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API Rate Limiting & Scalability Patterns · Aula

Contador de janela fixa explicado

Descubra como funciona o algoritmo do contador de janela fixa, sua simplicidade e suas possíveis limitações ao lidar com picos de tráfego.

Contador de janela fixa explicado é uma aula grátis de API Rate Limiting & Scalability Patterns no CoddyKit. Esta é a aula 1 de 4. Você pode ler a aula completa abaixo gratuitamente — depois pratica ao vivo no navegador com um editor de código integrado e um tutor de IA 24/7. Faz parte do caminho de aprendizado de API Rate Limiting & Scalability Patterns, e seu progresso é sincronizado entre a web e o app CoddyKit. O curso de API Rate Limiting & Scalability Patterns inclui 4 aulas no total.

Partes desta aula ainda não foram traduzidas e aparecem em inglês.

Why Algorithms?

Rate limiting isn't just a 'yes' or 'no' check. It relies on smart algorithms to manage traffic. These algorithms decide how and when to allow or deny requests, ensuring fairness and stability.

We'll start with one of the simplest: the Fixed Window Counter.

Fixed Window Counter: The Idea

The Fixed Window Counter is a straightforward rate limiting algorithm. It works by dividing time into fixed, non-overlapping windows.

  • Each window has its own request counter.
  • Once a request comes in, the counter for the current window increments.
  • If the counter exceeds a predefined limit within that window, further requests are blocked.

How It Counts

Imagine a clock. For every minute (our fixed window), we allow, say, 10 requests. When a new minute starts, the counter resets to zero.

  • Window: A specific time period (e.g., 60 seconds).
  • Limit: Maximum requests allowed in that window.
  • Counter: Tracks requests within the current window.

It's like a bouncer at a club, letting in only a set number of people each hour, then resetting the count for the next hour.

Example: 10 RPS Limit

Let's say our limit is 10 requests per second (RPS).

  • Window 1 (0-1s): 7 requests made. 3 requests remaining.
  • Window 2 (1-2s): 12 requests made. First 10 allowed, next 2 blocked.
  • Window 3 (2-3s): 5 requests made. All allowed.

At the start of each new second, the counter resets, regardless of activity in the previous second.

Basic Counter Logic

Here's a simple Java class simulating a request counter. This forms the foundation of our rate limiter. It keeps track of requests within a defined window.

import java.time.Instant;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicInteger;

class FixedWindowCounter {
    private final int limit;
    private final long windowSizeMillis; // e.g., 60_000 for 1 minute
    private final ConcurrentHashMap<Long, AtomicInteger> counters;

    public FixedWindowCounter(int limit, long windowSizeMillis) {
        this.limit = limit;
        this.windowSizeMillis = windowSizeMillis;
        this.counters = new ConcurrentHashMap<>();
    }

    public boolean allowRequest(String userId) {
        long currentWindowKey = Instant.now().toEpochMilli() / windowSizeMillis;
        
        // Get or create counter for the current window
        AtomicInteger counter = counters.computeIfAbsent(
            currentWindowKey, k -> new AtomicInteger(0)
        );

        // Increment and check if within limit
        return counter.incrementAndGet() <= limit;
    }
}

public class Main {
    public static void main(String[] args) {
        System.out.println("FixedWindowCounter class defined.");
        System.out.println("Ready to use in next example.");
    }
}

Testing the Window

Let's use our FixedWindowCounter class to simulate requests and see how it limits them within a 1-second window. Observe how requests are counted and then reset for the next window.

import java.time.Instant;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicInteger;

// The FixedWindowCounter class
class FixedWindowCounter {
    private final int limit;
    private final long windowSizeMillis;
    private final ConcurrentHashMap<Long, AtomicInteger> counters;

    public FixedWindowCounter(int limit, long windowSizeMillis) {
        this.limit = limit;
        this.windowSizeMillis = windowSizeMillis;
        this.counters = new ConcurrentHashMap<>();
    }

    public boolean allowRequest(String userId) {
        long currentWindowKey = Instant.now().toEpochMilli() / windowSizeMillis;
        AtomicInteger counter = counters.computeIfAbsent(
            currentWindowKey, k -> new AtomicInteger(0)
        );
        return counter.incrementAndGet() <= limit;
    }
}

public class Main {
    public static void main(String[] args) throws InterruptedException {
        // Allow 3 requests per 1-second window
        FixedWindowCounter limiter = new FixedWindowCounter(3, 1000); 

        System.out.println("--- First Window ---");
        for (int i = 0; i < 5; i++) {
            boolean allowed = limiter.allowRequest("user1");
            System.out.println("Request " + (i + 1) + ": " + (allowed ? "ALLOWED" : "BLOCKED"));
        }

        // Wait for next window to start
        Thread.sleep(1100); 

        System.out.println("\n--- Second Window ---");
        for (int i = 0; i < 2; i++) {
            boolean allowed = limiter.allowRequest("user1");
            System.out.println("Request " + (i + 1) + ": " + (allowed ? "ALLOWED" : "BLOCKED"));
        }
    }
}

Fixed Window: Pros

The Fixed Window Counter algorithm is popular for its simplicity and efficiency in certain scenarios.

  • Easy to Implement: Requires minimal logic and data structures (just a counter and a timestamp).
  • Low Resource Usage: Very little memory and CPU overhead per window.
  • Predictable: The reset at the start of each window is clear and easy to understand.

It's a good choice for basic rate limiting where precision isn't paramount.

The Burst Problem

Despite its simplicity, the Fixed Window Counter has a significant drawback: it can allow twice the intended rate limit at the window boundaries.

Imagine a limit of 10 requests per minute.

  • A user makes 10 requests at 0:59 (end of window 1).
  • They then make 10 more requests at 1:01 (start of window 2).

This means 20 requests were made within a very short 2-minute period, effectively doubling the rate in a small burst.

Boundary Bursts

Let's visualize the burst issue with a 5 requests/minute limit.

  • Window 1 (0:00 - 0:59): 5 requests sent at 0:58. (Allowed)
  • Window 2 (1:00 - 1:59): 5 requests sent at 1:01. (Allowed)

In just 3 minutes (0:58 to 1:01), 10 requests were allowed. This is effectively 5 requests in ~3 seconds, not 5 requests per minute, defeating the purpose of the limit.

This 'burst' can overwhelm your system if not accounted for.

Fixed Window Check

Consider a fixed window rate limiter set to 5 requests per minute. The current time is 0:59:30. A user has already made 4 requests in the current window (0:00:00 to 0:59:59).

They then make another 3 requests at 0:59:45. Immediately after, at 1:00:05 (5 seconds into the next window), they make 3 more requests.

Recap: Fixed Window

We've explored the Fixed Window Counter algorithm:

  • It divides time into distinct, non-overlapping windows.
  • Each window has a request counter that resets at the start of a new window.
  • It's simple to implement and understand.
  • Its main drawback is the burst problem, where requests at window boundaries can effectively double the rate in a short period.

Next, we'll look at algorithms that try to smooth out these bursts!

Perguntas Frequentes

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O que vou aprender em “Contador de janela fixa explicado”?

Descubra como funciona o algoritmo do contador de janela fixa, sua simplicidade e suas possíveis limitações ao lidar com picos de tráfego. Você pratica API Rate Limiting & Scalability Patterns com código prático que executa diretamente no navegador, e um tutor de IA 24/7 responde suas dúvidas enquanto trabalha na aula.

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Nenhuma experiência prévia é necessária. API Rate Limiting & Scalability Patterns no CoddyKit é estruturado para alunos iniciantes até avançados, então você pode começar aqui ou desde o início e aprender no seu ritmo. Esta é a aula 1 de 4.

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Todas as aulas deste curso

  1. Contador de janela fixa explicado
  2. Análise detalhada do algoritmo do balde furado
  3. Mecânica do algoritmo do balde de tokens
  4. Escolha do algoritmo adequado
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