How to develop a current limiter function using Redis and Lua

How to use Redis and Lua to develop the current limiter function

Introduction:
With the development of the Internet, many applications are facing the challenge of high concurrency. When facing a large number of requests, measures must be taken to protect the stability and availability of the system. One of the important means is current limiting. Current limiting refers to controlling the flow of requests to ensure that the system can still operate normally during load peaks. This article will introduce how to develop a simple current limiter function using Redis and Lua, and provide specific code examples.

1. Introduction to Redis
Redis is an open source in-memory database that is widely used in scenarios such as caching, message queues, counters, and rankings. Its high performance and flexible data structures make it the first choice for many applications. In the development of current limiters, Redis's atomic operations and built-in Lua scripting capabilities will be very useful.

2. Current limiter design ideas
The current limiter mainly has three key factors: limited request rate, time window and counter. In Redis, we can use Sorted Set to store key-value pairs of request number and timestamp. The specific design ideas are as follows:

1. Use an ordered collection to store the number of requests and timestamps, where the timestamp is used as the score.
2. Every time a request comes, store the timestamp of the request and the number of requests in an ordered collection.
3. Check whether the number of requests in the ordered set exceeds the limit.
4. If the limit is exceeded, reject the request; otherwise, allow the request and update the number of requests in the ordered set.

3. Specific implementation code example
The following is a specific implementation code example of a current limiter developed using Redis and Lua.

1. Initialize the current limiter:

local limitKey = 'limit:' .. KEYS[1]
local rate = tonumber(ARGV[1])
local interval = tonumber(ARGV[2])

redis.call('DEL', limitKey)
redis.call('ZADD', limitKey, redis.call('TIME')[1], rate)
redis.call('PEXPIRE', limitKey, interval * 1000)

2. Determine whether the request is restricted:

local limitKey = 'limit:' .. KEYS[1]
local now = tonumber(ARGV[1])
local interval = tonumber(ARGV[2])
local maxRequests = tonumber(ARGV[3])

redis.call('ZREMRANGEBYSCORE', limitKey, '-inf', '(' .. now - interval)
redis.call('ZADD', limitKey, now, now)
if redis.call('ZCARD', limitKey) > maxRequests then
    return 0
else
    return 1
end

Fourth, use the current limiter to implement Request limit
We can encapsulate the above code into a reusable current limiter function for other applications to call. The following is a simple example:

local function limitRequest(bucket, rate, interval, maxRequests)
    local limitKey = 'limit:' .. bucket
    local now = tonumber(redis.call('TIME')[1])

    redis.call('ZREMRANGEBYSCORE', limitKey, '-inf', '(' .. now - interval)
    redis.call('ZADD', limitKey, now, now)
    redis.call('PEXPIRE', limitKey, interval * 1000)

    if redis.call('ZCARD', limitKey) > maxRequests then
        return 0
    else
        return 1
    end
end

local bucket = 'api:rate_limiter'
local rate = 10  -- 最大请求数
local interval = 60  -- 时间窗口大小（秒）
local maxRequests = 100  -- 限制的请求数量
local allowed = limitRequest(bucket, rate, interval, maxRequests)

if allowed == 1 then
    -- 允许请求
    -- TODO: 处理请求
else
    -- 拒绝请求
    -- TODO: 返回错误信息
end

By calling the limitRequest function, we can easily implement the request limitation function.

Summary:
This article introduces how to use Redis and Lua to develop a simple current limiter function, and gives specific code examples. The current limiter can help us control the flow of requests and protect the stability and availability of the system. In actual applications, you can further customize and expand it according to your needs. Hope this article is helpful to you.

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