Speed ​​up your applications: A simple guide to Guava caching

Guava Cache Beginner’s Guide: Speeding Up Your Applications

Guava Cache is a high-performance in-memory caching library that can significantly improve Application performance. It provides a variety of caching strategies, including LRU (least recently used), LFU (least recently used), and TTL (time to live).

1. Install Guava cache

Add the dependency of Guava cache library to your project.

<dependency>
  <groupId>com.google.guava</groupId>
  <artifactId>guava</artifactId>
  <version>31.1-jre</version>
</dependency>

2. Create the cache

import com.google.common.cache.CacheBuilder;
import com.google.common.cache.CacheLoader;
import com.google.common.cache.LoadingCache;

public class GuavaCacheExample {

  public static void main(String[] args) {
    // 创建一个LRU缓存，最大容量为100
    LoadingCache<String, String> cache = CacheBuilder.newBuilder()
        .maximumSize(100)
        .build(new CacheLoader<String, String>() {
          @Override
          public String load(String key) throws Exception {
            // 从数据库或其他数据源中加载数据
            return "value-" + key;
          }
        });

    // 将数据放入缓存中
    cache.put("key1", "value1");
    cache.put("key2", "value2");

    // 从缓存中获取数据
    String value1 = cache.getIfPresent("key1");
    String value2 = cache.getIfPresent("key2");

    // 输出结果
    System.out.println(value1); // value1
    System.out.println(value2); // value2
  }
}

3. Use the cache

Once you have created the cache, you can use It is used to store and retrieve data. You can put data into the cache using the put() method and get data from the cache using the get() method.

// 将数据放入缓存中
cache.put("key3", "value3");

// 从缓存中获取数据
String value3 = cache.getIfPresent("key3");

// 输出结果
System.out.println(value3); // value3

4. Caching strategy

Guava cache provides a variety of caching strategies, including LRU (least recently used), LFU (least recently used) and TTL (survival time). You can choose the appropriate caching strategy based on your specific needs.

// 创建一个LRU缓存，最大容量为100
LoadingCache<String, String> lruCache = CacheBuilder.newBuilder()
        .maximumSize(100)
        .build(new CacheLoader<String, String>() {
          @Override
          public String load(String key) throws Exception {
            // 从数据库或其他数据源中加载数据
            return "value-" + key;
          }
        });

// 创建一个LFU缓存，最大容量为100
LoadingCache<String, String> lfuCache = CacheBuilder.newBuilder()
        .maximumSize(100)
        .weigher(Weighers.singleton())
        .build(new CacheLoader<String, String>() {
          @Override
          public String load(String key) throws Exception {
            // 从数据库或其他数据源中加载数据
            return "value-" + key;
          }
        });

// 创建一个TTL缓存，生存时间为10秒
LoadingCache<String, String> ttlCache = CacheBuilder.newBuilder()
        .expireAfterWrite(10, TimeUnit.SECONDS)
        .build(new CacheLoader<String, String>() {
          @Override
          public String load(String key) throws Exception {
            // 从数据库或其他数据源中加载数据
            return "value-" + key;
          }
        });

5. Cache statistics

Guava cache provides rich statistical information, and you can use these statistics to understand cache usage.

// 获取缓存的命中率
double hitRate = cache.stats().hitRate();

// 获取缓存的未命中率
double missRate = cache.stats().missRate();

// 获取缓存的平均加载时间
long averageLoadTime = cache.stats().averageLoadPenalty();

// 获取缓存的大小
long size = cache.size();

6. Conclusion

Guava cache is a high-performance memory caching library that can significantly improve application performance. It provides a variety of caching strategies, including LRU (least recently used), LFU (least recently used), and TTL (time to live). You can choose the appropriate caching strategy based on your specific needs.

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