Caching Strategies: Redis + CDN + Edge Computing · Leçon

Publication/abonnement Redis pour l’invalidation

Découvrez comment utiliser la publication et l’abonnement de Redis pour invalider en temps réel le cache sur plusieurs instances d’application.

Publication/abonnement Redis pour l’invalidation est une leçon Caching Strategies: Redis + CDN + Edge Computing gratuite sur CoddyKit. Ceci est la leçon 3 sur 4. Tu peux lire la leçon complète ci-dessous gratuitement — puis la pratiquer en direct dans le navigateur avec un éditeur de code intégré et un tuteur IA 24/7. Elle fait partie du parcours d'apprentissage Caching Strategies: Redis + CDN + Edge Computing, et ta progression se synchronise sur le web et l'application CoddyKit. Le cours Caching Strategies: Redis + CDN + Edge Computing comprend 4 leçons au total.

Certaines parties de cette leçon n'ont pas encore été traduites et s'affichent en anglais.

Real-time Cache Updates

Imagine you have multiple copies of your application running, all using a local cache. When data changes in the database, how do you tell all these application instances to update their caches immediately?

Redis Publish/Subscribe (Pub/Sub) is a powerful messaging pattern that allows you to send real-time notifications to multiple clients, making it perfect for distributed cache invalidation.

Beyond Time-To-Live (TTL)

While Time-To-Live (TTL) is great for automatically expiring old data, it doesn't guarantee instant freshness. If critical data changes, you don't want to wait for the TTL to expire.

Pub/Sub provides a way to force immediate invalidation. When data is updated in your primary data store (like a database), one application instance can broadcast a message, and all other instances listening will receive it and invalidate their specific cache entries.

The Publisher Role

In the Pub/Sub model, a Publisher is an entity (like one of your application instances) that sends messages to a specific channel.

When a significant data change occurs (e.g., a product's price is updated in the database), the application instance that made the change acts as a publisher.
It doesn't care who receives the message, only that it's sent to the designated channel.

The Subscriber Role

A Subscriber is an entity (another application instance) that listens for messages on one or more specific channels.

All other application instances would be subscribers to the 'cache-invalidation' channel.
When a message arrives on a channel they're subscribed to, they receive it and can then react, for example, by removing the corresponding item from their local cache.

Redis Pub/Sub Commands

Redis provides two main commands for Pub/Sub:

PUBLISH channel message: Sends message to the specified channel. All subscribers to that channel will receive it.
SUBSCRIBE channel [channel ...]: This client subscribes to one or more channels. Once subscribed, it will continuously listen for messages.

Remember, Pub/Sub messages are fire-and-forget; Redis doesn't store them.

Publishing a Cache Invalidation

Here's how an application instance can publish an invalidation message using Java and the Jedis client. This example sends a message to invalidate a specific product.

import redis.clients.jedis.Jedis;

public class CachePublisher {
  public static void main(String[] args) {
    // Connect to Redis (default localhost:6379)
    Jedis jedis = new Jedis("localhost", 6379);

    String channel = "product-updates";
    String message = "invalidate:product:456"; // Key to invalidate

    // Publish the message
    jedis.publish(channel, message);
    System.out.println("Published: '" + message + "' to channel '" + channel + "'");

    // Close the connection
    jedis.close();
  }
}

Setting Up a Cache Subscriber

Subscribers use a special listener class to handle incoming messages. The onMessage method is where your invalidation logic goes.

Note: The jedis.subscribe() call is blocking and keeps the connection open to listen. In a real app, this runs in a dedicated thread.

import redis.clients.jedis.Jedis;
import redis.clients.jedis.JedisPubSub;

public class CacheSubscriberSetup {
  public static void main(String[] args) {
    System.out.println("Preparing Redis Pub/Sub subscriber...");

    // Define your listener logic
    JedisPubSub listener = new JedisPubSub() {
      @Override
      public void onMessage(String channel, String message) {
        System.out.println("Received: '" + message + "' on channel '" + channel + "'");
        // Here, you would implement your cache invalidation logic
        // e.g., myLocalCache.remove(message.split(":")[1]);
      }

      @Override
      public void onSubscribe(String channel, int subscribedChannels) {
        System.out.println("Successfully subscribed to: " + channel);
      }
      // Other methods like onUnsubscribe, onPMessage, etc., can be overridden
    };

    // In a real application, you'd run:
    // try (Jedis jedis = new Jedis("localhost", 6379)) {
    //   jedis.subscribe(listener, "product-updates"); // This blocks!
    // }
    System.out.println("Subscriber listener defined. To truly listen, run a blocking subscribe call.");
    System.out.println("This runnable example exits to demonstrate setup.");
  }
}

End-to-End Invalidation Flow

Let's see the full picture:

App A updates a product in the database.
App A publishes an invalidation message ('invalidate:product:456') to the 'product-updates' channel in Redis.
Redis receives the message and broadcasts it to all clients subscribed to 'product-updates'.
App B, App C (and App A itself if subscribed) receive the message.
Each app's subscriber logic removes 'product:456' from its local cache, ensuring fresh data on next request.

Designing Invalidation Messages

What should you include in your invalidation message?

Specific Key: 'invalidate:user:123' is ideal for precise invalidation.
Category: 'invalidate:all:products' for broader invalidation (use with caution).
Timestamp/Version: Can help subscribers decide if their cached data is older than the update.

Keep messages concise. Subscribers should have enough info to know what to invalidate.

Pros and Cons of Pub/Sub

Benefits:

Real-time: Immediate cache updates across instances.
Decoupled: Publishers don't need to know about subscribers.
Scalable: Redis handles message distribution efficiently.

Considerations:

No Persistence: If a subscriber is offline, it misses messages.
At-Most-Once: Redis Pub/Sub doesn't guarantee delivery. For critical systems, consider other messaging patterns or a combination.

Pub/Sub Invalidation Quiz

You've learned how Redis Pub/Sub helps with real-time cache invalidation. Let's test your understanding!

Pub/Sub for Fresh Data

Great job! You've explored how Redis Publish/Subscribe is a vital tool for maintaining data freshness in distributed caching environments.

Pub/Sub allows real-time broadcasting of invalidation messages.
Publishers send messages, and subscribers listen to channels.
This pattern enables immediate cache updates across all application instances when data changes, improving consistency and user experience.
While powerful, remember its 'fire-and-forget' nature and consider persistence needs for critical systems.

Questions Fréquemment Posées

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Toutes les leçons de ce cours

Persistance et HA de Redis
Mise en cache distribuée avec Redis
Publication/abonnement Redis pour l’invalidation
Cluster Redis et partitionnement

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