Cache expiration strategy in Java caching technology

Cache expiration strategy in Java caching technology

In the process of using caching technology to optimize program performance, a reasonable cache expiration strategy is very important. Because once the cache expiration policy fails, it will lead to problems such as inaccurate, invalid or expired data in the cache, thus reducing the performance and accuracy of the program.

In Java caching technology, the cache expiration strategies often used are as follows:

1. Time expiration strategy

The time expiration strategy refers to setting a cache data Expiration time, within which the data is valid. Once the expiration time is reached, the cached data will be automatically invalidated and needs to be reacquired or calculated. Common application scenarios for this strategy include: user sessions, static pages, data queries, etc.

For example, the following is a cache based on the time expiration policy implemented through Guava cache:

Cache<String, Object> cache = CacheBuilder.newBuilder()
    .expireAfterWrite(10, TimeUnit.MINUTES) // 缓存过期时间为10分钟
    .build();

cache.put("key1", "value1"); // 将数据放入缓存
Object value = cache.getIfPresent("key1"); // 从缓存中获取数据

In the above example, the expiration time of the cached data is set to 10 minutes, so the data can only be It can survive for 10 minutes, and the data will automatically expire after 10 minutes.

2. Object upper limit policy

Object upper limit policy means that when the number of cached data objects reaches the set upper limit, some data in the cache needs to be automatically cleared. This strategy can avoid the problem of memory overflow caused by too much cached data. We can implement this strategy by setting an upper limit on the capacity of cached data.

For example, the following is the implementation of a caching strategy based on the upper capacity limit:

Cache<String, Object> cache = CacheBuilder.newBuilder()
    .maximumSize(100) // 缓存上限为100个对象
    .build();

cache.put("key1", "value1"); // 将数据放入缓存
Object value = cache.getIfPresent("key1"); // 从缓存中获取数据

In the above example, the maximum capacity of cached data is set to 100 objects. When the number of cached data reaches 100 When new objects need to be stored, the cache program will clear some of the less commonly used or least recently used objects to make room for new objects.

3. Periodic cleanup strategy

Periodic cleanup strategy refers to cleaning up the data in the cache regularly, which can avoid the problem of data not being cleared immediately when the expiration time is up, thus ensuring System performance and data accuracy. This strategy is usually used when the cached data is not particularly important, or when part of the data is no longer accessed after a period of time.

For example, the following is a cache implementation based on the periodic cleanup strategy:

Cache<String, Object> cache = CacheBuilder.newBuilder()
    .expireAfterWrite(10, TimeUnit.MINUTES) // 缓存过期时间为10分钟
    .maximumSize(100) // 缓存容量上限为100个对象
    .ticker(Ticker.systemTicker()) // 定时器使用系统定时器
    .build();

ScheduledExecutorService executorService = Executors.newScheduledThreadPool(1);
executorService.scheduleAtFixedRate(cache::cleanUp, 0, 1, TimeUnit.MINUTES);

In the above example, set the expiration time and capacity limit of the cached data to 10 minutes and 100 objects, and then pass Set a timer to clear cached data every minute.

In short, in the actual development process, the choice of cache expiration strategy depends on the specific business logic and scenario requirements. We need to flexibly use caching technology according to our actual situation and combine it with corresponding cache expiration strategies to improve the performance and stability of the application system.

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