我实际上是在寻求建议，而不是解决方案。
我提供了一项服务，用于比较远程数据库中的数据，并在必要时插入，更新或删除本地数据。 源数据库中有超过50k个条目，并且本地内存使用速度慢使脚本变得冗长。
以下是该服务的一部分：
function compare( $uosLocal, $uosDistant ) {
$idsLocal = array_keys($uosLocal);
$idsDistant = array_keys($uosDistant);
$toInsert = array_diff( $idsDistant, $idsLocal );
$toDisable = array_diff( $idsLocal, $idsDistant );
$this->insert( array_map( function ($uoid) use ($uosDistant) {
return ($uosDistant[$uoid]);
}, $toInsert ) );
$this->delete( array_map( function ($uoid) use ($uosLocal) {
return ($uosLocal[$uoid]);
}, $toDisable ) );
$uosLocal = $this->getLocal();
$uosDistant = $this->getDistant();
$idsLocal = array_keys($uosLocal);
$idsDistant = array_keys($uosDistant);
$toUpdate = array_intersect( $idsDistant, $idsLocal );
$this->update( $toUpdate, $uosDistant, $uosLocal );
}
function insert( $array_uos ) {
$em = $this->doctrine->getManager();
$count = 0;
$total = count($array_uos);
$precision = 2;
$suffixes = array('', 'k', 'M', 'G', 'T');
if ($total > 0)
$this->output->writeln(" $total to insert : ");
foreach ($array_uos as $simple_uo) {
$uo = new UO();
$uo
->setName($simple_uo['NAME'])
->setId($simple_uo['ID'])
;
$em->persist($uo);
unset($uo);
$count++;
if ($count % 100 === 0) {
$base = log(memory_get_usage(), 1024);
$em->flush();
$this->output->writeln('['. (new \DateTime())->format('H:i:s') .'] ' . floor( $count / $total * 100 *100) /100 . "% ($count / $total) (memory : " . round(pow(1024, $base - floor($base)), $precision) . $suffixes[floor($base)] . ") ");
}
}
$em->flush();
$this->output->writeln( " $count was inserted " );
}
这是导致大量内存使用的insert方法。
查看日志：
Starting data extraction from referentiel : 56215 to insert :
[09:49:55] 0.17% (100 / 56215) (memory : 55.37M)
[09:49:55] 0.35% (200 / 56215) (memory : 56.43M)
[09:49:55] 0.53% (300 / 56215) (memory : 56.98M)
[09:49:56] 0.71% (400 / 56215) (memory : 57.47M)
[09:49:56] 0.88% (500 / 56215) (memory : 57.95M)
[09:49:57] 1.06% (600 / 56215) (memory : 58.45M)
[09:49:57] 1.24% (700 / 56215) (memory : 59.11M)
[09:49:57] 1.42% (800 / 56215) (memory : 59.59M)
[09:49:58] 1.6% (900 / 56215) (memory : 60.07M)
[09:49:58] 1.77% (1000 / 56215) (memory : 60.56M)
[09:49:59] 1.95% (1100 / 56215) (memory : 61.09M)
[09:50:00] 2.13% (1200 / 56215) (memory : 61.59M)
[09:50:00] 2.31% (1300 / 56215) (memory : 62.09M)
[09:50:01] 2.49% (1400 / 56215) (memory : 62.83M)
[09:50:01] 2.66% (1500 / 56215) (memory : 63.32M)
[09:50:02] 2.84% (1600 / 56215) (memory : 63.82M)
[09:50:03] 3.02% (1700 / 56215) (memory : 64.32M)
[09:50:03] 3.2% (1800 / 56215) (memory : 64.81M)
[09:50:04] 3.37% (1900 / 56215) (memory : 65.3M)
[09:50:05] 3.55% (2000 / 56215) (memory : 65.79M)
[09:50:05] 3.73% (2100 / 56215) (memory : 66.31M)
[09:50:06] 3.91% (2200 / 56215) (memory : 66.84M)
[09:50:07] 4.09% (2300 / 56215) (memory : 67.33M)
[09:50:08] 4.26% (2400 / 56215) (memory : 67.82M)
[09:50:09] 4.44% (2500 / 56215) (memory : 68.31M)
[09:50:10] 4.62% (2600 / 56215) (memory : 68.81M)
[09:50:10] 4.8% (2700 / 56215) (memory : 69.8M)
[09:50:11] 4.98% (2800 / 56215) (memory : 70.28M)
[09:50:12] 5.15% (2900 / 56215) (memory : 70.78M)
[09:50:13] 5.33% (3000 / 56215) (memory : 71.27M)
[09:50:14] 5.51% (3100 / 56215) (memory : 71.77M)
[09:50:15] 5.69% (3200 / 56215) (memory : 72.26M)
[09:50:16] 5.87% (3300 / 56215) (memory : 72.75M)
[09:50:17] 6.04% (3400 / 56215) (memory : 73.24M)
[09:50:18] 6.22% (3500 / 56215) (memory : 73.74M)
[09:50:20] 6.4% (3600 / 56215) (memory : 74.23M)
[09:50:21] 6.58% (3700 / 56215) (memory : 74.72M)
[09:50:22] 6.75% (3800 / 56215) (memory : 75.21M)
[09:50:23] 6.93% (3900 / 56215) (memory : 75.7M)
[09:50:24] 7.11% (4000 / 56215) (memory : 76.2M)
[09:50:26] 7.29% (4100 / 56215) (memory : 76.73M)
[09:50:27] 7.47% (4200 / 56215) (memory : 77.3M)
[09:50:28] 7.64% (4300 / 56215) (memory : 77.79M)
这是正常的，可以改善吗？
非常感谢！
答案 0 :(得分：0)
正如评论中所述，我在$em->clear()之后添加$em->flush()并且有效