The document discusses MySQL optimization and indexing principles. It provides examples of queries with and without indexes and uses the EXPLAIN statement to analyze query performance. Indexing types for MyISAM and InnoDB storage engines are explained. Considerations for when indexes can and cannot be used are also covered. The document is presented by someone who works with MySQL and offers their contact information for questions.

1. MySQL Optimization
Ha noi php day 2009
vanchinh@gmail.com
19/12/2009 Ha Noi - 2009 1

2. Content
 Introduction
 Example
 Indexing Principles
 Considerations
 Explain
 General discussion
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3. Introduction
Ha noi php day 2009
vanchinh@gmail.com
19/12/2009 Ha Noi - 2009 3

4. Who am i
 I working in NaisCorp (socbay.com)
 I’ve been using MySQL personally for
2 years and professionally for over 1 years.
 Contact info:
 Personal: vanchinh@gmail.com
 work: chinhnv@socbay.com
 Web: http://ffx.socbay.com
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5. Example
Ha noi php day 2009
vanchinh@gmail.com
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6. Example
 SELECT * FROM news WHERE cate_id =1
ORDER BY createdate DESC LIMIT 0,10;
 SELECT * FROM news WHERE cate_id =1 or
cate_id=2 ORDER BY createdate DESC
LIMIT 0,10;
 SELECT * FROM news WHERE id <
12345678 ORDER BY createdate DESC LIMIT
0, 10
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7. Example
 Query Parsing and Optimizing
Query
Parse
Thread 1
Thread 2
Thread 3 Optimize
Thread 4
MyISAM Key Buffer
Engine API
MyISAM
…
Thread 5
Storage
Execute (ha_myisam)
(fetch) *.MYD, *.MYI
Thread n
(update) InnoDB Key Buffer
InnoDB
(ha_innodb) ibdataN
Results
Group By
Having
Order By
Group By and Order By can be done with indexes instead.
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8. Example
 Query Parsing and Optimizing
 All parsing and optimizing steps are the same for all
storage engines
 All ORDER BY / GROUP BY steps are the same
 The only difference for a given storage engine is in
actually fetching the rows
 Some types of indexes don’t exist on some table
types: e.g. FULLTEXT and SPATIAL indexes don’t
exist for InnoDB
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9. Example
 Explain SELECT * FROM news WHERE
cate_id =1 ORDER BY createdate DESC
LIMIT 0,10;
 Run time: 0.9724s
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10. Example
WHERE cate_id =1 Order By createdate Limit 0,10
2.000.000 2.000.000
10
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11. Indexing Principles
Ha noi php day 2009
vanchinh@gmail.com
19/12/2009 Ha Noi - 2009 11

12. Optimization – Indexing Principles
 Indexing principles
 Single-column index
 Multi-column index
 Table news
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13. Optimization – Indexing Principles
Single index
Table news
Multi index
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14. Optimization – Indexing Principles
 Basic Index Principles
 Only one index can be used, per table, per query
 Index definitions must match your real-world use
 You don’t have to do anything special to maintain indexes
after creation
 Creating/Dropping Indexes
 CREATE INDEX cate ON news (cate_id)
 DROP INDEX cate ON news;
 ALTER TABLE news ADD INDEX cate
(cate_id);
 ALTER TABLE news DROP INDEX cate;
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15. Optimization – Indexing Principles
 CREATE INDEX cate_date ON news (cate_id,
createdate)
 Explain SELECT * FROM news WHERE
cate_id =1 ORDER BY createdate DESC
LIMIT 0,10
 Run time: 0.0007 s
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16. Optimization – Indexing Principles
WHERE cate_id =1 Order By createdate Limit 0,10
2.000.000 2.000.000
10
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17. Optimization – Indexing Principles
 Explain SELECT * FROM news WHERE
cate_id =1 or cate_id=2 ORDER BY createdate
DESC LIMIT 0,10
 Run time: 1.0067S
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18. Optimization – Indexing Principles
Cate_id=1 Order by Limit 0,10
1.000.000
Cate_id=2 3.000.000 10
2.000.000
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19. Optimization – Indexing Principles
 SELECT news.* FROM (
(SELECT id FROM news WHERE cate_id=1
ORDER BY createdate LIMIT 0,10)
UNION
(SELECT id FROM news WHERE cate_id=2
ORDER BY createdate LIMIT 0,10)
) as temp, news where news.id=temp.id ORDER
BY createdate DESC LIMIT 0,10;
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20. Optimization – Indexing Principles
 Run time: 0.00928s
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21. Optimization – Indexing Principles

Cate_id=1 Order by Limit
10
20 10
Cate_id=2
10
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22. Optimization – Indexing Principles
 MyISAM indexes
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23. Optimization – Indexing Principles
 MyISAM indexes
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24. Optimization – Indexing Principles
 MyISAM indexes
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25. Optimization – Indexing Principles
 InnoDB indexes
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26. Optimization – Indexing Principles
 MyISAM vs InnoDB
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27. Optimization – Considerations
 When can indexes be used?
 Simple PRIMARY KEY lookups
 PRIMARY KEY(i) :: WHERE i = 5
 Secondary KEY (index) lookups
 INDEX(i) :: WHERE i = 7
 Prefix lookups
 INDEX(s) :: WHERE s LIKE “foo%”
 INDEX(i, j) :: WHERE i = 5
 Joins – index either table
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28. Optimization – Considerations
 When can’t indexes be used?
 LIKE that starts with a wildcard
 INDEX(s) :: WHERE s LIKE “%foo”
 Bitwise operations
 INDEX(i) :: WHERE i & 4
 Non-prefix lookups
 INDEX(i, j) :: WHERE j = 5
 Using a function containing column ref
 INDEX(s) :: WHERE foo(s) = “FOO”
 INDEX(dt) :: WHERE unix_timestamp(dt) = 1
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29. Optimization – Explain
 Explain SELECT * FROM news WHERE
cate_id = 218103808 ORDER BY id DESC
LIMIT 0,10;
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30. Optimization – Explain
 Fields in EXPLAIN
 id – (4.1+) The ID number of this SELECT
 select_type – (4.1+) The type of this SELECT
 table – The name of the table in question
 type – The type of reading done on this table (system,
const, eq_ref, ref, ref_or_null, index_merge,
unique_subquery, index_subquery, range,
index, ALL)
 possible_keys – The keys which were examined for
possible use
 key – The key that was finally chosen for use
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31. Optimization – Explain
 Fields in EXPLAIN
 key_len – The length of the part of the key that
was finally chosen for use
 ref – Row reference; What is used to look up
row values from the index
 rows – The approximate number of rows which
must be examined from this table using the chosen
optimizations
 Extra – Any extra comments the server wanted
to add about this optimization path (free form)
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32. General Discussion
Got any questions for me?
Ha noi php day 2009
vanchinh@gmail.com
19/12/2009 Ha Noi - 2009 32