<?php
require_once('itemCache.inc.php');
/**
* The code here is a rather effective demonstration of how inneffective
* the itemcache object is for random access to a set of N values which
* is significantly larger than the cache size M; at best the hit
* ratio will be M/N
* however this may still provide performance benefits using a
* overflow + underflow handler since the resultant writes will
* be batched. See also
* http://dev.mysql.com/doc/refman/5.0/en/insert-speed.html
*
* As M->N, the hit ratio will -> 1.0
*
* On the other hand if there is some implicit grouping in the
* input set of key values, then there is likely to be a big
* performance benefit.
*/
// ratio is the number of gets / number of adds
$tests=array(
array('size'=>50, 'minkey'=>0, 'maxkey'=>200, 'iters'=>250000, 'rwratio'=>0.5),
array('size'=>200, 'minkey'=>0, 'maxkey'=>2000, 'iters'=>250000, 'rwratio'=>0.3),
array('size'=>300, 'minkey'=>0, 'maxkey'=>1000, 'iters'=>250000, 'rwratio'=>0.1),
array('size'=>300, 'minkey'=>0, 'maxkey'=>400, 'iters'=>250000, 'rwratio'=>0.1)
);
foreach ($tests as $t) {
$start=microtime(true);
$c=new itemCache($t['size']);
for ($i=0; $i<$t['iters']; $i++) {
$key=rand($t['minkey'], $t['maxkey']);
if (rand(0,100)<$t['rwratio']) {
$val=rand($t['minkey'], $t['maxkey']);
$c->add($key, $val);
} else {
@$c->get($key);
}
}
$complete=microtime(true);
$r=$c->stats();
$result=array_merge($t
, $r
, array('hitratio' => $r['hits']/($r['hits']+$r['misses'])
, 'mem' => memory_get_usage()
, 'elapsed' => ($complete-$start)
)
);
print_r($result);
}
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