How to use redis message queue to publish Weibo in PHP

This article mainly introduces the method of PHP using the redis message queue to publish Weibo. It analyzes the related skills and precautions of PHP combined with the redis database to operate the message queue to implement Weibo publishing based on specific examples. Friends in need can refer to the following , hope it can help everyone.

In some applications where users publish content, tens of thousands of users may publish messages simultaneously in one second. At this time, "too many connections" errors may occur when using mysql. Of course, set the max_connections parameter of Mysql to A larger number, but this is a temporary solution rather than a permanent solution. Using the redis message queue, messages posted by users are temporarily stored in the message queue, and then multiple cron programs are used to insert the data in the message queue into Mysql. This effectively reduces the high concurrency of Mysql. The specific implementation principle is as follows:

Existing Weibo publishing interface:

$weibo = new Weibo();
$uid = $weibo->get_uid();
$content =$weibo->get_content;
$time = time();
$webi->post($uid,$content,$time);

This method directly writes Weibo content into Mysql. The specific process is omitted.

Write the message to redis:

$redis = new Redis(localhost,6379);
$redis->connect();
$webiInfo = array('uid'=>get_uid(),'content'=>get_content(),'time'=>time());
$redis->lpush('weibo_list',json_encode($weiboInfo));
$redis->close();

Get the data from redis:

while(true){
   if($redis->lsize('weibo_list') > 0){
     $info = $redis->rpop('weibo_list');
     $info = json_decode($info);
   }else{
     sleep(1);
   }
}
$weibo->post($info->uid,$info->content,$info->time);
//插入数据的时候可以用一次性插入多条数据的方法，避免循环插入，不停的循环插入可能会导致死锁问题。

Tips: You can run multiple cron programs to insert message queue data into Mysql at the same time. When a Redis server cannot handle a large amount of concurrency, use the consistent Hash algorithm to distribute concurrency to different Redis server.

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