
5 /
[wait]
SQL> exec dbms_stats.export_database_stats(...)
SQL> insert into DB@target select * from STATTAB;
SQL> alter database convert to physical standby;
364
histograms

183. 9/26/2013
183
365
Inflammatory
statements
which will
alienate the
audience
Presentation Duration
1
2
3
4
366
"histograms are only goodness.
Only use METHOD_OPT auto"
Maria Colgan, Oct 2013
(2 days ago)

184. 9/26/2013
184
367
similar quote
368
histograms...

185. 9/26/2013
185
369
... SUCK
370
not really but...

186. 9/26/2013
186
371
two problems
372
1) risks when gathering

187. 9/26/2013
187
373
missing values in sample
374

188. 9/26/2013
188
375
SQL> select availability, count(*)
2 from bet_events
3 group by availability;
AVAILABILITY COUNT(*)
-------------------- ----------
Pending 3404
Open 18
Closed 12345
Completed 3840938
...
...
376
SQL> begin
2 dbms_stats.gather_table_stats('','bet_events',
3 method_opt=>'for all columns size 1,
4 for columns availability size 10');
5 end;
6 /
SQL> set autotrace traceonly explain
SQL> select * from bet_events
2 where availability = 'UnProcessed';
------------------------------------------------
| Id | Operation | Name | Rows |
------------------------------------------------
| 0 | SELECT STATEMENT | | 18 |
|* 1 | TABLE ACCESS FULL| BET_EVENTS | 18 |
------------------------------------------------

189. 9/26/2013
189
377
SQL> select availability, count(*)
2 from bet_events
3 group by availability;
AVAILABILITY COUNT(*)
-------------------- ----------
Pending 3404
Open 18
Closed 12345
Completed 3840938
...
...
56
378
SQL> set autotrace traceonly explain
SQL> select * from bet_events
2 where availability = 'UnProcessed';
----------------------------------------------
| Id | Operation | Name | Rows|
----------------------------------------------
| 0 | SELECT STATEMENT | | 929 |
|* 1 | TABLE ACCESS FULL| BET_EVENTS | 929 |
----------------------------------------------

190. 9/26/2013
190
379
missing values in height balanced
380
12c a lot better...
top n frequency hybrid
"histograms are only goodness"maybe

191. 9/26/2013
191
381
2) the worst thing in 9i

192. 9/26/2013
192
383
SQL> variable b1 number
SQL> exec :b1 := 1
SQL> select /*+ gather_plan_statistics */ *
2 from MY_100K_ROWS
3 where r < :b1;
------------------------------------------------------------
| Id | Operation | Name | E-Rows | A-Rows |
------------------------------------------------------------
| 0 | SELECT STATEMENT | | | 0 |
|* 1 | TABLE ACCESS FULL| MY_100K_ROWS | 5000 | 0 |
------------------------------------------------------------
5%
384

193. 9/26/2013
193
385
histograms
386
10g

194. 9/26/2013
194
387
method_opt
for all columns size auto
388
sys.col_usage$

195. 9/26/2013
195
389
SQL> desc SYS.COL_USAGE$
Name Null? Type
----------------------- -------- ---------
OBJ# NUMBER
INTCOL# NUMBER
EQUALITY_PREDS NUMBER
EQUIJOIN_PREDS NUMBER
NONEQUIJOIN_PREDS NUMBER
RANGE_PREDS NUMBER
LIKE_PREDS NUMBER
NULL_PREDS NUMBER
TIMESTAMP DATE
390
Oracle doesn’t know ...

196. 9/26/2013
196
391
... how your app works
392
... what your app is !

197. 9/26/2013
197
393
example 1
394
SQL> create table T
2 as select * from dba_objects;
Table created.
SQL> exec dbms_stats.gather_table_stats('','T');
PL/SQL procedure successfully completed.

198. 9/26/2013
198
395
SQL> select COLUMN_NAME,NUM_DISTINCT,
2 ( select count(*)
3 from all_tab_histograms
4 where owner = a.owner
5 and table_name = a.table_name
6 and column_name = a.column_name )
7 from all_tab_cols a
8 where table_name = 'T'
9 order by column_id;
COLUMN_NAME NUM_DISTINCT HIST_CNT
------------------------------ ------------ ----------
OWNER 25 2
OBJECT_NAME 53000 2
SUBOBJECT_NAME 230 2
OBJECT_ID 90808 2
396
then...

199. 9/26/2013
199
397
398

200. 9/26/2013
200
399
SQL> select intcol#,equality_preds,
2 range_preds,timestamp
3 from sys.col_usage$
4 where obj# = (select object_id
5 from obj
6 where object_name = 'T' );
INTCOL# EQUALITY_PREDS RANGE_PREDS TIMESTAMP
---------- -------------- ----------- ---------
1 1 0 24-SEP-13
400
SQL> exec dbms_stats.gather_table_stats('','T');
SQL> select COLUMN_NAME,NUM_DISTINCT,
2 ( select count(*)
3 from all_tab_histograms
4 where owner = a.owner
5 and table_name = a.table_name
6 and column_name = a.column_name )
7 from all_tab_cols a
8 where table_name = 'T'
9 order by column_id;
COLUMN_NAME NUM_DISTINCT HIST_CNT
------------------------------ ------------ ----------
OWNER 25 25
OBJECT_NAME 53000 2
SUBOBJECT_NAME 230 2
OBJECT_ID 90808 2

201. 9/26/2013
201
401
Oracle doesn’t know your app !
402
example 2

202. 9/26/2013
202
403
boudary conditions
404
SQL> create table T (
2 skew varchar2(10),
3 even number);
Table created.
SQL> insert into T
2 select
3 case
4 when rownum > 99995 then 'SPECIAL'
5 else dbms_random.string('U',8)
6 end,
7 mod(rownum,200)
8 from dual
9 connect by level <= 100000
10 /
100000 rows created.
5 special
values
even
distribution

203. 9/26/2013
203
405
SQL> exec dbms_stats.gather_table_stats(
user,'T', estimate_percent=>null);
PL/SQL procedure successfully completed.
SQL> select COLUMN_NAME,NUM_DISTINCT,DENSITY,
2 ( select count(*)
3 from user_tab_histograms
4 where table_name = 'T'
5 and column_name = c.column_name )
6 from user_tab_cols c
7 where table_name = 'T'
8 order by table_name,COLUMN_ID
9 /
COLUMN_NAME NUM_DISTINCT DENSITY HIST_CNT
------------------- ------------ ---------- ----------
SKEW 99996 .00001 2
EVEN 200 .005 2
406
SQL> select * from T where skew = 'SPECIAL';
SKEW VAL
---------- ----------
SPECIAL 196
SPECIAL 197
SPECIAL 198
SPECIAL 199
SPECIAL 0
5 rows selected.
SQL> select * from T where even = 5;
TAG VAL
---------- ----------
IBRXGVIE 5
[snip]
500 rows selected.

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SQL> exec dbms_stats.gather_table_stats(
user,'T', estimate_percent=>null);
PL/SQL procedure successfully completed.
SQL> select COLUMN_NAME,NUM_DISTINCT,DENSITY,
2 ( select count(*)
3 from user_tab_histograms
4 where table_name = 'T'
5 and column_name = c.column_name )
6 from user_tab_cols c
7 where table_name = 'T'
8 order by table_name,COLUMN_ID
9 /
COLUMN_NAME NUM_DISTINCT DENSITY HIST_CNT
------------------- ------------ ---------- ----------
SKEW 99996 .00001 2
EVEN 200 .000005 200
408
recommendation #5

205. 9/26/2013
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409
histograms...
...can be very cool
suck
410
explicit control for each table

206. 9/26/2013
206
411
set_schema_prefs
for all columns size 1
get NDV benefit...better in 12c
412
set_table_prefs
for column CCC size nnn

207. 9/26/2013
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413
one more useful tool
414

208. 9/26/2013
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415
416
SQL> desc CONFERENCE_ATTENDEES
Name Null? Type
----------------------------- -------- --------------
PID NUMBER
GENDER CHAR(1)
NAME VARCHAR2(40)
AGE NUMBER

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417
SQL> select
2 count(distinct GENDER) NDV
3 from
4 CONFERENCE_ATTENDEES
NDV
----------------------
???
418
SQL> select
2 ntile(GENDER) over ( ... )
3 from
4 CONFERENCE_ATTENDEES

210. 9/26/2013
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419
set_table_stats
num_rows
avg_row_len
420
set_column_stats
high_value
num_distinct

211. 9/26/2013
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421
when all else fails ...
422
... lie and cheat

212. 9/26/2013
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423
424
no

213. 9/26/2013
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425
analyze ... validate structure
426
SQL> desc INDEX_STATS
Name Null? Type
----------------------------- -------- --------------
HEIGHT NUMBER
BLOCKS NUMBER
NAME VARCHAR2(30)
PARTITION_NAME VARCHAR2(30)
...
OPT_CMPR_COUNT NUMBER
OPT_CMPR_PCTSAVE NUMBER

214. 9/26/2013
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427
wrap up
428
don't collect stats .... unless
don't collect system stats ... unless
don't collect histograms ... unless
default estimate size (NDV)
lie and cheat

215. 9/26/2013
215
Connor McDonald
429
www.oracledba.co.uk
connormcdonald.wordpress.com
@connor_mc_d
Thu 11:00, SQL Tuning 101,
Moscone South, 102
sorry :-)
ORA-03113
connormcdonald.wordpress.com 430