A quick class to provide a lightweight cache wrapper on top of the ConcurrentHashMap class
This is my attempt at a lightweight caching type. There is probably a better built in implementation, but since I like to make things more difficult for myself, I created one on my own! This was created as an extension on the ConcurrentHashMap class, in an effort to provide an upper bound for the number of objects allowed. In addition to this, caches can reference transform functions that allow transparent data manipulation upon retrieval. Sorted cache natively purges based on least computationally expensive elements, in the case that a transform is defined.
Use this in maven projects by adding this to your repositories,
<repositories>
<repository>
<id>jitpack.io</id>
<url>https://jitpack.io</url>
</repository>
</repositories>
and this to your dependencies
<dependency>
<groupId>com.github.jbharter</groupId>
<artifactId>JCache</artifactId>
<version>1.0.0-STABLE</version>
</dependency>
Alternately, you can build it yourself with Apache Maven.
git clone git@github.com:jbharter/JCache.git
cd JCache
mvn -U clean package
// Simple K -> K Cache
FlashCache<String,String> test = new FlashCache<>(/* Step Size */1L,/* max number of elements*/10L);
test.put(Arrays.asList("0","1","2","3","4","5","6","7","8","9","10","11","12"));
test.size() // == 10 --> Cache has an upper bound on it's size
// Simple K -> K cache with transform
FlashCache<String,String> test = new FlashCache<>();
test.setMapper(String::toUpperCase);
test.put("rand");
test.setMapper(String::toLowerCase);
test.put("OTHER");
test.get("rand") // == "RAND"
test.get("OTHER") // == "other"
// Simple K -> V Cache
FlashCache<String,Integer> test = new FlashCache<>(/* Step Size */1L,/* max number of elements*/10L);
test.setMapper(Integer::parseInt);
test.put(Arrays.asList("0","1","2","3","4","5","6","7","8","9","10","11","12"));
test.get("3") == 3 // String key type maps to Integer Value type. The upper bound is also still imposed.
For a slightly more exotic cache, you can specify any transform you like, and when you approach the memory bounds, the cache will create space by purging the least computationally expensive elements.
// Compute Complexity Sorted K -> K Cache with transform
SortedCache<String,String> test = new SortedCache<>();
test.setMapper(String::trim);
test.put(Arrays.asList("0","1","2","3","4","5","6","7","8","9","10","11","12"));
test.setMapper(str -> {
try {
Thread.sleep(1000);
return "fancy func";
} catch (InterruptedException e) {
e.printStackTrace();
return "fail";
}
});
test.poll() // != "fancy func" --> poll pops the least computationally expensive element in the cache