% mysqladmin -u admin -p extended | grep -i qcache

Then I type in the password. Well, I grew tired of typing in the extra options, plus the password. Turns out, MySQL will look for the configuration file .my.cnf in your home directory after it looks in /etc/my.cnf (it looks in a few other places as well). So I put this in my ~/.my.cnf:

[client]
user=admin
password=secret

And now I can simply run:

% mysqladmin extended | grep -i qcache

and it works right away.  Note that the password is stored in the clear.

1

$sql = "select event_id from events where event_dt >= curdate()";

Because MySQL knows that this query run today is not the same query when it is run tomorrow. There are other SQL functions such as rand() and unix_timestamp() that will bypass the query cache. These are listed here.

So I avoid these functions when possible by calculating the value in PHP. For example, I’d rewrite the above query as:

1
2

$date = date('Y-m-d');
$sql = "select event_id from events where event_dt >= '$date'";

But turning this option on and allowing .htaccess files may be a performance hit. More specifically, enabling the AllowOverride option in Apache is a performance hit. The Apache docs sums up the problem best:

“Wherever in your URL-space you allow overrides (typically .htaccess files) Apache will attempt to open .htaccess for each filename component. For example,

1 2 3 4

DocumentRoot /www/htdocs <Directory /> AllowOverride all </Directory>

and a request is made for the URI /index.html. Then Apache will attempt to open /.htaccess, /www/.htaccess, and /www/htdocs/.htaccess.”

So I disabled all .htaccess files in production, and inserted each file’s individual mod_rewrite rules into the main Apache config file. After a quick Apache Bench run, one project looked around 3% faster. Note that there are a few other useful optimizations on that page.

So instead of this:

$num = $db->getone("select count(*) from events where event_id = 15");
 
if ($num > 0)
{
   $sql = "update events set name = 'New name' where event_id = 15";
}
else
{
   $sql = "insert into events (event_id, name) values (null, 'New name')";
}

you can do something like this:

$id = (empty($_POST['id'])) ? null : $_POST['id'];
$sql = "insert into events (event_id, name) values ($id, 'New name') on duplicate key update name = 'New name'";

Neat, eh?

In case you’re wondering what the difference is between ON DUPLICATE KEY UPDATE and a REPLACE query, a REPLACE fires a DELETE followed by an INSERT query, as opposed to a real UPDATE.

So, instead of something like this:

1
2
3
4
5
6
7
8
9

$exclude = array(1, 4, 6, 8);
 
for ($i = 0, $size = count($data); $i < $size; $i++)
{
   if (in_array($data[$i]['id'], $exclude)
   {
      // do something
   }
}

do something like:

1
2
3
4
5
6
7
8
9
10
11
12

$exclude[1] = true;
$exclude[4] = true;
$exclude[6] = true;
$exclude[8] = true;
 
for ($i, $size = count($data); $i < $size; $i++)
{
   if (isset($exclude[$data[$i]['id']]))
   {
      // do something
   }
}

So does this make a difference? Let’s write a little benchmark script.

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21

#!/usr/bin/php
<?php
$haystack = array();
for ($i = 0; $i < 1000; $i++)
{
    $haystack[] = rand(0, 1000);
}
 
$needles = array();
for ($i = 0; $i < 1000; $i++)
{
    $needles[] = rand(0, 1000);
}
 
for ($i = 0; $i < 1000; $i++)
{
    foreach ($needles as $needle)
    {
        if (in_array($needle, $haystack));
    }
}

We fill two arrays with 1000 random integers. One is the haystack – what we will search through. The other is the list of needles – we want to search for each one. For each needle, we look for it in the haystack. Then, we repeat this 1000 times.

Executing this, the script takes around 37 seconds:

% time ./bench.php
 
real    0m37.400s
user    0m37.282s
sys     0m0.068s

Now, let’s change the last for() loop to this:

15
16
17
18
19
20
21
22

for ($i = 0; $i < 1000; $i++)
{
    $tmp = array_flip($haystack);
    foreach ($needles as $needle)
    {
        if (isset($tmp[$needle]));
    }
}

The new output:

% time ./bench.php
 
real    0m0.778s
user    0m0.764s
sys     0m0.008s

Execution time drops from around 37 seconds to 0.7 seconds.