This document provides tips for optimizing PHP and MySQL applications. It discusses avoiding excess variables, using caching, preventing queries in loops, selecting only needed columns, using count(col_name) over count(*), limiting to 1 row, indexing columns commonly used in joins and filters, and using the MySQL profiling tool to analyze query performance. Indexes are recommended on columns searched frequently, and indexes should match column types for more efficient joins.

1. PHP
+
MySQL
Optimization

2. Introduction
• The report includes project-related (EU) queries, tables
or databases example.
• We can learn simple php/mysql optimization.
• Know the main idea of using index in a table.

3. Let’s start from simple
cases

4. Let’s start from simple
cases
Avoid excess variables
function
isSomething()
{
$is_something
=
false;
if
($some_condition_happens)
{
$is_something
=
true;
}
return
$is_something;
}

5. Let’s start from simple
cases
Use cache
(eg. APC, memcache)

6. Let’s start from simple
cases
Avoid queries inside a loop.
$player_ids = array(1, 2, 3, 4, 5, 6, 7, 8);
foreach ($player_ids as $id) {
$players_infos[] = $db->query(“SELECT * FROM player WHERE id = ?”,
array($id));
}

7. Let’s start from simple
cases
Select only needed columns.

8. Let’s start from simple
cases
count(*) vs count(col_name)

9. Let’s start from simple
cases
limit 1 when retrieving a
unique row.

10. Index to remember

11. Index to remember
Without an index, MySQL must begin
with the first row and then read
through the entire table to find the
relevant rows.

12. Index to remember
If there is a choice between multiple
indexes, MySQL normally uses the
index that finds the smallest number
of rows

13. Index to remember
To retrieve rows from other tables
when performing joins, MySQL can
use indexes on columns more
efficiently if they are declared as the
same type and size.
(Comparison of dissimilar columns may prevent use of
indexes if values cannot be compared directly without
conversion.)

14. Index to remember
“Index has significant cost. So you should not
create index everywhere.”
- http://lab.klab.org/
mysql-bootcamp/key.html

15. Examples

16. Examples
Scenario : Imagine you have a table that will
store millions of records (eg. item_history)
and you don’t have indexes.

17. Examples
The table structure :
id
int(10) unsigned
player_id
unsigned
item_master_id
unsigned
type
enum('INC','DEC')
reason
int(10)
int(10)

18. Examples
The problem : When you try to select data
from a table without index
See how many rows were checked after the search?

19. Examples
The solution : We are going to add index for the player_id
column
ALTER TABLE `item_history` ADD INDEX ( `player_id` )
See the advantage of adding an index?
The search took 1 row search only.

20. Examples
Upon looking on the table structure
which column/s can be used as index
when you want to retrieved a player’s
item history?

21. Exercise
Table Name : unit_history
Description : Tracks player’s record when he/she gained, evolved,
etc.. a unit.
Table structure :
id
player_id
unit_master_id
type
‘ITEM’)
created
int(10)
int(10)
int(10)
enum(‘INC’, ‘DEC’, ‘EVOLVED’, ‘EXP’,
timestamp

22. Exercise
The Scenario :
List player ids who gained and evolved the unit
id 10
The Question :
What are the possible index we might need in
order to retrieve the data faster.

23. Using index in joins
• columns that you will use as the join
•
•
condition ( ON a.id = b.id ) should be
indexed.
LEFT JOIN will use indexed column from left
( a.id )
RIGHT JOIN will use indexed column from
right ( b.id )

24. Did you know?
That we MySQL has a built-in profiling tool?
SET PROFILING = 1;
SELECT COUNT(*) FROM table_name WHERE id = 1;
SHOW PROFILE FOR QUERY 1;
SHOW PROFILES;