1. Introduction to
Oracle Optimizer
Heribertus Bramundito

2. Agenda
 Our Environment
 Heap Table
 Histogram
 Oracle Optimizer
 Cost
 Selectivity & Cardinality
 Clustering Factor
 Access Method
 Partitioning
 Join Method
 Sub-query
 Hint

3. Our Environment
Heap Table
 This is default table when we issue the CREATE TABLE
statement
 Data is stored in random fashion, no specific sort of order
(best fit algorithm)
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4. Our Environment
Heap Table (result from table access)
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5. Our Environment
Heap Table (result from index access)
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6. Our Environment
IOT Table (a comparison)
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7. Our Environment
Histogram
 Collection of information about data distribution in
specific column
 Oracle maintains 2 types of histogram: frequency and
height-balanced
 Oracle use histogram as additional information when
deciding whether to use index scan or table scan
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8. Our Environment
Histogram (column without histogram)
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9. Our Environment
Histogram (create histogram)
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10. Our Environment
Histogram (column with histogram)
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11. Agenda
 Our Environment
 Heap Table
 Histogram
 Oracle Optimizer
 Cost
 Selectivity & Cardinality
 Clustering Factor
 Access Method
 Partitioning
 Join Method
 Sub-query
 Hint

12. Cost
 Jonathan Lewis: “The cost represents the optimizer‟s best estimate of the
time it will take to execute the statement”
 A result of the calculation performed by optimizer
 Few conditions that make CBO produces wrong result”
 No statistics on the underlying objects or statistics are obsolete
 Performance characteristics of hardware or current workloads are not known
 Bug
 From Oracle Performance Tuning Guide and Reference
Cost = (#SRds * sreadtim + #MRds * mreadtim +
#CPUCycles / cpuspeed) / sreadtim
#SRds: number of single data block reads
#MRds: number of multi data block reads
#CPUCycle: number of CPU cycles
sreadtim: single block read time
mreadtim: multi block read time
cpuspeed: CPU cycles per second
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13. Cost (the calculation)
 #SRds = blevel + #leaf_block * idx_sel + clustering_factor * tbl_sel (index




scan)
#MRds = #tbl_blocks under HWM / mbrc (full table/ index scan)
sreadtim = ioseektim + block_size * iotfrspeed (SREADTIM)
mreadtim = ioseektim + mbrc * block_size * iotfrspeed (MREADTIM)
mbrc = db_file_multiblock_read_count (MBRC)
 Going back to slide #4 (let‟s try to calculate cost of table
scan)
 Cost = (24 / 16) * (10 + 16 * 8192 / 4092) / (10 + 8192 / 4092) = 1.5 * 42 /
12 = 5.25
 Slide #5 (index scan only)
 Cost = 0 + ceil(1 * 0.0588) = ceil(0.0588) = 1
 Slide #10 (index scan with access to the table)
 Cost = 0 + 1 + ceil((4 / 17) * 20) = 1 + ceil(4.705) = 1 + 5 = 6
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14. Selectivity & Cardinality
 Selectivity is what fraction of row the predicate is supposed to fetch/ return
Selectivity = 1 / num_distinct (no histogram)
Selectivity = density (histogram)
 Cardinality is total number of row the predicate is supposed to return
Cardinality = num_rows * density
 Going back to slide #4

Cardinality = num_rows = 20
 Slide #5

Selectivity = (number of bucket with data / number of total bucket) = 17 / 17 = 1

Cardinality = selectivity * num_rows = 1 * 20 = 20
 Slide #10

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Selectivity = 4 / 17 = 0.235

Cardinality = 0.235 * 20 = 4.7

15. Clustering Factor
 Represents the degree to which data is randomly
distributed through a table
 Number of blocks <= clustering factor <= number of rows
 Index has better selectivity if clustering factor is close to
number of data block, means Oracle can do multi block
read on the table for several index‟s key
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16. Clustering Factor (block_id from rowid)
 Going back to NORMAL_HASH table example, due to
the anomaly configuration of pctfree and pctused, every
block contains single row only
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17. Access Method
 There are 2 access methods: table and index
access
 Index access can be: Fast Full Scan, Full Scan,
Unique Scan, Range Scan, Range Scan
(MIN/MAX) and Skip Scan
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18. Access Method
Full Table Scan
 Oracle is reading all rows from the table
 Not suitable for OLTP system with high volume of
transaction and usually only access small fraction of data
 Suitable for DSS system with batch reporting query
 Not good for Nested Loop (NL) for the outer table (huge
table)
 Usually we see it in Hash Join (HJ)
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19. Access Method
Index Fast Full Scan
 Oracle is reading all rows from the index to get the
result (doesn‟t required table access since the index
contains all columns required to resolve the query)
 To be able to use Index FFS, the column should be
defined as NOT NULL or at least one column in a
composite index is NOT NULL, the reason is that
NULL values are not included in the index creation,
so when the column is defined as NOT NULL Oracle
knows that all values are available in the index
 Index FFS will be available as an option if we put “IS
NOT NULL” in the WHERE clause explicitly
 Cost will be only for accessing the index
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20. Access Method
Index Fast Full Scan (forced by hint)
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21. Access Method
Index Fast Full Scan (cost calculation)
 If we remove the HINT, we will have Index Full Scan
 Cost for Index Fast Full Scan
 Cost = (8 / 16) * (10 + 16 * 8192 / 4092) / (10 + 8192 / 4092) = 0.5 * 32 / 12 =
ceil(1.333) = 2
 Cost for Index Full Scan
 Cost = 0 + ceil(1 * 1 / 14) = ceil(0.0714) = 1
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22. Access Method
Index Fast Full Scan (building the example)
 Another figure from index with more leaf block
(another anomaly configuration in the pctfree of
the index)
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23. Access Method
Index Fast Full Scan (the result)
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24. Access Method
Index Full Scan
 Oracle is reading all rows from the index, and
may be accessing these rows in the underlying
table
Without table
access
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25. Access Method
Index Full Scan (with table access)
Unique index
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26. Access Method
Index Unique Scan
 Oracle is reading 0 or 1 rows from the index, only on
unique index
 Equality operator in the predicate (=), ay be seen in AND,
OR, IS NULL operator
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27. Access Method
Index Unique Scan (the result)
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28. Access Method
Index Range Scan
 Oracle is reading 0 or more contiguous rows
from the index
 Non unique index with range operator in the
predicate (>, <, >=, <=)
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29. Access Method
Index Range Scan (MIN/MAX)
 Oracle is identifying 0 or more contiguous rows
in the index, but is reading only one (the first or
the last) in order to satisfy a MIN or MAX
aggregate function
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30. Access Method
Index Skip Scan
 Oracle is reading 0 or more rows from different
parts of the index (composite index), and may be
accessing these rows in the underlying table
 Skip Scan will be happened when we access a
composite index with second column in the
index‟s order. It will not be happened for the third
column, forth, etc.
 It will works only if first column in the index has
low cardinality (few distinct value) otherwise full
table scan will be better in most of the case
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31. Access Method
Index Skip Scan (building the example)
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32. Access Method
Index Skip Scan (the result)
First index‟s
column with low
cardinality
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33. Access Method
Index Skip Scan (a comparison)
First index‟s
column with high
cardinality
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34. Partitioning
 There are some consideration when we are
working with partition table. One of its is
regarding access path. We introduce partitioning
on the table usually to reduce the number of
rows which will affected by any query, since we
know that not all of those rows are being used in
the query.
 There are 4 kinds of access method for
partitioned table: Partition Range Single,
Partition Range Iterator, Partition Range All and
Partition Range Sub-query
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35. Partitioning (building the example)
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36. Partitioning
Partition Range Single
 Exactly only single partition of the table involves
in the query. Access path on this partition
depends on the query, can be Table Scan or any
Index Scan
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37. Partitioning
Partition Range Iterator
 We will see this kind of access path whenever
we have several partitions in the query
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38. Partitioning
Partition Range All
 In this kind of access method, all partitions in the table
will be scanned. This is a bad example of table design 
(create a partition table without taking any benefit of it)
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39. Partitioning
Partition Range Sub-query (building an example)
 This method is new in 10g. If the partitioned table
is bigger compare to the other join table and the
expected number of the records (result) is
significantly less, Oracle will perform dynamic
partition pruning using sub-query
 The partitioned table will be having 200,000
blocks and the other join only 200 blocks
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40. Partitioning
Partition Range Sub-query (the result)
Only 7 rows compare
to 1000 rows from
partitioned table
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41. Partitioning
Partition Range Sub-query (a comparison)
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42. Join Method
 There are 3 join methods: Nested Loop (NL),
Hash Join (HJ) and Sort Merge Join (SM)
 Most of the time we see only „standard‟ join
between 2 tables, but in rare case we will see
Anti-Join and Semi-Join variation for all above 3
methods. Anti-Join will be appear when we are
working with NOT IN clause while Semi-Join will
be appear when we are working with EXISTS
clause
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43. Join Method
Nested Loop
 The Nested means an iteration. Pseudo-code for
this kind of join will be like below:
for x in (select [col] from outer_table) loop
for y in (select [col] from inner_table where outer_table.join_col =
inner_table.join_col) loop
return the rows from outer and inner table
end loop;
end loop;
 Suitable for small “size” for the outer (driving)
table. For the inner table, it should be accessed
using index scan
 Starting from 9i, Oracle introduces new „table
prefetching‟ method which will reduce logical I/O
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44. Join Method
Nested Loop (building the example)
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45. Join Method
Nested Loop (table prefetching method)
note down the
logical I/O
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46. Join Method
Nested Loop (legacy method)
recreate with
UNIQUE index
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47. Join Method
Nested Loop (the result)
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48. Join Method
Hash Join
 In this method, first Oracle will choose 1 dataset
(build table – this is outer table in Nested Loop), and
then create hash table in memory using generated
hash-key from join column. Once completed, second
table (probe table – this is inner table in Nested
Loop) will be scanned using the same hash function
(probing the hash table)
 Applicable for join with equality operator (=)
 There are 3 level of effectiveness: optimal, one-pass
and multi-pass. Optimal when the size of tables is
matched with hash_area_size. One-pass or Multipass when the tables is not enough to be hash-ed in
the memory (requires disk operation)
 Event 10104 for tracing Hash Join operation
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49. Join Method
Hash Join (cont.)
 Check hash_area_size and
workarea_size_policy database parameter
 Check v$sysstat for relevant system statistics
SELECT name, value, case when sum(value) over() = 0 then 0
else round(value*100/sum(value) over(),2) end as pct
FROM v$sysstat
WHERE name LIKE 'workarea executions%'
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50. Join Method
Hash Join (components)
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51. Join Method
Hash Join (build the example)
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52. Join Method
Hash Join (the result – optimal)
workarea_size_policy = AUTO
test on SMALL table
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53. Join Method
Hash Join (the result – optimal, part 2)
workarea_size_policy = AUTO
test on BIG table
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54. Join Method
Hash Join (with index scan on the tables)
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55. Join Method
Hash Join (event 10104)
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56. Join Method
Sort Merge
 There are 2 operation in this method: sort and merge. So




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it is application for any query which requires sorting (on
the join column): Order By clause, Group By clause, Set
operation, Distinct operator, Analytical function, Index
creation, Connect By query and etc
Similar to Hash Join, there are 3 level of effectiveness for
sorting operation: optimal, one-pass and multi-pass.
Optimal when the size sort_area_size is enough to
handle sort operation. One-pass or Multi-pass when
Oracle requires disk operation for the sorting
Event 10032 for tracing sort operation and 10033 for
tracing sort I/O operation
Check sort_area_size and workarea_size_policy
database parameter
Check v$sysstat for relevant system statistics and
v$tempstat for sorting statistics

57. Join Method
Sort Merge (cont.)
 Merging part can be one of the following
possibilities:
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58. Join Method
Sort Merge (build the example)
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59. Join Method
Sort Merge (sorting only example)
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60. Join Method
Sort Merge (sorting only example – cont.)
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61. Join Method
Sort Merge (the example)
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62. Join Method
Sort Merge (Merge Join Cartesian)
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63. Join Method
Sort Merge (event 10032)
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64. Sub-query
 There 2 main types of sub-query: Nested Sub-
query and Correlated Sub-query
 Nested sub-query when the sub-query (inner
query) need to be completed first and then the
result will be passed to the main query
 Correlated sub-query when the main query
should be executed first in order to execute the
inner query
 In some cases we can rewrite sub-query into join
form for performance improvement
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65. Sub-query (building the example)
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66. Sub-query
Nested
 The select statement against “sub_q” is executed
first and the outputs will be used by main query
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67. Sub-query
Correlated
 We can see from Predicate Information,
“sub_q” is executed for every value from
“main_q”
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68. Sub-query
Correlated – rewrite into join
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69. Sub-query
Correlated – comparing the statistics
Check
logical I/O
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70. Hint
 Some of famous Oracle hints
 PARALLEL, PARALLEL_INDEX
 FULL
 INDEX, INDEX_SS, INDEX_FFS
 LEADING
 ORDERED
 DRIVING_SITE
 USE_NL, USE_HASH, USE_MERGE
 APPEND
 USE_CONCAT
 Other hints
 MERGE_AJ, HASH_AJ
 MERGE_SJ, HASH_SJ
 UNNEST, NO_UNNEST
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71. References
 Jonathan Lewis, Cost-Based Oracle
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
Fundamentals
Thomas Kyte, Expert Oracle Database
Architecture – 9i and 10g Programming
Techniques and Solutions
http://www.orafaq.com/tuningguide/
http://oraclerandolf.blogspot.com/2011/10/paralleldowngrade.html
http://asktom.oracle.com/pls/asktom/f?p=100:1:0::
NO::
http://jonathanlewis.wordpress.com/