Spring Boot provides a number of features out of the box for caching static and dynamic data. This article will explore the most popular caching strategies used in Spring Boot, including the pros and cons of each.
The simplest form of caching is to cache static data that does not change often. This can be done using the @Cacheable annotation. For example, if we have a slow service that returns a list of users, we can cache the result using the following code:
@Cacheable(value = "users")
public List<User> getAllUsers() {
// Slow service call
}
This will store the result of the service call in a cache with the key "users". The next time the service is called, the cached result will be returned instead of making the slow service call.
Caching dynamic data is a bit more complicated, but can be very useful for reducing the load on a database or other resource. There are a couple of different approaches that can be taken.
The cache-aside pattern is a common approach for caching data that is read from a database or other slow resource. The basic idea is to first check the cache for the requested data. If the data is not in the cache, it is fetched from the slow resource and then stored in the cache. This pattern can be implemented using the following code:
@Cacheable(value = "users", key = "#id")
public User getUserById(String id) {
// Check cache
User user = cache.get(id);
// If not in cache, fetch from database
if (user == null) {
user = database.get(id);
// Store in cache
cache.put(id, user);
}
return user;
}
This will first check the cache for a user with the given ID. If the user is not in the cache, it will be fetched from the database and stored in the cache. The next time the same user is requested, the cached copy will be returned.
Another common pattern for caching data is the read-through cache. This pattern is similar to the cache-aside pattern, but the data is always fetched from the slow resource. The result is then stored in the cache and returned to the caller. This pattern can be implemented using the following code:
@Cacheable(value = "users", key = "#id")
public User getUserById(String id) {
// Fetch from database
User user = database.get(id);
// Store in cache
cache.put(id, user);
return user;
}
This will fetch the user from the database and store the result in the cache. The next time the same user is requested, the cached copy will be returned.
There is no one perfect caching strategy for all situations. The right strategy depends on the data being cached, the expected load on the system, and other factors.
For static data that does not change often, the simplest solution is to use the @Cacheable annotation. This will store the data in the cache and return it on subsequent requests.
For dynamic data, the choice of caching strategy depends on a number of factors. If the data is read frequently and the load on the system is high, a cache-aside or read-through cache may be the best option. If the data is read less frequently or the load on the system is low, a cache-aside pattern may be sufficient.