Drupal Meetup Group Toronto

1. <Insert Picture Here>
Optimizing MySQL
Morgan Tocker, MySQL Community Manager
http://www.tocker.ca/

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3. Options
•
•
•
•
Upgrade Hardware and/or MySQL Version
Optimize Configuration
Optimize Queries
Optimize Schema

4. Commentary
• There are some specific cases where upgrades can
make individual queries faster (i.e. subqueries). When I
like this optimization the most, is to increase“capacity”.
Lots of multi-core, multi-disk enhancements in 5.5 / 5.6.
• MySQL 5.6 comes with a much more optimized
configuration. There are now only 3-4 settings that
need to change.
• Optimizing queries is my favourite method :) There can
be some big wins here.
• Optimizing schema relates to query optimization.
Sometimes you have to change schema to support
certain queries, but it always starts with the queries.

5. Optimizing Queries
• Allows you to focus on queries that damage user
experiences rather than just slow.
• Best method is to install a profiler.
• MySQL also supports slow query logging +
Performance Schema (5.6+).

6. # Continent Asia + population > 5M!
mysql> EXPLAIN SELECT * FROM Country WHERE continent='Asia'
AND population > 5000000G!
*************************** 1. row ***************************!
id: 1!
select_type: SIMPLE!
table: Country!
type: ALL!
possible_keys: NULL!
key: NULL!
key_len: NULL!
ref: NULL!
rows: 267!
Extra: Using where!
1 row in set (0.00 sec)

7. mysql> ALTER TABLE Country ADD INDEX p (population);!
Query OK, 0 rows affected (0.02 sec)!
Records: 0 Duplicates: 0 Warnings: 0!
!
mysql> EXPLAIN SELECT * FROM Country WHERE continent='Asia'
AND population > 5000000G!
*************************** 1. row ***************************!
id: 1!
select_type: SIMPLE!
table: Country!
type: ALL!
possible_keys: p!
key: NULL!
key_len: NULL!
ref: NULL!
rows: 264!
Extra: Using where!
1 row in set (0.01 sec)

8. # 50 Million!
mysql> EXPLAIN SELECT * FROM Country WHERE continent='Asia'
AND population > 50000000G!
*************************** 1. row ***************************!
id: 1!
select_type: SIMPLE!
table: Country!
type: range!
possible_keys: p!
key: p!
key_len: 4!
ref: NULL!
rows: 24!
Extra: Using index condition; Using where!
1 row in set (0.00 sec)

9. mysql> ALTER TABLE Country ADD INDEX c (continent);!
Query OK, 0 rows affected (0.02 sec)!
Records: 0 Duplicates: 0 Warnings: 0!
!
mysql> EXPLAIN SELECT * FROM Country WHERE continent='Asia' !
AND population > 50000000G!
*************************** 1. row ***************************!
id: 1!
select_type: SIMPLE!
table: Country!
type: ref!
possible_keys: p,c!
key: c!
key_len: 1!
ref: const!
rows: 51!
Extra: Using index condition; Using where!
1 row in set (0.00 sec)

10. mysql> ALTER TABLE Country ADD INDEX pc (population,continent);!
Query OK, 0 rows affected (0.02 sec)!
Records: 0 Duplicates: 0 Warnings: 0!
!
mysql> EXPLAIN SELECT * FROM Country WHERE continent='Asia' !
AND population > 50000000G!
*************************** 1. row ***************************!
id: 1!
select_type: SIMPLE!
table: Country!
type: ref!
possible_keys: p,c,pc!
key: c!
key_len: 1!
ref: const!
rows: 51!
Extra: Using index condition; Using where!
1 row in set (0.00 sec)

11. mysql> ALTER TABLE Country ADD INDEX cp (continent,population);!
Query OK, 0 rows affected (0.01 sec)!
Records: 0 Duplicates: 0 Warnings: 0!
!
mysql> EXPLAIN SELECT * FROM Country WHERE continent='Asia' !
AND population > 50000000G!
*************************** 1. row ***************************!
id: 1!
select_type: SIMPLE!
table: Country!
type: range!
possible_keys: p,c,pc,cp!
key: cp!
key_len: 5!
ref: NULL!
rows: 11!
Extra: Using index condition!
1 row in set (0.00 sec)

12. Tips
• Think of where you can use indexes to eliminate
rows - that’s the column you typically index.
• Read: http://dev.mysql.com/doc/refman/5.6/en/
explain.html
• Composite indexes somewhat an advanced topic:
• Useful when a single column does not eliminate
enough work.
• “Ranges to the right”