Background
When using Memcache or Redis in PHP, we usually encapsulate Memcache and Redis and write a Cache class separately as a proxy for Memcache or Redis, and Generally singleton mode. In the business code, when using the Cache class, the basic sample code of the operation is as follows
// cache 的 key
$key = 'this is key';
$expire = 60;// 超时时间
// cache 的实例
$cache = Wk_Cache::instance();
$data = $cache->fetch($key);
// 判断data
if(empty($data)){
// 如果为空，调用db方法
$db = new Wk_DB();
$data = $db->getXXX();
$cache->store($key, $data, $expire);
}
// 处理$data相关数据
return $data;The basic process is
Step 1 , first assemble the query key and query the value in Cache. If it exists, continue processing and enter the third step; if it does not exist, enter the second step
The second step is to query the relevant data in the DB according to the request. If the data exists, put the data into the Cache
The third step is to process the data returned in the cache or db
Problem
The above process will basically appear in every call to the Cache. Query the cache first. If not, call the DB or third-party interface to obtain the data, store it in the cache again, and continue data processing. Since multiple calls are a problem, this query method should be encapsulated into a lower-level method. Instead of repeating such logic every time, in addition to encapsulation issues, there are other issues. Let’s list them together
First: from a design perspective, repeated code requires lower-level logic encapsulation.
Second: The assembly of the key is cumbersome and cumbersome. In actual situations, various parameters may be assembled. During maintenance, you dare not modify it.
Third: The set expire timeout will be scattered in various logical codes, making it difficult to calculate the Cache cache time in the end.
Fourth: Since the cache->store method needs to be executed after calling the db, if there are other logical processes after the db, it is possible to forget to put the data into the cache, resulting in data loss.
Fifth: In a high-concurrency system, when the cache fails, a large number of requests will directly penetrate to the rear, causing the pressure on the DB or third-party interface to rise sharply, slowing down the response, and further affecting the stability of the system. This phenomenon for "Dogpile".
Among the above problems, the simplest ones are 2 and 3. For the problem of scattered expire timeouts, we can solve it through a unified configuration file. For example, we can create such a configuration file.
“test"=>array( // namespace，方便分组
"keys"=> array(
“good”=>array( // 定义的key，此key非最终入cache的key，入key需要和params组装成唯一的key
"timeout"=>600, // 此处定义超时时间
"params"=>array("epid"=>1,"num"=>1), // 通过这种方法，描述需要传递参数，用于组装最终入cache的key
"desc"=>"描述"
),
"top_test"=>array( // 定义的key，此key非最终入cache的key，入key需要和params组装成唯一的key
"timeout"=>60, // 此处定义超时时间
"ttl"=>10, // 自动触发时间
"params"=>array('site_id'=>1,'boutique'=>1,'offset'=>1,'rows'=> 1,'uid'=>1,'tag_id'=>1,'type'=>1), // 通过这种方法，描述需要传递参数，用于组装最终入cache的key
"desc"=>"描述",
"author"=>"ugg",
),
）
）
As shown above, through an algorithm, we can assemble site_top_feeds and params into a unique warehousing key. The assembled key , something like this site_top_feeds_site_id=12&boutique=1&offset=0&rows=20&uid=&tag_id=0&type=2 In this way, we prevent workers from assembling the key themselves, thereby eliminating the second problem. At the same time, in this configuration file, we also set a timeout , when calling the store, we can read directly from the configuration file, thus avoiding the third problem. After the above modifications, our cache method has also been appropriately adjusted. The calling example is as follows.
$siteid = 121;
$seminal = 1;
$tag_id = 12;
$tag_id = 22;
$data = fetch(‘site_top_feeds’,array('site_id'=>$siteid,'boutique'=>$seminal, 'offset'=>"0", 'rows' => "20", 'uid' =>null,’tag_id’=>$tag_id,’type'=>$type),'feed');
if(empty($data)){
// db相关操作
$db = new Wk_DB();
$data = $db->getTopFeeds($site_id,$seminal,0,20,null,$tag_id,$type);
// $data数据其他处理逻辑 这里
……
$cache->store(‘site_top_feeds’,$data,array(‘site_id'=>$siteid,'boutique'=>$seminal, 'offset'=>"0", 'rows' => "20", 'uid' =>null,’tag_id’=>$tag_id,’type'=>$type),'feed');
}
Through the above solution, I did not see that the timeout timeout is gone and the key assembly is gone. For outer calls, It's transparent. But we can know the timeout of site_top_feeds through the configuration file, and what the assembled key looks like through the encapsulated algorithm.
This method does not solve the first and fourth problems, encapsulation; in order to achieve encapsulation, the first thing to do is the callback function. As a school-based language, PHP does not have a complete concept of function pointers. , of course, you don’t actually need a pointer to execute a function. PHP supports callback functions in two ways: call_user_func and call_user_func_array.
However, I made two examples and found that the execution efficiency of the above method is much different than the native method
native:0.0097959041595459s call_user_func:0.028249025344849s call_user_func_array:0.046605110168457s
The example code is as follows:
$s = microtime(true);
for($i=0; $i< 10000 ; ++$i){
$a = new a();
$data = $a->aaa($array, $array, $array);
$data = a::bbb($array, $array, $array);
}
$e = microtime(true);
echo "native:".($e-$s)."s\n";
$s = microtime(true);
for($i=0; $i< 10000 ; ++$i){
$a = new a();
$data = call_user_func(array($a,'aaa'),$array,$array,$array);
$data = call_user_func(array('a','bbb'),$array,$array,$array);
}
$e = microtime(true);
echo "call_user_func:".($e-$s)."s\n";
$s = microtime(true);
for($i=0; $i< 10000 ; ++$i){
$a = new a();
$data = call_user_func_array(array($a,'aaa'),array(&$array,&$array,&$array));
$data = call_user_func_array(array('a','bbb'),array(&$array,&$array,&$array));
}
$e = microtime(true);
echo “call_user_func_array:".($e-$s)."s\n";
In PHP, if you know an object and a method, it is actually very simple to call the method. For example, in the example above
$a = new a(); $data = $a->aaa($array, $array, $array); $obj = $a; $func = ‘aaa’; $params = array($array,$array,$array); $obj->$func($params[0],$params[1],$params[2]); // 通过这种方式可以直接执行
What is the execution performance of this method? In this way, after our comparative testing, we found that
native:0.0092940330505371s call_user_func:0.028635025024414s call_user_func_array:0.048038959503174s my_callback:0.11308288574219s
switch(count($params)){
case 0: $result = $obj->{$func}();break;
case 1: $result = $obj->{$func}($params[0]);break;
case 2: $result = $obj->{$func}($params[0],$params[1]);break;
case 3: $result = $obj->{$func}($params[0],$params[1],$params[2]);break;
case 4: $result = $obj->{$func}($params[0],$params[1],$params[2],$params[3]);break;
case 5: $result = $obj->{$func}($params[0],$params[1],$params[2],$params[3],$params[4]);break;
case 6: $result = $obj->{$func}($params[0],$params[1],$params[2],$params[3],$params[4],$params[5]);break;
case 7: $result = $obj->{$func}($params[0],$params[1],$params[2],$params[3],$params[4],$params[5],$params[6]);break;
default: $result = call_user_func_array(array($obj, $func), $params); break;
}
After completing the above preparations, you can use the callback mechanism and call the business code again
….
// 相关变量赋值
$db = new Wk_DB();
$callback['obj'] = $db;
$callback['func'] = 'getTopFeeds';
$callback['params'] = array('site_id'=>$siteid,'boutique'=>$seminal, 'offset'=>"0", 'rows' => "20", 'uid' =>null,'tag_id'=>$tag_id,'type'=>$type);
$top_feed_list = $cache->smart_fetch('site_top_feeds',$callback,'feed');
…
// 变量初始化
$key = “this is key”;
$expiration = 600;
$recalculate_at = 100;
$lock_length = 20;
$data = $cache->fetch($key);
$ttl = $cache->redis->ttl($key);
if($recalculate_at>=$ttl&&$r->setnx("lock:".$key,true)){
$r->expire(“lock:”.$key, $lock_length);
$db = new Wk_DB();
$data = $db->getXXX();
$cache->store($key, $expiration, $value);
}
解决方案
好了，关键核心代码如下
1：function回调部分代码
public static function callback($callback){
// 安全检查
if(!isset($callback['obj']) || !isset($callback['func'])
|| !isset($callback['params']) || !is_array($callback['params'])){
throw new Exception("CallBack Array Error");
}
// 利用反射，判断对象和函数是否存在
$obj = $callback['obj'];
$func = $callback['func'];
$params = $callback['params'];
// 方法判断
$method = new ReflectionMethod($obj,$func);
if(!$method){
throw new Exception("CallBack Obj Not Find func");
}
// 方法属性判断
if (!($method->isPublic() || $method->isStatic())) {
throw new Exception("CallBack Obj func Error");
}
// 参数个数判断(不进行逐项检测)
$paramsNum = $method->getNumberOfParameters();
if($paramsNum < count($params)){
throw new Exception("CallBack Obj Params Error");
}
// 6个参数以内，逐个调用,超过6个，直接调用call_user_func_array
$result = false;
// 判断静态类方法
if(!is_object($obj) && $method->isStatic()){
switch(count($params)){
case 0: $result = $obj::{$func}();break;
case 1: $result = $obj::{$func}($params[0]);break;
case 2: $result = $obj::{$func}($params[0],$params[1]);break;
case 3: $result = $obj::{$func}($params[0],$params[1],$params[2]);break;
case 4: $result = $obj::{$func}($params[0],$params[1],$params[2],$params[3]);break;
case 5: $result = $obj::{$func}($params[0],$params[1],$params[2],$params[3],$params[4]);break;
case 6: $result = $obj::{$func}($params[0],$params[1],$params[2],$params[3],$params[4],$params[5]);break;
case 7: $result = $obj::{$func}($params[0],$params[1],$params[2],$params[3],$params[4],$params[5],$params[6]);break;
default: $result = call_user_func_array(array($obj, $func), $params); break;
}
}else{
switch(count($params)){
case 0: $result = $obj->{$func}();break;
case 1: $result = $obj->{$func}($params[0]);break;
case 2: $result = $obj->{$func}($params[0],$params[1]);break;
case 3: $result = $obj->{$func}($params[0],$params[1],$params[2]);break;
case 4: $result = $obj->{$func}($params[0],$params[1],$params[2],$params[3]);break;
case 5: $result = $obj->{$func}($params[0],$params[1],$params[2],$params[3],$params[4]);break;
case 6: $result = $obj->{$func}($params[0],$params[1],$params[2],$params[3],$params[4],$params[5]);break;
case 7: $result = $obj->{$func}($params[0],$params[1],$params[2],$params[3],$params[4],$params[5],$params[6]);break;
default: $result = call_user_func_array(array($obj, $func), $params); break;
}
}
public function smart_fetch($key,$callback,$namespace="wk") {
key = $prefix.$key.$suffix;
$result = $this->_redis->get($key);
$bttl = false;
// ttl状态判断(注意冷启动)
if(!empty($ttl)){
// 获得过期时间
$rttl = $this->_redis->ttl($key);
if($rttl > 0 && $ttl >= $rttl &&
$this->_redis->setnx("lock".$key,true)){
// 设置超时时间(超时时间3秒)
$this->_redis->expire("lock".$key,3);
$bttl = true;
}
}
// 如何返回值不存在，调用回调函数，获取数值，并保持数据库
if($bttl || !$result || (isset($CONFIG['FLUSH']) && !empty($CONFIG['FLUSH']))){
// 重新调整参数
$callbackparams = array();
foreach($params as $k=>$value){
$callbackparams[] = $value;
}
$callback['params'] = $callbackparams;
$result = Wk_Common::callback($callback);
$expire = $key_config["timeout"];
// 存储数据
$status = $this->_redis->setex($key, $expire, $result);
$result=$this->_redis->get($key);
}
// 删除锁
if($bttl){
$this->_redis->delete("lock".$key);
}
return $result;
}
至此，我们使用脚本语言特性，通过user_call_func_array方法补齐所有函数回调机制，从而实现对Cache的封装，通过配置文件定义组装key的规则和每个key的超时时间，再通过Redis的ttl和setnx特性，保证只有一个进程执行DB操作，从而很好避免dogpile问题，实现cache自动触发，保证cache持续存在数据，并且有效减少DB的访问次数，提高性能。
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