Spring Boot 4 Microservices & REST APIs · 课时

微服务缓存策略

探索并实现 Redis 等缓存机制，提升微服务性能。

第 5 / 9 课12 个步骤

微服务缓存策略 是 CoddyKit 上的免费 Spring Boot 4 Microservices & REST APIs 课时。这是第 5 节课，共 9 节。你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。这是 Spring Boot 4 Microservices & REST APIs 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Spring Boot 4 Microservices & REST APIs 课程共包含 9 节课。

本课时的部分内容尚未翻译，以英文显示。

Why Use Caching?

Imagine your microservice frequently fetches the same data from a database or another slow service. Each request means waiting, consuming resources, and slowing things down.

Performance Boost: Caching stores frequently accessed data closer to your application.
Reduced Load: Less pressure on databases and external services.
Faster Responses: Users experience quicker interactions.

Caching is a powerful technique for optimizing microservice performance.

Understanding Cache Basics

A cache is a temporary storage area that holds copies of data. When your application needs data, it first checks the cache.

Cache Hit: Data is found in the cache, retrieved quickly.
Cache Miss: Data is not in the cache, so it's fetched from the original source (e.g., database) and then stored in the cache for future use.

Think of it like remembering a phone number you dial often!

In-Memory vs. Distributed Cache

There are two main types of caches:

In-Memory Cache: Stored directly within a single application instance. Fast, but data is lost if the instance restarts, and not shared across multiple microservice instances.
Distributed Cache: A separate service (like Redis) that multiple microservice instances can connect to. Data is shared and persistent across instances, crucial for scalable microservices.

For microservices, distributed caching is usually preferred.

Introducing Redis for Caching

Redis (Remote Dictionary Server) is a popular, open-source, in-memory data store. It's often used as a distributed cache due to its speed and versatility.

Key-Value Store: Stores data as simple key-value pairs.
Blazingly Fast: Operations are very quick, often in microseconds.
Versatile: Supports various data structures like strings, hashes, lists, sets, and more.

It's an excellent choice for shared caching in a microservices architecture.

Spring Boot & Redis Setup

To integrate Redis with Spring Boot, you'll need the spring-boot-starter-data-redis dependency.

Add this to your pom.xml (Maven) or build.gradle (Gradle):

<dependency>
  <groupId>org.springframework.boot</groupId>
  <artifactId>spring-boot-starter-data-redis</artifactId>
</dependency>

Spring Boot auto-configures Redis if it finds a running instance (e.g., via Docker) or connection properties in application.properties.

Spring's Caching Magic

Spring Boot provides a powerful Cache Abstraction layer. This means you can add caching to your application with simple annotations, without directly interacting with Redis code.

To enable caching in your Spring Boot application, simply add the @EnableCaching annotation to your main application class:

@SpringBootApplication
@EnableCaching
public class MyServiceApplication { ... }

This tells Spring to look for caching annotations on your methods.

Reading from Cache: @Cacheable

The @Cacheable annotation is used on methods whose results you want to cache. When a method annotated with @Cacheable is called:

Spring checks if the result for the given arguments is already in the cache.
If found, the cached value is returned (cache hit).
If not found, the method is executed, its result is stored in the cache, and then returned (cache miss).

Specify a value (cache name) and optionally a key expression.

Live Demo: Caching Concept

This simple Java program demonstrates the core idea behind caching. Notice how the 'database' call count increases only for new IDs, while repeated calls retrieve data instantly from the 'cache'.

import java.util.HashMap;
import java.util.Map;

// A simple in-memory cache
class SimpleProductCache {
    private Map<String, String> cache = new HashMap<>();

    public String get(String key) {
        return cache.get(key);
    }

    public void put(String key, String value) {
        cache.put(key, value);
    }

    public void remove(String key) {
        cache.remove(key);
    }
}

class ProductFetcher {
    private SimpleProductCache productCache;
    private int dbCallCount = 0;

    public ProductFetcher(SimpleProductCache cache) {
        this.productCache = cache;
    }

    public String fetchProductName(String productId) {
        // Try to get from cache first
        String cachedName = productCache.get(productId);
        if (cachedName != null) {
            System.out.println("--> Retrieved '" + productId + "' from cache.");
            return cachedName;
        }

        // If not in cache, simulate database call
        dbCallCount++;
        System.out.println("--> Fetching '" + productId + "' from database (Call #" + dbCallCount + ").");
        try {
            Thread.sleep(100); // Simulate delay
        } catch (InterruptedException e) {
            Thread.currentThread().interrupt();
        }
        String productName = "Product " + productId + " Name";

        // Store in cache
        productCache.put(productId, productName);
        return productName;
    }
}

public class Main {
    public static void main(String[] args) {
        SimpleProductCache cache = new SimpleProductCache();
        ProductFetcher fetcher = new ProductFetcher(cache);

        System.out.println("--- First requests ---");
        System.out.println(fetcher.fetchProductName("A1"));
        System.out.println(fetcher.fetchProductName("B2"));

        System.out.println("\n--- Repeat requests ---");
        System.out.println(fetcher.fetchProductName("A1")); // Should be from cache
        System.out.println(fetcher.fetchProductName("B2")); // Should be from cache

        System.out.println("\n--- New request ---");
        System.out.println(fetcher.fetchProductName("C3")); // Should be from DB
    }
}

Updating Cache: @CachePut

Sometimes you want to update the cache with the result of a method call, even if the data was already in the cache. This is where @CachePut comes in.

@CachePut(value = "products", key = "#product.id")
public Product updateProduct(Product product) {
  // ... update product in database ...
  return product;
}

Unlike @Cacheable, the method is always executed.
Its result is then placed into the cache.

Use it for methods that modify data and you want the cache to reflect the latest state.

Removing Stale Data: @CacheEvict

When data changes in your database, you need to remove the old, stale data from the cache. The @CacheEvict annotation handles this.

@CacheEvict(value = "products", key = "#id")
public void deleteProduct(String id) {
  // ... delete product from database ...
}

When this method is called, the entry for the specified key in the products cache will be removed.
You can also use allEntries = true to clear the entire cache.

Use it after delete or update operations to ensure data consistency.

Cache Strategy Quiz

You are building a microservice that manages customer data. Which caching strategy would you use for the following scenarios?

在交互式课程中回答

Caching for Performance: Recap

Congratulations! You've learned about caching strategies for microservices.

Caching boosts performance and reduces database load.
Distributed caches like Redis are ideal for microservices.
Spring's Cache Abstraction simplifies caching with annotations.
Use @Cacheable for read-heavy operations.
Use @CachePut to update cached entries.
Use @CacheEvict to remove stale cache entries.

Mastering caching helps you build highly scalable and responsive microservices.

免费开始

用 AI 导师学习 Java — 免费

在浏览器中编写并运行真实代码，获得全天候 AI 导师的即时帮助，并在网页或应用中继续学习。

课程: 24
课程: 93

免费开始学习查看完整课程

常见问题解答

「微服务缓存策略」课时是免费的吗？

是的 — 「微服务缓存策略」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Spring Boot 4 Microservices & REST APIs 课程的其余内容，请升级到 CoddyKit PRO。 Spring Boot 4 Microservices & REST APIs 课程共包含 9 节课。

「微服务缓存策略」这节课中我会学到什么？

探索并实现 Redis 等缓存机制，提升微服务性能。你通过在浏览器中直接运行的动手代码来练习 Spring Boot 4 Microservices & REST APIs，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Spring Boot 4 Microservices & REST APIs 需要有经验吗？

无需任何先前经验。CoddyKit 上的 Spring Boot 4 Microservices & REST APIs 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。这是第 5 节课，共 9 节。

「微服务缓存策略」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 Spring Boot 4 Microservices & REST APIs 课中编写并运行代码吗？

能。每节 Spring Boot 4 Microservices & REST APIs 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

此课程中的所有课时

← 返回 Spring Boot 4 Microservices & REST APIs