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Top tips for Oracle SQL
tuning
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Guy Harrison
Senior Software Architect,
Quest Software
Top 10 Oracle SQL tuning tips
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Design and develop with performance in mind
Establish a tuning environment
Index wisely
Reduce parsing
Take advantage of Cost Based Optimizer
Avoid accidental table scans
Optimize necessary table scans
Optimize joins
Use array processing
Consider PL/SQL for “tricky” SQL
Hint #1: Design and develop with
performance in mind
 Explicitly identify performance targets
 Focus on critical transactions
– Test the SQL for these transactions against simulations of production
data
 Measure performance as early as possible
 Consider prototyping critical portions of the applications
 Consider de-normalization and other performance by design
features early on
Hint #2: Establish a tuning and
development environment
 A significant portion of SQL that performs poorly in production
was originally crafted against empty or nearly empty tables.
 Make sure you establish a reasonable sub-set of production
data that is used during development and tuning of SQL
 Make sure your developers understand EXPLAIN PLAN and
tkprof, or equip them with commercial tuning tools.
Understanding SQL tuning tools
 The foundation tools for SQL tuning are:
– The EXPLAIN PLAN command
– The SQL Trace facility
– The tkprof trace file formatter
 Effective SQL tuning requires either familiarity with
these tools or the use of commercial alternatives such
as SQLab
EXPLAIN PLAN
 The EXPLAIN PLAN reveals the execution plan for an SQL
statement.
 The execution plan reveals the exact sequence of steps that
the Oracle optimizer has chosen to employ to process the
SQL.
 The execution plan is stored in an Oracle table called the “plan
table”
 Suitably formatted queries can be used to extract the execution
plan from the plan table.
A simple EXPLAIN PLAN
SQL> EXPLAIN PLAN FOR select count(*) from sales
where product_id=1;
Explained.
SQL> SELECT RTRIM (LPAD (' ', 2 * LEVEL) || RTRIM (operation)
||' '||RTRIM (options) || ' ' || object_name) query_plan
2
FROM plan_table
3
CONNECT BY PRIOR id = parent_id
4*
START WITH id = 0
QUERY_PLAN
-------------------------------------------SELECT STATEMENT
SORT AGGREGATE
TABLE ACCESS FULL SALES
Interpreting EXPLAIN PLAN
 The more heavily indented an access path is, the
earlier it is executed.
 If two steps are indented at the same level, the
uppermost statement is executed first.
 Some access paths are “joined” – such as an index
access that is followed by a table lookup.
A more complex EXPLAIN PLAN
SELECT STATEMENT
VIEW SYS_DBA_SEGS
UNION-ALL
NESTED LOOPS
NESTED LOOPS
NESTED LOOPS
NESTED LOOPS
NESTED LOOPS
VIEW SYS_OBJECTS
UNION-ALL
TABLE ACCESS FULL TAB$
TABLE ACCESS FULL TABPART$
TABLE ACCESS FULL CLU$
TABLE ACCESS FULL IND$
TABLE ACCESS FULL INDPART$
TABLE ACCESS FULL LOB$
TABLE ACCESS FULL TABSUBPART$
TABLE ACCESS FULL INDSUBPART$
TABLE ACCESS FULL LOBFRAG$
TABLE ACCESS BY INDEX ROWID OBJ$
INDEX UNIQUE SCAN I_OBJ1
SQL_TRACE and tkprof
 ALTER SESSION SET SQL_TRACE TRUE causes a trace of
SQL execution to be generated.
 The TKPROF utility formats the resulting output.
 Tkprof output contains breakdown of execution statistics,
execution plan and rows returned for each step. These stats
are not available from any other source.
 Tkprof is the most powerful tool, but requires a significant
learning curve.
Tkprof output
count2
------ -----Parsea
1d
Executeb
1e
Fetchc
20j
------ -----total
22
cpu3 elapsed4
disk5
query6 current7
rows8
------ -------- ------- -------- -------- -----0.02
0.01
0
0
0
0
0.00
0.00
0
0
0
0
141.10
141.65
1237 1450011
386332
99i
------ -------- ------- -------- -------- -----141.12
141.66
1237k 1450011f 386332g
99h
Rowsl
Execution Planm
------- --------------------------------------------------0 SELECT STATEMENT
GOAL: CHOOSE
99
FILTER
96681
TABLE ACCESS
GOAL: ANALYZED (FULL) OF 'CUSTOMERS'
96582
TABLE ACCESS
GOAL: ANALYZED (FULL) OF 'EMPLOYEES'
Using SQLab
 Because EXPLAIN PLAN and tkprof are unwieldy and hard to
interpret, third party tools that automate the process and
provide expert advice improve SQL tuning efficiency.
 The Quest SQLab product:
– Identifies SQL your database that could benefit from tuning
– Provides a sophisticated tuning environment to examine, compare and
evaluate execution plans.
– Incorporates an expert system to advise on indexing and SQL
statement changes
SQLab SQL tuning lab
– Display execution plan in a variety of intuitive ways
– Provide easy access to statistics and other useful data
– Model changes to SQL and immediately see the results
SQLab Expert Advice
– SQLab provides specific advice on how to tune an SQL
statement
SQLab SQL trace integration
– SQLab can also retrieve the execution statistics that are otherwise only
available through tkprof
Hint #3: Index wisely
 Index to support selective WHERE clauses and join conditions
 Use concatenated indexes where appropriate
 Consider overindexing to avoid table lookups
 Consider advanced indexing options
– Hash Clusters
– Bit mapped indexes
– Index only tables
Effect of adding columns to a
concatenated index
– Novice SQL programmers often are satisfied if the
execution plan shows an index
– Make sure the index has all the columns required
700
Surname index only
40
Merge 3 indexes
20
Index on Surname+f irstname
Index on
Surname+f irstname+DOB
6
Index on
Surname+f irstname+dob+phoneo
4
0
100
200
300
400
Logical IO
500
600
700
800
Bit-map indexes
– Contrary to widespread belief, can be effective when there
are many distinct column values
– Not suitable for OLTP however
100
Elapsed time (s)
10
1
0.1
0.01
1
10
100
1,000
10,000
100,000
1,000,000
Distinct values
Bitmap index
B*-Tree index
Full table scan
Hint #4: Reduce parsing
 Use bind variables
– Bind variables are key to application scalability
– If necessary in 8.1.6+, set cursor CURSOR_SHARING to
FORCE
 Reuse cursors in your application code
– How to do this depends on your development language
 Use a cursor cache
– Setting SESSION_CACHED_CURSORS (to 20 or so) can
help applications that are not re-using cursors
Hint #5: Take advantage of the Cost
Based Optimizer
 The older rule based optimizer is inferior in almost
every respect to the modern cost based optimizer
 Using the cost based optimizer effectively involves:
– Regular collection of table statistics using the ANALYZE or
DBMS_STATS command
– Understand hints and how they can be used to influence
SQL statement execution
– Choose the appropriate optimizer mode: FIRST_ROWS is
best for OLTP applications; ALL_ROWS suits reporting and
OLAP jobs
Hint #6: Avoid accidental tablescans
 Tablescans that occur unintentionally are a major
source of poorly performing SQL. Causes include:
– Missing Index
– Using “!=“, “<>” or NOT
• Use inclusive range conditions or IN lists
– Looking for values that are NULL
• Use NOT NULL values with a default value
– Using functions on indexed columns
• Use “functional” indexes in Oracle8i
Hint #7: Optimize necessary table
scans
 There are many occasions where a table scan is the only option.
If so:
– Consider parallel query option
– Try to reduce size of the table
• Adjust PCTFREE and PCTUSED
• Relocate infrequently used long columns or BLOBs
• Rebuild when necessary to reduce the high water mark
– Improve the caching of the table
• Use the CACHE hint or table property
• Implement KEEP and RECYCLE pools
– Partition the table (if you really seek a large subset of data)
– Consider the fast full index scan
Fast full index scan performance
– Use when you must read every row, but not every column
– Counting the rows in a table is a perfect example
19.83
Index range scan (RULE)
17.76
Full index scan
12.53
Full table scan
5.23
Parallel table scan
4.94
fast full index
2.44
Parallel fast full index
0
5
10
Elapsed time (s)
15
20
Hint #8: Optimize joins
 Pick the best join method
– Nested loops joins are best for indexed joins of subsets
– Hash joins are usually the best choice for “big” joins
 Pick the best join order
– Pick the best “driving” table
– Eliminate rows as early as possible in the join order
 Optimize “special” joins when appropriate
–
–
–
–
–
STAR joins for data-warehousing applications
STAR_TRANSFORMATION if you have bitmap indexes
ANTI-JOIN methods for NOT IN sub-queries
SEMI-JOIN methods for EXISTS sub-queries
Properly index CONNECT BY hierarchical queries
Oracle 8 semi-joins
 Optimizes queries using EXISTS where there is no
supporting index
select *
No index on employees
from customers c
where exists
(select 1 from employees e
where e.surname=c.contact_surname
and e.firstname=c.contact_firstname
and e.date_of_birth=c.date_of_birth)
Oracle 8 semi-joins
 Without the semi-join or supporting index, queries like
the one on the preceding slide will perform very badly.
 Oracle will perform a tablescan of the inner table for
each row retrieved by the outer table
 If customers has 100,000 rows, and employees 800
rows then 80 MILLION rows will be processed!
 In Oracle7, you should create the index or use an INbased subquery
 In Oracle8, the semi-join facility allows the query to be
resolved by a sort-merge or hash join.
To Use semi-joins
 Set ALWAYS_SEMI_JOIN=HASH or MERGE in
INIT.ORA, OR
 Use a MERGE_SJ or HASH_SJ hint in the subquery
of the SQL statement
SELECT *
FROM customers c
WHERE exists
(select /*+merge_sj*/ 1
from employees e
where ….)
Oracle8 semi-joins
 The performance improvements are impressive (note
the logarithmic scale)
1,343.19
EXISTS no semi-join or indexes
31.01
EXISTS no semi-join but with index
6.83
EXISTS - merge semi-join
6.69
IN-based subquery
1
10
100
Elapsed time (logarithmic scale)
1,000
10,000
Star Join improvements
 A STAR join involves a large “FACT” table being
joined to a number of smaller “dimension” tables
Star Join improvements
 The Oracle7 Star join algorithm works well when there is a
concatenated index on all the FACT table columns
 But when there are a large number of dimensions, creating
concatenated indexes for all possible queries is impossible.
 Oracle8’s “Star transformation” involves re-wording the query
so that it can be supported by combinations of bitmap indexes.
 Since bitmap indexes can be efficiently combined, a single
bitmap index on each column can support all possible queries.
To enable the star transformation
 Create bitmap indexes on each of the FACT table
columns which are used in star queries
 Make sure that
STAR_TRANSFORMATION_ENABLED is TRUE,
either by changing init.ora or using an ALTER
SESSION statement.
 Use the STAR_TRANSFORMATION hint if necessary.
Drawback of Star transformation
 Bitmap indexes reduce concurrency (row-level locking
may break down).
 But remember that large number of distinct column
values may not matter
Star transformation performance
 When there is no suitable concatenated index, the
Star transformation results in a significant
improvement
0.35
No suitable concatenated index
9.94
Star_transformation
Star
0.24
Concatenated index
0.01
0
1
2
3
4
5
Elapsed time (s)
6
7
8
9
10
Hint #9: Use ARRAY processing
– Retrieve or insert rows in batches, rather than one at a time.
– Methods of doing this are language specific
60
50
Elapsed time
40
30
20
10
0
0
20
40
60
80
100 120 140
160 180 200 220 240
Array size
260 280 300
Hint #10: Consider PL/SQL for
“tricky” SQL
 With SQL you specify the data you want, not how to
get it. Sometime you need to specifically dictate your
retrieval algorithms.
 For example:
–
–
–
–
–
Getting the second highest value
Doing lookups on a low-high lookup table
Correlated updates
SQL with multiple complex correlated subqueries
SQL that seems to hard to optimize unless it is broken into
multiple queries linked in PL/SQL
Oracle8i PL/SQL Improvements
– Array processing
– NOCOPY
– Temporary tables
– The profiler
– Dynamic SQL
Bonus hint: When your SQL is
tuned, look to your Oracle
configuration
 When SQL is inefficient there is limited benefit in investing in
Oracle server or operating system tuning.
 However, once SQL is tuned, the limiting factor for
performance will be Oracle and operating system
configuration.
 In particular, check for internal Oracle contention that
typically shows up as latch contention or unusual wait
conditions (buffer busy, free buffer, etc)
 Third party tools – such as Quest’s Spotlight on Oracle
product – can be invaluable
www.quest.com