Using Redis to implement current limiting strategy in PHP

With the development of the Internet, the number of requests for many websites or applications is increasing day by day, which brings great challenges to server-side resource management. In this case, the current limiting strategy becomes an important solution. This article will discuss how to use Redis to implement current limiting strategies in PHP applications.

1. Introduction to Redis

Redis is a modern open source database that uses memory to store data, making reading and writing very fast. Redis supports a variety of data types, including strings, hashes, lists, sets, and ordered sets. In addition, Redis also provides advanced functions such as publishing and subscription, transactions, etc.

2. Introduction to the current limiting strategy

The current limiting strategy refers to limiting the request frequency of an application or website to protect server-side resources and prevent overuse. For example, for some API services that require payment, website and application administrators may limit requests from unpaid users to prevent resource abuse and revenue decline. For another example, for some operations that require login verification, the administrator may restrict illegal requests to prevent brute force attacks.

3. Method of using Redis to implement the current limiting strategy

Redis provides an algorithm called "Token Bucket" for implementing the current limiting strategy. In this algorithm, requests are treated as tokens, and the server stores these tokens in a bucket (referred to as the Redis data structure ZSET). Each token carries a timestamp indicating when the token was generated. When a request arrives, it attempts to obtain a token, and if the acquisition is successful, execution can continue downwards. If the acquisition fails, the request is considered to be throttling.

The following is the implementation method of using Redis to implement the token bucket algorithm in a PHP application:

1. Create a Redis client object:

// Create a Redis client
$redis = new Redis();
$redis->connect('127.0.0.1', 6379);

2. Set the maximum capacity of the bucket:

//Set the maximum capacity of the token bucket
$bucket_capacity = 1000;

3.Set the token generation rate:

//Set the token generation rate
$token_rate = 100.0;

4. Add token:

// Add token
function add_token($redis, $token_rate, $bucket_capacity) {

$current_time = microtime(true);
$tokens = $redis->zrevrangebyscore('tokens', '+inf', $current_time);
$tokens_count = count($tokens);

// 计算当前桶内的令牌数
$current_capacity = $bucket_capacity - $tokens_count;

// 计算新令牌的数量
$new_tokens_count = ($token_rate / $bucket_capacity) * $current_capacity;
$new_tokens_count = min($new_tokens_count, $bucket_capacity - $tokens_count);

// 添加新令牌
if ($new_tokens_count > 0) {
    $multi_exec = $redis->multi();
    for ($i = 0; $i < $new_tokens_count; $i++) {
        $multi_exec->zadd('tokens', $current_time + ($i / $token_rate), $current_time + ($i / $token_rate));
    }
    $multi_exec->exec();
}

}

5. Check token:

// Check token
function check_token($redis, $bucket_capacity) {

$current_time = microtime(true);
$tokens = $redis->zrevrangebyscore('tokens', '+inf', $current_time);
$tokens_count = count($tokens);

// 计算当前桶内的令牌数
$current_capacity = $bucket_capacity - $tokens_count;

// 如果桶是满的，则限流
if ($current_capacity <= 0) {
    return false;
}

// 如果桶是空的，则添加新令牌
if ($tokens_count == 0) {
    add_token($redis, $token_rate, $bucket_capacity);
}

// 获取第一个令牌
$token_time = reset($tokens);

// 如果获取令牌的时间早于当前时间，则限流
if ($token_time < $current_time) {
    return false;
}

// 删除此令牌
$redis->zremrangebyscore('tokens', '-inf', $token_time);

return true;

}

4. Conclusion

Through the introduction of this article, we can find that the current limiting strategy can be easily implemented using the token bucket algorithm provided by Redis. It prevents brute force attacks and resource abuse and is important for protecting the security and stability of websites and applications. In general, we can use the above methods to implement current limiting strategies in PHP applications, thereby effectively maintaining server-side resource management.

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