I have been obsessed with business development recently and haven’t updated my blog for a while. I plan to include some practical solutions in business scenarios or better design ideas in subsequent blog posts. Sharing is not like spending a lot of time sorting out related content around a topic before (holding back the ultimate trick). The content of the subsequent article may not be so rich, but it can be more detailed on one point as much as possible, or More in-depth analysis, through continuous sharing and self-review, accumulation of experience, while increasing the frequency of blog sharing
SCENARIO
SCENARIO 1
留言功能限制,30秒 内只能评论 10次,超出次数不让能再评论,并提示:过于频繁
SCENARIO 2
点赞功能限制,10秒 内只能点赞 10次,超出次数后不能再点赞,并禁止操作 1个小时,提示:过于频繁,被禁止操作1小时
Scenario 3
上传记录功能,限制一天只能上传 100次,超出次数不让能再上传,并提示:超出今日上线
Abstracting from the essence
In the process of business development, we are constantly involved in the design of various business scenarios, and it is often easy to encounter very similar problems Scenarios, but the business modules they currently belong to are different. In fact, the essence of these requirements is to solve the same problem. When encountering this scenario, we need to extract the essential issues of the requirements based on our own experience analysis and implement a universal Solutions, make your solutions more valuable, this may be the difference between you being an engineer with a soul or the strongest cp (copy paste) king.
Analyzing the above three business scenarios, we can find that they have similar logic and call them similar problems. Now we are going to isolate this problem, design a general solution, and outline the same logic flow chart :
By analyzing the above demand scenarios, we can extract the conditions they all need:
Restricted objects: User restricted operations (comments, likes) , record, ...) within the time range
(最小时间单位用秒:天/小时/分钟都可换算成秒,用秒可以解决更多的场景)If the function is extracted into a general function, would it look like this:
<?php /** * 频率限制 * @param string $action 操作动作 * @param int $userId 发起操作的用户ID * @param int $time 时间范围X秒内 * @param int $number 限制操作数Y次 * @param array $expire 超出封印时间Z ['type'=>1,'ttl'=>过期时间/秒] ['type'=>2,'ttl'=>具体过期时间戳] 二选一 * @return bool * @throws \Exception */public static function frequencyLimit(string $action, int $userId, int $time, int $number, $expire = []){ // todo 根据用户操作动作时间范围,进行频率的控制和失效释放}

The function needs to carry out the operations and time initiated by the user, as well as the cumulative number of times Storage, and need to clean up expiration. If we rely on mysql for storage at this time, it will be quite painful to think about it. The protagonist here: redis finally appears. Based on the characteristics of redis, the atomic operation of incr and key support the expiration mechanism and memory storage. The efficiency advantage can accomplish the purpose relatively simply, flexibly and efficiently.
Here is a simple code to implement a common function:
<?php /** * 频率限制 * @param string $action 操作动作 * @param int $userId 发起操作的用户ID * @param int $time 时间范围X秒内 * @param int $number 限制操作数Y次 * @param array $expire 超出封印时间Z ['type'=>1,'ttl'=>过期时间/秒] ['type'=>2,'ttl'=>具体过期时间戳] 二选一 * @return bool * @throws \Exception */public function frequencyLimit(string $action, int $userId, int $time, int $number, $expire = []){ if (empty($action) || $userId get($key)); if ($current >= $number) return false; //累计并返回最新值 $current = $r->incr($key); //第一次累加,设置控制操作频率的有效时间 if ($current === 1) $r->expire($key, $time); //未超出限制次数先放过 if ($current 0 && in_array($type, [1, 2])) { if ($type === 1) $r->expire($key, $ttl); if ($type === 2) $r->expireAt($key, $ttl); } return false; }//场景1/** * 评论限制 * @param int $userId * @return bool|string */public function doComment(int $userId){ try { $pass = FrequencyLimit::doHandle('comment', $userId, 30, 10); if (!$pass) return '过于频繁'; // todo 评论逻辑 return true; } catch (\Exception $e) { return $e->getMessage(); } }//场景2/** * 点赞限制 * @param int $userId * @return bool|string */public function doLike(int $userId){ try { $pass = FrequencyLimit::doHandle('like', $userId, 10, 10, ['type' => 1, 'ttl' => 1 * 60 * 60]); if (!$pass) return '过于频繁,被禁止操作1小时'; // todo 点赞逻辑 return true; } catch (\Exception $e) { return $e->getMessage(); } }//场景3/** * 上传限制 * @param int $userId * @return bool|string */public function doUpload(int $userId){ try { $expire = strtotime(date('Y-m-d', strtotime(+1 . 'days'))); $pass = FrequencyLimit::doHandle('upload', $userId, 1 * 24 * 60 * 60, 100, ['type' => 2, 'ttl' => $expire]); if (!$pass) return '超出今日上线'; // todo 上传逻辑 return true; } catch (\Exception $e) { return $e->getMessage(); } }//场景N
编码上可以根据你设计这个通用方案的复杂度进行进一步抽象,如抽象成频率限制的功能类等
Summary
Analyze similar business scenarios, discover essential problems and design general solutions
Make solutions more valuable and be a developer with a soul
Master redis proficiently and make full use of its features and advantages
For more Redis-related technical articles, please visit
RedisTutorialcolumn to learn!
The above is the detailed content of Redis actual combat limit operation frequency. For more information, please follow other related articles on the PHP Chinese website!

Redis stands out because of its high speed, versatility and rich data structure. 1) Redis supports data structures such as strings, lists, collections, hashs and ordered collections. 2) It stores data through memory and supports RDB and AOF persistence. 3) Starting from Redis 6.0, multi-threaded I/O operations have been introduced, which has improved performance in high concurrency scenarios.

RedisisclassifiedasaNoSQLdatabasebecauseitusesakey-valuedatamodelinsteadofthetraditionalrelationaldatabasemodel.Itoffersspeedandflexibility,makingitidealforreal-timeapplicationsandcaching,butitmaynotbesuitableforscenariosrequiringstrictdataintegrityo

Redis improves application performance and scalability by caching data, implementing distributed locking and data persistence. 1) Cache data: Use Redis to cache frequently accessed data to improve data access speed. 2) Distributed lock: Use Redis to implement distributed locks to ensure the security of operation in a distributed environment. 3) Data persistence: Ensure data security through RDB and AOF mechanisms to prevent data loss.

Redis's data model and structure include five main types: 1. String: used to store text or binary data, and supports atomic operations. 2. List: Ordered elements collection, suitable for queues and stacks. 3. Set: Unordered unique elements set, supporting set operation. 4. Ordered Set (SortedSet): A unique set of elements with scores, suitable for rankings. 5. Hash table (Hash): a collection of key-value pairs, suitable for storing objects.

Redis's database methods include in-memory databases and key-value storage. 1) Redis stores data in memory, and reads and writes fast. 2) It uses key-value pairs to store data, supports complex data structures such as lists, collections, hash tables and ordered collections, suitable for caches and NoSQL databases.

Redis is a powerful database solution because it provides fast performance, rich data structures, high availability and scalability, persistence capabilities, and a wide range of ecosystem support. 1) Extremely fast performance: Redis's data is stored in memory and has extremely fast read and write speeds, suitable for high concurrency and low latency applications. 2) Rich data structure: supports multiple data types, such as lists, collections, etc., which are suitable for a variety of scenarios. 3) High availability and scalability: supports master-slave replication and cluster mode to achieve high availability and horizontal scalability. 4) Persistence and data security: Data persistence is achieved through RDB and AOF to ensure data integrity and reliability. 5) Wide ecosystem and community support: with a huge ecosystem and active community,

Key features of Redis include speed, flexibility and rich data structure support. 1) Speed: Redis is an in-memory database, and read and write operations are almost instantaneous, suitable for cache and session management. 2) Flexibility: Supports multiple data structures, such as strings, lists, collections, etc., which are suitable for complex data processing. 3) Data structure support: provides strings, lists, collections, hash tables, etc., which are suitable for different business needs.

The core function of Redis is a high-performance in-memory data storage and processing system. 1) High-speed data access: Redis stores data in memory and provides microsecond-level read and write speed. 2) Rich data structure: supports strings, lists, collections, etc., and adapts to a variety of application scenarios. 3) Persistence: Persist data to disk through RDB and AOF. 4) Publish subscription: Can be used in message queues or real-time communication systems.


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