在实际项目或者自己编写小工具(比如新闻聚合,商品价格监控,比价)的过程中, 通常需要从第3方网站或者API接口获取数据, 在需要处理1个URL队列时, 为了提高性能, 可以采用cURL提供的curl_multi_*族函数实现简单的并发.
本文将探讨两种具体的实现方法, 并对不同的方法做简单的性能对比.
经典的cURL实现机制在网上很容易找到, 比如参考PHP在线手册的如下实现方式:
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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压入并发队列, 然后执行并发过程, 等待所有请求接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的空闲和浪费. 如果URL队列很短, 这种空闲和浪费还处在可接受的范围, 但如果队列很长, 这种等待和浪费将变得不可接受.
仔细分析不难发现经典cURL并发还存在优化的空间, 优化的方式时当某个URL请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工作, 从而避免CPU的空闲和浪费. 闲话不多说, 下面贴上具体的实现:
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|
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
;
}
|
改进前后的性能对比试验在LINUX主机上进行, 测试时使用的并发队列如下
简要说明下实验设计的原则和性能测试结果的格式: 为保证结果的可靠, 每组实验重复20次, 在单次实验中, 给定相同的接口URL集合, 分别测量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), 并计算节省的时间(Excellence, 秒为单位)以及性能提升比例(Excel. %). 为了尽量贴近真实的请求而又保持实验的简单, 在对返回结果的处理上只是做了简单的正则表达式匹配, 而没有进行其他复杂的操作. 另外, 为了确定结果处理回调对性能对比测试结果的影响, 可以使用usleep模拟现实中比较负责的数据处理逻辑(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:
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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%左右.
------------------------------------------------------------------------------------------------ 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
通过上面的性能对比, 在处理URL队列并发的应用场景中Rolling cURL应该是更加的选择, 并发量非常大(1000+)时, 可以控制并发队列的最大长度, 比如20, 每当1个URL返回并处理完毕之后立即加入1个尚未请求的URL到队列中, 这样写出来的代码会更加健壮, 不至于并发数太大而卡死或崩溃. 详细的实现请参考:http://code.google.com/p/rolling-curl/