Caching in a JEE : don’t write it yourself, use LoadingCache from Google Guava libraries.

Caching data is something you use in almost every JEE project. Most of the time it’s pretty simple : put your data in a .properties file and use a PropertyManager to fetch the data.

But that’s not very flexible and manageable. Updating the values means, updating your property file, repackaging the ear file, and redeploying, and only developers can update the data.

Putting the data in JNDI entries, and using JNDI lookups may solve the problem of redeploying, but if you got a few 100 properties, it’s still not very manageable.

Most of the times, JNDI entries are entered via some application server console which, in a production environment, is not accessible for your users who need to manage this data.

So lets put the data that needs to be cached in a database, or make it accessible via a web service. That would be ideal. You can write your own application on it, and have the data managed by your users.

But that means that you have to write your own, thread safe, caching algorithms.

No big deal if the data only changes once every 10 years, but refreshing it on a time or size basis, makes the whole thing a bit more complicated. And that’s where the great LoadingCache class from the Google Guava library comes in.

What are the Guave libraries ? Well, here’s how they describe it : ‘The Guava project contains several of Google’s core libraries that we rely on in our Java-based projects: collections, caching, primitives support, concurrency libraries, common annotations, string processing, I/O, and so forth.’

Now for caching, the Guava LoadingCache class caches data in a key-object map, and lets you define a cache refreshing mechanism, all done in a thread safe manner.

So lets show a small  example and explain how it works. Suppose your cache contains a list of products that are on sale for 1 day. Depending on the no. of sold products, the price will increase during that day. This means that the cache should be updated every few seconds, to update the price, and after 1 day, the whole cache should be refreshed with new products. Suppose that price setting and product selections are in the database, updated by some back-end application, and we need the new data in our frontend application and we want to cache it.

All this can be done with this simple class :

import java.util.concurrent.TimeUnit;
import javax.ejb.EJB;
import javax.ejb.Singleton;
import be.iadvise.dao.DatabaseDAO;
import be.iadvise.entities.Product;

public class ProductCache {

 DatabaseDAO databaseDAO;
 private static final Integer REFRESH_PRODUCT_AFTER_5_SECONDS = 5;
 private static final Integer EXPIRE_PRODUCT_AFTER_1_DAY = 1;
 private final LoadingCache<String, Optional<Product>> cache;

 public ProductCache() {
      cache = CacheBuilder.newBuilder()
           .expireAfterWrite(EXPIRE_PRODUCT_AFTER_1_DAY, TimeUnit.DAYS)
           .refreshAfterWrite(REFRESH_PRODUCT_AFTER_5_SECONDS, TimeUnit.SECONDS)
           .build( new CacheLoader<String, Optional<Product>>() {
                 public Optional<Product> load( String productId ) throws Exception {
                     return loadCache(productId);

 public Optional<Product> getEntry( String productId ) {
      return cache.getUnchecked( productId );

 private Optional<Product> loadCache(String productId) {
      Product product = databaseDAO.getProduct(productId);
      return Optional.fromNullable(product);


  1. In the constructor, we build the cache using the CacheLoader, defining the refresh mechanism. In our example we define 2 rules :
    - expireAfterWrite : after this period, the object will be evicted from the cache, and replaced the next time it is requested.
    - refreshAfterWrite : after this period, the object will be refreshed using the loadCache method. (with our new price)
  2. getEntry(String productId) method : will return the object with given key. So in this example, the cache is not loaded all at once, but only when the object is needed.
  3. loadCache(String productId) : will load the product and add it to the cache, or replace it if it’s already there and needs to be refreshed.

That’s all there is to it !

A few other remarks on the code

  1. There are other mechanism like expire/refresh AfterRead, which will time only from the last read, or let the cache hold only a certain no. of objects,…
  2. This code is implemented as a session bean. To make a singleton, I’m using EJB 3 annotation @Singleton. Because I only want 1 cache in my application
  3. My DAO is also injected using the @EJB annotation
  4. The LoadingCache does not want any null objects in the map (returns an error), so I’m using the Guava ‘Optional’ class here. This is basically a wrapper for my object and used to check if there is a value for my product id or not. So if someone uses a wrong productId, my cache will indicate that there is no product for this id, and I don’t have to go to the database every time it is requested.

To conclude:

Programming a caching mechanism in a JEE environment is not as trivial as it may seem. Testing it in a multithreaded environment is even more difficult. The caching classes of Guave gives you ready-to-use solution. It’s programmed, tested and used by Google, so I think we can say in all honesty : this is proven technology.

A remark on deploying on Weblogic 12c:

Weblogic also uses the Guava libraries, but an older version. This causes following error on deployment :



Adding the following to your weblogic-application.xml will solve the problem (force weblogic to use your deployed Guava libraries :


Guava libraries run under Apache license, more info/download can be found on :

Have fun !

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