PHP和phpSpider：如何应对大规模数据爬取的性能问题？

<?php
$urls = array(
    'https://example.com/page1',
    'https://example.com/page2',
    'https://example.com/page3',
    // 更多待爬取的URL
);

$threads = array();

// 创建线程
foreach ($urls as $url) {
    $thread = new MyThread($url);
    $threads[] = $thread;
    $thread->start();
}

// 等待线程执行完毕
foreach ($threads as $thread) {
    $thread->join();
}

class MyThread extends Thread {
    private $url;

    public function __construct($url) {
        $this->url = $url;
    }

    public function run() {
        // 在这里写爬取逻辑
        // 使用$this->url作为爬取的URL
    }
}
?>

<?php
require 'vendor/autoload.php'; // 请确保已安装Guzzle库

use GuzzleHttpClient;
use GuzzleHttpPool;
use GuzzleHttpPsr7Request;

$urls = array(
    'https://example.com/page1',
    'https://example.com/page2',
    'https://example.com/page3',
    // 更多待爬取的URL
);

$client = new Client();

$requests = function ($urls) {
    foreach ($urls as $url) {
        yield new Request('GET', $url);
    }
};

$pool = new Pool($client, $requests($urls), [
    'concurrency' => 10, // 并发请求数量
    'fulfilled' => function ($response, $index) {
        // 在这里处理请求成功的响应
        // $response为响应对象
    },
    'rejected' => function ($reason, $index) {
        // 在这里处理请求失败的原因
        // $reason为失败原因
    },
]);

$promise = $pool->promise();
$promise->wait();
?>

<?php
$urls = array(
    'https://example.com/page1',
    'https://example.com/page2',
    'https://example.com/page3',
    // 更多待爬取的URL
);

$memcached = new Memcached();
$memcached->addServer('localhost', 11211);

foreach ($urls as $url) {
    $data = $memcached->get($url);

    if ($data === false) {
        // 如果缓存中没有数据，则进行爬取并存入缓存
        // 爬取逻辑略

        $data = $result; // 假设$result为爬取得到的数据
        $memcached->set($url, $data);
    }

    // 使用$data进行后续数据处理
}
?>