phpcurlmulti技巧_运用Rolling优化PHP curl_multi

本文将磋商两种详细的实现方法, 并对不同的方法做大略的性能比拟.

经典的cURL实现机制在网上很随意马虎找到, 比如参考PHP在线手册的如下实现办法:

function classic_curl($urls, $delay) { $queue = curl_multi_init(); $map = array(); foreach ($urls as $url) { // create cURL resources $ch = curl_init(); // set URL and other appropriate options curl_setopt($ch, CURLOPT_URL, $url); curl_setopt($ch, CURLOPT_TIMEOUT, 1); curl_setopt($ch, CURLOPT_RETURNTRANSFER, 1); curl_setopt($ch, CURLOPT_HEADER, 0); curl_setopt($ch, CURLOPT_NOSIGNAL, true); // add handle curl_multi_add_handle($queue, $ch); $map[$url] = $ch; } $active = null; // execute the handles do { $mrc = curl_multi_exec($queue, $active); } while ($mrc == CURLM_CALL_MULTI_PERFORM); while ($active > 0 && $mrc == CURLM_OK) { if (curl_multi_select($queue, 0.5) != -1) { do { $mrc = curl_multi_exec($queue, $active); } while ($mrc == CURLM_CALL_MULTI_PERFORM); } } $responses = array(); foreach ($map as $url=>$ch) { $responses[$url] = callback(curl_multi_getcontent($ch), $delay); curl_multi_remove_handle($queue, $ch); curl_close($ch); } curl_multi_close($queue); return $responses;}

首先将所有的URL压入并发行列步队, 然后实行并发过程, 等待所有要求吸收完之后进行数据的解析等后续处理. 在实际的处理过程中, 受网络传输的影响, 部分URL的内容会优先于其他URL返回, 但是经典cURL并发必须等待最慢的那个URL返回之后才开始处理, 等待也就意味着CPU的空闲和摧残浪费蹂躏. 如果URL行列步队很短, 这种空闲和摧残浪费蹂躏还处在可接管的范围, 但如果行列步队很长, 这种等待和摧残浪费蹂躏将变得不可接管.

仔细剖析不难创造经典cURL并发回存在优化的空间, 优化的办法时当某个URL要求完毕之后尽可能快的去处理它, 边处理边等待其他的URL返回, 而不是等待那个最慢的接口返回之后才开始处理等事情, 从而避免CPU的空闲和摧残浪费蹂躏. 闲话不多说, 下面贴上详细的实现:

function rolling_curl($urls, $delay) { $queue = curl_multi_init(); $map = array(); foreach ($urls as $url) { $ch = curl_init(); curl_setopt($ch, CURLOPT_URL, $url); curl_setopt($ch, CURLOPT_TIMEOUT, 1); curl_setopt($ch, CURLOPT_RETURNTRANSFER, 1); curl_setopt($ch, CURLOPT_HEADER, 0); curl_setopt($ch, CURLOPT_NOSIGNAL, true); curl_multi_add_handle($queue, $ch); $map[(string) $ch] = $url; } $responses = array(); do { while (($code = curl_multi_exec($queue, $active)) == CURLM_CALL_MULTI_PERFORM) ; if ($code != CURLM_OK) { break; } // a request was just completed -- find out which one while ($done = curl_multi_info_read($queue)) { // get the info and content returned on the request $info = curl_getinfo($done['handle']); $error = curl_error($done['handle']); $results = callback(curl_multi_getcontent($done['handle']), $delay); $responses[$map[(string) $done['handle']]] = compact('info', 'error', 'results'); // remove the curl handle that just completed curl_multi_remove_handle($queue, $done['handle']); curl_close($done['handle']); } // Block for data in / output; error handling is done by curl_multi_exec if ($active > 0) { curl_multi_select($queue, 0.5); } } while ($active); curl_multi_close($queue); return $responses;}3. 两种并发实现的性能比拟

改进前后的性能比拟试验在LINUX主机上进行, 测试时利用的并发行列步队如下:

简要解释下实验设计的原则和性能测试结果的格式: 为担保结果的可靠, 每组实验重复20次, 在单次实验中, 给定相同的接口URL凑集, 分别丈量Classic(指经典的并发机制)和Rolling(指改进后的并发机制)两种并发机制的耗时(秒为单位), 耗时短者胜出(Winner), 并打算节省的韶光(Excellence, 秒为单位)以及性能提升比例(Excel. %). 为了只管即便贴近真实的要求而又保持实验的大略, 在对返回结果的处理上只是做了大略的正则表达式匹配, 而没有进行其他繁芜的操作. 其余, 为了确定结果处理回调对性能比拟测试结果的影响, 可以利用usleep仿照现实中比较卖力的数据处理逻辑(如提取, 分词, 写入文件或数据库等).

性能测试中用到的回调函数为:

function callback($data, $delay) { preg_match_all('/<h3>(.+)<\/h3>/iU', $data, $matches); usleep($delay); return compact('data', 'matches');}

数据处理回调无延迟时: Rolling Curl略优, 但性能提升效果不明显.

------------------------------------------------------------------------------------------------Delay: 0 micro seconds, equals to 0 milli seconds------------------------------------------------------------------------------------------------Counter Classic Rolling Winner Excellence Excel. %------------------------------------------------------------------------------------------------1 0.1193 0.0390 Rolling 0.0803 67.31%2 0.0556 0.0477 Rolling 0.0079 14.21%3 0.0461 0.0588 Classic -0.0127 -21.6%4 0.0464 0.0385 Rolling 0.0079 17.03%5 0.0534 0.0448 Rolling 0.0086 16.1%6 0.0540 0.0714 Classic -0.0174 -24.37%7 0.0386 0.0416 Classic -0.0030 -7.21%8 0.0357 0.0398 Classic -0.0041 -10.3%9 0.0437 0.0442 Classic -0.0005 -1.13%10 0.0319 0.0348 Classic -0.0029 -8.33%11 0.0529 0.0430 Rolling 0.0099 18.71%12 0.0503 0.0581 Classic -0.0078 -13.43%13 0.0344 0.0225 Rolling 0.0119 34.59%14 0.0397 0.0643 Classic -0.0246 -38.26%15 0.0368 0.0489 Classic -0.0121 -24.74%16 0.0502 0.0394 Rolling 0.0108 21.51%17 0.0592 0.0383 Rolling 0.0209 35.3%18 0.0302 0.0285 Rolling 0.0017 5.63%19 0.0248 0.0553 Classic -0.0305 -55.15%20 0.0137 0.0131 Rolling 0.0006 4.38%------------------------------------------------------------------------------------------------Average 0.0458 0.0436 Rolling 0.0022 4.8%------------------------------------------------------------------------------------------------Summary: Classic wins 10 times, while Rolling wins 10 times

数据处理回调延迟5毫秒: Rolling Curl完胜, 性能提升40%旁边.

------------------------------------------------------------------------------------------------Delay: 5000 micro seconds, equals to 5 milli seconds------------------------------------------------------------------------------------------------Counter Classic Rolling Winner Excellence Excel. %------------------------------------------------------------------------------------------------1 0.0658 0.0352 Rolling 0.0306 46.5%2 0.0728 0.0367 Rolling 0.0361 49.59%3 0.0732 0.0387 Rolling 0.0345 47.13%4 0.0783 0.0347 Rolling 0.0436 55.68%5 0.0658 0.0286 Rolling 0.0372 56.53%6 0.0687 0.0362 Rolling 0.0325 47.31%7 0.0787 0.0337 Rolling 0.0450 57.18%8 0.0676 0.0391 Rolling 0.0285 42.16%9 0.0668 0.0351 Rolling 0.0317 47.46%10 0.0603 0.0317 Rolling 0.0286 47.43%11 0.0714 0.0350 Rolling 0.0364 50.98%12 0.0627 0.0215 Rolling 0.0412 65.71%13 0.0617 0.0401 Rolling 0.0216 35.01%14 0.0721 0.0226 Rolling 0.0495 68.65%15 0.0701 0.0428 Rolling 0.0273 38.94%16 0.0674 0.0352 Rolling 0.0322 47.77%17 0.0452 0.0425 Rolling 0.0027 5.97%18 0.0596 0.0366 Rolling 0.0230 38.59%19 0.0679 0.0480 Rolling 0.0199 29.31%20 0.0657 0.0338 Rolling 0.0319 48.55%------------------------------------------------------------------------------------------------Average 0.0671 0.0354 Rolling 0.0317 47.24%------------------------------------------------------------------------------------------------Summary: Classic wins 0 times, while Rolling wins 20 times

通过上面的性能比拟, 在处理URL行列步队并发的运用处景中Rolling cURL该当是更佳选择, 并发量非常大(1000+)时, 可以掌握并发行列步队的最大长度, 比如20, 每当1个URL返回并处理完毕之后立即加入1个尚未要求的URL到行列步队中, 这样写出来的代码会更加健壮, 不至于并发数太大而卡去世或崩溃. 详细的实现请参考: https://code.google.com/p/rolling-curl/