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This article mainly shares with you common usage scenarios of Redis and simple string caching practice. I hope it can help you.
$redis->connect('127.0.0.1', 6379); $strCacheKey = 'Test_bihu';//SET 应用$arrCacheData = [ 'name' => 'job', 'sex' => '男', 'age' => '30']; $redis->set($strCacheKey, json_encode($arrCacheData)); $redis->expire($strCacheKey, 30); # 设置30秒后过期$json_data = $redis->get($strCacheKey); $data = json_decode($json_data); print_r($data->age); //输出数据//HSET 应用$arrWebSite = [ 'google' => [ 'google.com', 'google.com.hk' ], ]; $redis->hSet($strCacheKey, 'google', json_encode($arrWebSite['google'])); $json_data = $redis->hGet($strCacheKey, 'google'); $data = json_decode($json_data); print_r($data); //输出数据
Simple queue practice
$redis->connect('127.0.0.1', 6379); $strQueueName = 'Test_bihu_queue';//进队列$redis->rpush($strQueueName, json_encode(['uid' => 1,'name' => 'Job'])); $redis->rpush($strQueueName, json_encode(['uid' => 2,'name' => 'Tom'])); $redis->rpush($strQueueName, json_encode(['uid' => 3,'name' => 'John']));echo "---- 进队列成功 ---- <br /><br />";//查看队列$strCount = $redis->lrange($strQueueName, 0, -1);echo "当前队列数据为: <br />"; print_r($strCount);//出队列$redis->lpop($strQueueName);echo "<br /><br /> ---- 出队列成功 ---- <br /><br />";//查看队列$strCount = $redis->lrange($strQueueName, 0, -1);echo "当前队列数据为: <br />"; print_r($strCount);
Simple publish and subscribe practice
//以下是 pub.php 文件的内容 cli下运行ini_set('default_socket_timeout', -1); $redis->connect('127.0.0.1', 6379); $strChannel = 'Test_bihu_channel';//发布$redis->publish($strChannel, "来自{$strChannel}频道的推送");echo "---- {$strChannel} ---- 频道消息推送成功~ <br/>"; $redis->close();
Simple counter practice
//以下是 sub.php 文件内容 cli下运行ini_set('default_socket_timeout', -1); $redis->connect('127.0.0.1', 6379); $strChannel = 'Test_bihu_channel';//订阅echo "---- 订阅{$strChannel}这个频道,等待消息推送...---- <br/><br/>"; $redis->subscribe([$strChannel], 'callBackFun');function callBackFun($redis, $channel, $msg){ print_r([ 'redis' => $redis, 'channel' => $channel, 'msg' => $msg ]); }
Ranking practice
$redis->connect('127.0.0.1', 6379); $strKey = 'Test_bihu_comments';//设置初始值$redis->set($strKey, 0); $redis->INCR($strKey); //+1$redis->INCR($strKey); //+1$redis->INCR($strKey); //+1$strNowCount = $redis->get($strKey);echo "---- 当前数量为{$strNowCount}。 ---- ";
$redis->connect('127.0.0.1', 6379); $strKey = 'Test_bihu_score';//存储数据$redis->zadd($strKey, '50', json_encode(['name' => 'Tom'])); $redis->zadd($strKey, '70', json_encode(['name' => 'John'])); $redis->zadd($strKey, '90', json_encode(['name' => 'Jerry'])); $redis->zadd($strKey, '30', json_encode(['name' => 'Job'])); $redis->zadd($strKey, '100', json_encode(['name' => 'LiMing'])); $dataOne = $redis->ZREVRANGE($strKey, 0, -1, true);echo "---- {$strKey}由大到小的排序 ---- <br /><br />"; print_r($dataOne); $dataTwo = $redis->ZRANGE($strKey, 0, -1, true);echo "<br /><br />---- {$strKey}由小到大的排序 ---- <br /><br />"; print_r($dataTwo);
Explanation: Pessimistic Lock, as the name suggests, is very pessimistic.
Every time I go to get the data, I think that others will modify it, so I lock it every time I get the data.
Scenario: If cache is used in the project and a timeout is set for the cache.
When the amount of concurrency is relatively large, if there is no lock mechanism, then the moment the cache expires,
A large number of concurrent requests will penetrate the cache and directly query the database, causing an avalanche effect.
/** * 获取锁 * @param String $key 锁标识 * @param Int $expire 锁过期时间 * @return Boolean */public function lock($key = '', $expire = 5) { $is_lock = $this->_redis->setnx($key, time()+$expire); //不能获取锁 if(!$is_lock){ //判断锁是否过期 $lock_time = $this->_redis->get($key); //锁已过期,删除锁,重新获取 if (time() > $lock_time) { unlock($key); $is_lock = $this->_redis->setnx($key, time() + $expire); } } return $is_lock? true : false; }/** * 释放锁 * @param String $key 锁标识 * @return Boolean */public function unlock($key = ''){ return $this->_redis->del($key); }// 定义锁标识$key = 'Test_bihu_lock';// 获取锁$is_lock = lock($key, 10);if ($is_lock) { echo 'get lock success<br>'; echo 'do sth..<br>'; sleep(5); echo 'success<br>'; unlock($key); } else { //获取锁失败 echo 'request too frequently<br>'; }
Optimistic locking practice for simple transactions
Explanation: Optimistic Lock (Optimistic Lock), as the name suggests, is very optimistic.
Every time I go to get the data, I think that others will not modify it, so it will not be locked.
The watch command will monitor the given key. If the monitored key has changed since calling watch during exec, the entire transaction will fail.
You can also call watch multiple times to monitor multiple keys. In this way, optimistic locking can be added to the specified key.
Note that the watch key is valid for the entire connection, and the same is true for transactions.
If the connection is disconnected, monitoring and transactions will be automatically cleared.
Of course, the exec, discard, and unwatch commands will clear all monitoring in the connection.
$strKey = 'Test_bihu_age'; $redis->set($strKey,10); $age = $redis->get($strKey);echo "---- Current Age:{$age} ---- <br/><br/>"; $redis->watch($strKey);// 开启事务$redis->multi();//在这个时候新开了一个新会话执行$redis->set($strKey,30); //新会话echo "---- Current Age:{$age} ---- <br/><br/>"; //30$redis->set($strKey,20); $redis->exec(); $age = $redis->get($strKey);echo "---- Current Age:{$age} ---- <br/><br/>"; //30//当exec时候如果监视的key从调用watch后发生过变化,则整个事务会失败
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