How to build a secondary cache with redis and caffiene
To build Redis and Caffeine as the second-level cache, you can follow the steps below :
- - Configure Redis as the primary cache:
Install and configure a Redis server.
Use the Redis client library in your application to connect and interact with a Redis server.
- Integrate Caffeine as a second-level cache:
Add the dependencies of the Caffeine cache library to your project (you can use Maven, Gradle and other build tools).
To create a Caffeine cache instance in the application, you can use the Caffeine.newBuilder() method to build the cache object.
Configure the attributes of Caffeine cache, such as cache size, expiration time, etc.
Where data needs to be cached, use Caffeine cache objects to store and retrieve data.
- The use of the second level cache:
In the data acquisition operation, it first tries to acquire data from the Caffeine cache, and returns directly if the data exists.
If the data does not exist in the Caffeine cache, it tries to get the data from the Redis main cache.
If the data exists in Redis, store the data in the Caffeine cache and return the data.
If the data does not exist in Redis, get the data from the data source (such as database, API, etc.), store the data in the Redis primary cache and Caffeine secondary cache, and return the data.
- Data update and synchronization:
When the data is updated, the Redis primary cache and the Caffeine secondary cache need to be updated at the same time to maintain consistency.
After the data update operation is completed, update the corresponding data in Redis, and use the put() method of the Caffeine cache to update or add data to the Caffeine cache
The following is a sample code that demonstrates how to use Redis and Caffeine to build a basic implementation of the second-level cache:
import com.github.benmanes.caffeine.cache.Cache;
import com.github.benmanes.caffeine.cache.Caffeine;
import redis.clients.jedis.Jedis;
import java.util.concurrent.TimeUnit;
public class RedisCaffeineCacheDemo {
private static final int CACHE_EXPIRY_SECONDS = 60;
private Cache<String, String> caffeineCache;
private Jedis redisClient;
public RedisCaffeineCacheDemo() {
// 创建 Caffeine 缓存实例
caffeineCache = Caffeine.newBuilder()
.expireAfterWrite(CACHE_EXPIRY_SECONDS, TimeUnit.SECONDS)
.build();
// 创建 Redis 客户端连接
redisClient = new Jedis("localhost");
}
public String getData(String key) {
// 先尝试从 Caffeine 缓存中获取数据
String data = caffeineCache.getIfPresent(key);
if (data != null) {
System.out.println("Data retrieved from Caffeine cache: " + data);
return data;
}
// 尝试从 Redis 主缓存中获取数据
data = redisClient.get(key);
if (data != null) {
System.out.println("Data retrieved from Redis cache: " + data);
// 将数据存储到 Caffeine 缓存中
caffeineCache.put(key, data);
}
return data;
}
public void setData(String key, String value) {
// 存储数据到 Redis 主缓存
redisClient.set(key, value);
// 存储数据到 Caffeine 缓存
caffeineCache.put(key, value);
}
public static void main(String[] args) {
RedisCaffeineCacheDemo demo = new RedisCaffeineCacheDemo();
// 测试数据获取和设置
String key = "myKey";
String value = "myValue";
// 第一次获取数据，会从 Redis 中获取并存储到 Caffeine 缓存中
System.out.println("First data retrieval:");
String data = demo.getData(key);
// 第二次获取数据，会直接从 Caffeine 缓存中获取
System.out.println("Second data retrieval:");
data = demo.getData(key);
// 设置新的数据，并更新 Redis 和 Caffeine 缓存
System.out.println("Setting new data:");
demo.setData(key, value);
// 再次获取数据，会从更新后的 Redis 中获取并存储到 Caffeine 缓存中
System.out.println("Data retrieval after setting new data:");
data = demo.getData(key);
}
}
This sample code demonstrates how to implement a second-level cache with Redis and Caffeine. In the RedisCaffeineCacheDemo class, we create a Caffeine cache instance and a Redis client connection. The getData() method first tries to get the data from the Caffeine cache, and if it does not exist, it gets it from the Redis main cache and stores the data in the Caffeine cache. The setData() method is used to set new data and update Redis and Caffeine caches at the same time.
In the main() method, a simple test is performed to show the data acquisition and setting process
Caffeine has the following advantages as a second-level cache:
High performance: Caffeine is designed to provide high performance. It uses a variety of efficient data structures and algorithms to store and retrieve data quickly in memory. Compared to other caching libraries, Caffeine has lower latency on read and write operations and can handle a large number of concurrent requests.
Memory management: Caffeine provides flexible memory management options. You can set the maximum size of the cache, the maximum number of entries, and the expiration policy for various cache items to control the amount of memory the cache takes up. Caffeine also supports the weight function, which can manage the size of the cache according to the weight of the cache item, so that the cache can be better managed when memory resources are limited.
Support multiple strategies: Caffeine supports multiple cache strategies, such as least recently used (LRU), least recently used (LFU) and fixed size. You can choose an appropriate strategy based on the characteristics and requirements of your application to obtain the best cache performance.
Concurrency support: Caffeine is thread-safe and can provide stable performance and correct results in a high-concurrency environment. It uses fine-grained locks and lock-free techniques to ensure the correctness and efficiency of concurrent access to the cache.
Scalability: Caffeine has good scalability. It provides a plug-in mechanism and an extensible API, allowing developers to customize and extend cache functions according to their needs.
Statistics and monitoring: Caffeine provides a wealth of statistics and monitoring functions, which can be used to understand cache usage, hit rate, cache item status and other information. This information can help developers optimize cache configuration and performance, and perform troubleshooting and performance tuning.
Overall, Caffeine is a powerful and high-performance local caching library for a wide variety of Java applications. It provides a fast and reliable caching solution through efficient data structures, flexible memory management, and multiple caching strategies. Using Caffeine can significantly improve the performance and response speed of the application, especially suitable for caching frequently read data.