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2013-2-18
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2. • Important Statistics Values and Parameters
• Cardinality and Selectivity
• IO Cost model
• New Cost model
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3. Table Statistics:
Number of table blocks(BLOCKS)
Number of table rows(NUM_ROWS)
Index Statistics:
Levels of the index(BLEVEL)
Number of leaf blocks (LEAF_BLOCKS)
Clustering factor(CLUSTERING_FACTOR)
Number of distinct keys(DISTINCT_KEYS)
Column Statistics:
Number of distinct values(NUM_DISTINCT)
Number of NULL values(NUM_NULLS)
Density
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6. • NUM_DISTINCT=number of distinct value
• Base Cardinality = number of rows of the table
• FF=filter factor of the condition=1 / NUM_DISTINCT(column)
• Selectivity = FF= Estimated cardinality /Base Cardinality
• Estimated Cardinality = Selectivity * Base Cardinality
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7. • C1=value 1/NUM_DISTINCT
• C1 like value 1/NUM_DISTINCT
• C1>value ((Hi-Value)/(Hi-Lo))
• C1<value ((Value-Lo)/(Hi-Lo))
• C1>=value ((Hi-Value)/(Hi-Lo))+1/NUM_DISTINCT
• C1<=value ((Value-Lo)/(Hi-Lo))+1/NUM_DISTINCT
• C1 between value1 and value2 ((value2 – value1)/(Hi-
Lo))+2/NUM_DISTINCT
• Notice: if column is NULL
Adjusted selectivity =
Base selectivity * (1 - num_nulls/num_rows)
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8. • C1=:B1 C1.Density
• C1 like :B1 { 0.05 | C1.Density }
• C1 { < | <= | > | >= } :B1 C1.Density
• C1 between :B1 and :B2 C1.Density*C2. Density
• Notice: if column is NULL
Adjusted selectivity =
C1.Density * ( 1 - num_nulls/ num_rows )
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9. • C1 and C2 FF1 * FF2
• C1 or C2 FF1 + FF2 - FF1 * FF2
• Not C1 1-FF1
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11. • Full Table Scan:
Cost=( NBLKS/ k )+1 (if _table_scan_cost_plus_one = true)
• Non-Index costing:
Cost = blevel + (leaf_blocks * effective index selectivity)
+(clustering_factor * effective table selectivity)
• Unique-Index costing:
Cost=blevel + min cost of index +(clustering_factor * effective table selectivity)
• Join cost:
NESTED LOOP JOIN cost = cost of accessing outer table + (cardinality of outer table
* cost of accessing inner table )
SORT MERGE JOIN cost = (cost of accessing outer table + outer sort cost) + (cost
of accessing inner table + inner sort cost)
HASH JOIN cost = (cost of accessing outer table) + (cost of building hash table) +
(cost of accessing inner table )
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19. • Cost Calculation formula:
Cost= (NBLKS/ k)+1 (if _table_scan_cost_plus_one = true)
Case Name Estimate Cost Original Cost
Case 1 171/10.40+1=17.44 18
Case 2 1495/10.40+1=144.75 145
Case 3 12151/10.40+1=1169.37 1170
Case 4 12151/6.59+1=1844.85 1846
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23. Cost = blevel +( leaf_blocks * effective index selectivity +
clustering_factor * effective table selectivity)
Case Name Estimate Cost Original Cost
Case 1 1+(190*1)=191 191
Case 2 1+1=2 2
Case 3 1+(264*1+91723* 0.000027)=267.48 268
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26. Cost = blevel + ( leaf_blocks * effective index selectivity/k)
Case Name Estimate Cost Original Cost
Case 1 1+(190*1/10.40)=19.27 20
Case 2 1+(190*1/6.59)=29.83 30
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30. • NewDensity = [ (BktCnt - PopBktCnt) / BktCnt ] /
(NDV - PopValCnt)
• NewDensity=((254-12)/254)/(717-6)=0.001340022
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31. Cost = blevel + (leaf_blocks * effective index selectivity
+ clustering_factor * effective table selectivity)
Case Name Estimate Cost Original Cost
Case 1 1+(190*0.000285+84136*0.000285) 26
=25.03
Case 2 1+190*0.000285=1.05 2
Case 3 1+190*0.480315=92.25 93
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34. Cost= blevel + min cost of index +(clustering_factor * effective table
selectivity)
Case Name Estimate Cost Original Cost
Case 1 0+1=1 1
Case 2 0+5*1+12000*0.000417=10 10
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37. Cost = blevel + ( leaf_blocks * effective index selectivity *
max(NUM_DISTINCT(skipped columns)))+ clustering_factor *
effective table selectivity
Notice: need set _optimizer_skip_scan_enabled = true
Case Name Estimate Cost Original Cost
Case 1 1+(264*0.000027*36572+91723*0.0 268
00027)=264.16
Case 2 1+(110*0.000040*24724+39949*0.0 113
00040)=111.38
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40. Cost=cost of accessing outer table + (cardinality of outer table *
cost of accessing inner table )
Nest Loop Join :
Cost(T1)= 1+(21* 0.001721+9153*0.001721)=16.78
Cost(T2)=1+1
Cost(case1)=17+17*2=51 not equal 34 why?
Adjusted Cost(case1)=17+17*1=34
Cost(case2)=1+(21*0.00142+9153*0.00142)+14.02*1=28.04
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43. Cost = (cost of accessing outer table) + (cost of building hash table) + (cost of
accessing inner table )
Cost=( NBLKS/ k )+1 (if _table_scan_cost_plus_one = true)
Cost =blevel +( leaf_blocks * effective index selectivity + clustering_factor *
effective table selectivity)
Cost(hash build)=(Probe passes+1)*(large table block/k)+(small table/k)
Hash Join :
Cost(T1)=1+ 171/10.40=17.44
Cost(T2)=1+ 1495/10.40=144.75
Cost(hash build)=2*(1495/16.06)+171/16.06= 196.8
Cost(case1)=18+145+ 197= 360 != 391 (k=13.8)
Cost(T1)=1+ 171/10.40=17.44
Cost (T2)=1+ 191+ 1463=1655
Cost(case 2)=1655+18= 1673
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45. cost = (cost of accessing outer table + outer sort cost) + (cost of accessing
inner table + inner sort cost)
Cost =blevel +( leaf_blocks * effective index selectivity +
clustering_factor * effective table selectivity)
Sort Merge Join :
Cost(T1)= 1+(21* 0.001721+9153*0.001721)=16.78
Cost(T2)=1+(191*1)+1*1463 =192+1463=1655
Cost(sort outer)=120
Cost(sort inner)=0 (unique index)
Cost(case1)=1655+120+0+17=1792
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46. • What’s effect from “OPTIMIZER_INDEX_COST_ADJ”?
• What’s effect from parallelism degree?
• What’s effect from “Optimizer_Index_Caching”?
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48. • Cost = IO Cost+ (#CPUCost/cpuspeed)/sreadtim/1000) OR
(BLOCKS/MRBC)*(mreadtim/sreadtim)+((#CPUCost/cpuspeed)/s
readtim/1000)
• MRBC- number of multi block reads
• sreadtim is set to ioseektim + db_block_size/iotrfrspeed
• mreadtim is set to ioseektim + db_file_multiblock_read_count *
db_block_size/iotftspeed
• Notice: you can get these data from aux_stats$ table
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51. Cost=(BLOCKS/MRBC)*(mreadtim/sreadtim)+((#CPUCost/cpuspee
d)/sreadtim/1000) sreadtim is set to ioseektim +
db_block_size/iotrfrspeed
Sreadtim=18+8192/21110=18.39
Mreadtim=18+16*8192/21110=24.21
Case Name CPU Cost Estimate Cost Original Cost
Case 1 round(3117766/(1414 0+ceil(ceil(171/16)*24. 16
*1000*18.38)=0 21/18.39)+1+0=16
Case 2 round(28085703/(141 0+ceil(ceil(1495/16)*2 126
4*1000*18.38)=1 4.21/18.39)+1+1=126
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54. Cost = IO Cost+ (#CPUCost/cpuspeed)/sreadtim/1000)
Sreadtim=18+8192/21110=18.39
Mreadtim=18+16*8192/21110=24.21
Case Name CPU Cost Estimate Cost Original Cost
Case 1 round(19717195/141 191*1+1=192 192
4/18.39/1000)=1
Case 2 round(14443/1414/18 1+1+0=2 2
.39/1000) =0
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60. Cost= IO Cost+ (#CPUCost/cpuspeed)/sreadtim/1000)
Sreadtim=18+8192/21110=18.39
Mreadtim=18+16*8192/21110=24.21
Case Name CPU Cost Estimate Cost Original Cost
Case 1 round(202809 1+ceil((190*0.000288+ 27
/(1414*18.39*1000))= 84136*0.000288))+0=
0 26
Case 2 round(9169130 1+ceil(190*0.464567)+ 90
/(1414*18.39*1000))= 0=90
0
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63. Cost = IO Cost+ (#CPUCost/cpuspeed)/sreadtim/1000)
Case Name CPU Cost Estimate Cost Original Cost
Case 1 round(8171/1414/18. 0+1 1
39/1000) =0
Case 2 round(108772 0+5+5=10 9
/1414/18.39/1000)=0
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66. Cost= IO Cost+ (#CPUCost/cpuspeed)/sreadtim/1000)
Sreadtim=18+8192/21110=18.39
Mreadtim=18+16*8192/21110=24.21
Case Name CPU Cost Estimate Cost Original Cost
Case 1 round(1909776 1+(264*0.000027*365 268
/(1414*18.39*1000))= 72+91723*0.000027)+
0 0=264
Case 2 round(805543 1+((110*0.000040*247 113
/(1414*18.39*1000))= 24)+39949*0.000040)
0 +0=112
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69. Cost=cost of accessing outer table + (cardinality of outer table * cost of
accessing inner table )
Nest Loop Join :
Cost(CPU) =round(3418106/1414/18.39/1000)=0
Cost(T1)= ((171/16)*24.21/18.39)+1 = 15.07
Cost(T2)=1+0
Cost(case1)= 15.07 + 15.07 *1= 30.14
Cost(T1-CPU) =round(106010/1414/18.39/1000)=0
Cost(T2-CPU) =round(234970/1414/18.39/1000)=0
Cost(T1) =1+21*0.00142+9153*0.00142=14.02
Cost(case2)=14.02+14.02*1=28.04
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72. Cost = (cost of accessing outer table) + (cost of building hash table) + (cost of accessing inner table )
Cost=(BLOCKS/MRBC)*(mreadtim/sreadtim)+((#CPUCost/cpuspeed)/sreadtim/1000)+1
Cost(hash build)=(Probe passes+1)*(large table block/MRBC)+(small table/MRBC)
Hash Join :
Cost(T1-CPU)=round(3117766/(1414*18.39*1000))=0
Cost(T2-CPU)=round((28085703/(1414*18.39*1000)))=1
Cost(T1)=1+ (171/16)*24.21/18.39+0= 15.07, Cost(T2)=1+ (1495/16)*24.21/18.39+1=125
Cost(build Hash CPU)= 178640101/(1414*18.39*1000)= 6.87
Cost(case1)=15.07+125+ 6.87 = 146.94
Cost(T4-CPU)=round((30493428/(1414*18.39*1000)))=1
Cost(T2)=1+ (1495/16)*24.21/18.39+1=125 , Cost(T4)=1+ (1575/16)*24.21/18.39+1=131.59
Cost(build Hash CPU)= 128949682/(1414*18.39*1000)= 4.96
Cost(hash build)=2*(1575/16)+ (1495/16)=290
Cost(case2)=125+132+5+290= 552
© 2011 Cisco and/or its affiliates. All rights reserved. Cisco Confidential 72
73. • Wolfgang Breitling, A LOOK UNDER THE HOOD OF CBO: THE
10053 EVENT
• Wolfgang Breitling, The Effects of optimizer_index_cost_adj and
optimizer_index_caching on Access Plans
• Jonathan Lewis , Cost-Based Oracle Fundamentals
• Alberto Dell'Era, New Density calculation in 11g
• Chris Antognini ,CBO – A Configuration Roadmap
• Juliandyke,http://www.juliandyke.com/Diagnostics/Events/EventR
eference.html
• http://mikixiyou.iteye.com/blog/1709321
• http://www.oaktable.net/category/tags/system-statistics
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74. Thank you.
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Editor's Notes Bitmap index cost Join Selectivity = 1/max( ndvA, ndvB)* cardA * cardB C1 like :B1 { 0.05 | C1.Density }:Depending on whether the undocumented init.ora parameter _LIKE_WITH_BIND_AS_EQUALITY is false (the default) or true. LVLS BLEVEL The height of the index b-tree #LB LEAF_BLOCKS The number of leaf blocks #DK DISTINCT_KEYS The number of distinct keys of the index LB/K AVG_LEAF_BLOCKS_PER_KEY The average number of leaf blocks per key DB/K AVG_DATA_BLOCKS_PER_KEY The average number of data blocks per key CLUF CLUSTERING_FACTOR The clustering factor of the index http://blog.csdn.net/tianlesoftware/article/details/4668723Height-Balanced Histograms: We have a range of 11—running from 1 to 12. The right-hand edge hits zero at month_no = 23(high value + 11); the left-hand edge hits zero at month_no = -10 (low value – 11).This will be bad news to some people. If you have sequence, or time-based, values in acommonly queried column and haven’t been keeping the statistics up to date, then queriesthat use an equality on that column will have been using a flat line to give you the right answeras time passes. Now, those same queries are going to give you cardinalities that keep droppingas time passes—until suddenly, the cardinality gets so low that plans may change dramatically.Cases 19 and 20 (ranges outside the recorded low/high range): The optimizer detectsthat the query falls outside the known range, and seems to return a selectivity, hencecardinality that would be correct for column = constant. (There is a nasty boundary case,though, that appears from 9i onwards when every row holds the same value.) Using prorated density: 0.001420 of col #2 as selectvity of out-of-range/non-existent value pred Don’t get overly exited over the 0 cost of a unique index lookup in an NL join. It would appear to make NL joins with this kind of index access, e.g. a fully qualified primary key join predicate, cost free. (Prob+1)*round(1495/10.40)+round(171/10.40)=2*144 We Can open another topic for hash/SM/NL Don’t get overly exited over the 0 cost of a unique index lookup in an NL join. It would appear to make NL joins with this kind of index access, e.g. a fully qualified primary key join predicate, cost free. Full Table Scan: BLOCKS(table) / MBRC / parallelismdegree+ 1Index UniqueScan: (BLEVEL(index) + 1) * OPTIMIZER_INDEX_COST_ADJ / 100Index Unique Scan + Table Access by Index ROWID: (BLEVEL(index) + 2) * OPTIMIZER_INDEX_COST_ADJ / 100Index Full Scan: (BLEVEL(index) + LEAF_BLOCKS(index)) * OPTIMIZER_INDEX_COST_ADJ / 100Index Fast Full Scan: BLEVEL(index) + LEAF_BLOCKS(index) / MBRC / parallelismdegree+ 1Index Range Scan: (BLEVEL(index) + LEAF_BLOCKS(index) * FF1) / OPTIMIZER_INDEX_COST_ADJ * 100Index Range Scan+ Table Access by Index ROWID: (BLEVEL(index) + LEAF_BLOCKS(index) * FF1 + CLUSTERING_FACTOR(index) * FF2) * OPTIMIZER_INDEX_COST_ADJ / 100Index SkipScan: max(NUM_DISTINCT(skipped_columns)) * (BLEVEL(index) + LEAF_BLOCKS(index) * FF1) * OPTIMIZER_INDEX_COST_ADJ / 100Index SkipScan+ Table Access byIndex ROWID: max(NUM_DISTINCT(skipped_columns)) * (BLEVEL(index) + LEAF_BLOCKS(index) * FF1 + CLUSTERING_FACTOR(index) * FF2) * OPTIMIZER_INDEX_COST_ADJ / 100 exec DBMS_STATS.GATHER_SYSTEM_STATS('NOWORKLOAD');execute dbms_stats.gather_system_stats('start');execute dbms_stats.gather_system_stats('stop'); http://www.oaktable.net/category/tags/system-statistics If _table_scan_cost_plus_one=true, need +1 We Can open another topic for hash/SM/NL We Can open another topic for hash/SM/NL We Can open another topic for hash/SM/NL We Can open another topic for hash/SM/NL We Can open another topic for hash/SM/NL Using prorated density: 0.001420 of col #2 as selectvity of out-of-range/non-existent value pred Don’t get overly exited over the 0 cost of a unique index lookup in an NL join. It would appear to make NL joins with this kind of index access, e.g. a fully qualified primary key join predicate, cost free. (Prob+1)*round(1495/10.40)+round(171/10.40)=2*144+ (if _table_scan_cost_plus_one = true)
